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Feasibility of RACT for 3D dose measurement and range verification in a water phantom

Purpose: The objective of this study is to establish the feasibility of using radiation-induced acoustics to measure the range and Bragg peak dose from a pulsed proton beam. Simulation studies implementing a prototype scanner design based on computed tomographic methods were performed to investigate the sensitivity to proton range and integral dose. Methods: Derived from thermodynamic wave equation, the pressure signals generated from the dose deposited from a pulsed proton beam with a 1 cm lateral beam width and a range of 16, 20, and 27 cm in water using Monte Carlo methods were simulated. The resulting dosimetric images were reconstructed implementing a 3D filtered backprojection algorithm and the pressure signals acquired from a 71-transducer array with a cylindrical geometry (30 × 40 cm) rotated over 2π about its central axis. Dependencies on the detector bandwidth and proton beam pulse width were performed, after which, different noise levels were added to the detector signals (using 1 μs pulse width and a 0.5 MHz cutoff frequency/hydrophone) to investigate the statistical and systematic errors in the proton range (at 20 cm) and Bragg peak dose (of 1 cGy). Results: The reconstructed radioacoustic computed tomographic image intensity was shown to be linearly correlated to the dose within the Bragg peak. And, based on noise dependent studies, a detector sensitivity of 38 mPa was necessary to determine the proton range to within 1.0 mm (full-width at half-maximum) (systematic error < 150 μm) for a 1 cGy Bragg peak dose, where the integral dose within the Bragg peak was measured to within 2%. For existing hydrophone detector sensitivities, a Bragg peak dose of 1.6 cGy is possible. Conclusions: This study demonstrates that computed tomographic scanner based on ionizing radiation-induced acoustics can be used to verify dose distribution and proton range with centi-Gray sensitivity. Realizing this technology into the clinic has the potential to significantly impact beam commissioning, treatment verification during particle beam therapy and image guided techniques.

07 ISOTOPE AND RADIATION SOURCES↗

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗

TU-EF-BRA-00: MR Basics I

NMR, and Proton Density MRI of the 1D Patient - Anthony Wolbarst Net Voxel Magnetization, m(x,t). T1-MRI; The MRI Device - Lisa Lemen ‘Classical’ NMR; FID Imaging in 1D via k-Space - Nathan Yanasak Spin-Echo; S-E/Spin Warp in a 2D Slice - Ronald Price Magnetic resonance imaging not only reveals the structural, anatomic details of the body, as does CT, but also it can provide information on the physiological status and pathologies of its tissues, like nuclear medicine. It can display high-quality slice and 3D images of organs and vessels viewed from any perspective, with resolution better than 1 mm. MRI is perhaps most extraordinary and notable for the plethora of ways in which it can create unique forms of image contrast, reflective of fundamentally different biophysical phenomena. As with ultrasound, there is no risk from ionizing radiation to the patient or staff, since no X-rays or radioactive nuclei are involved. Instead, MRI harnesses magnetic fields and radio waves to probe the stable nuclei of the ordinary hydrogen atoms (isolated protons) occurring in water and lipid molecules within and around cells. MRI consists, in essence, of creating spatial maps of the electromagnetic environments around these hydrogen nuclei. Spatial variations in the proton milieus can be related to clinical differences in the biochemical and physiological properties and conditions of the associated tissues. Imaging of proton density (PD), and of the tissue proton spin relaxation times known as T1 and T2, all can reveal important clinical information, but they do so with approaches so dissimilar from one another that each is chosen for only certain clinical situations. T1 and T2 in a voxel are determined by different aspects of the rotations and other motions of the water and lipid molecules involved, as constrained by the local biophysical surroundings within and between its cells – and they, in turn, depend on the type of tissue and its state of health. Three other common applications of MRI exploit its capability to detect and image distinct movements of fluids: MR angiography (MRA), which rivals CT angiography but often requires no contrast medium, monitors the bulk flow of blood; functional MRI (f MRI), distinguishes the perfusion of oxygenated blood from that of de-oxygenated, and lights up parts of the brain that are activated by a stimulus, rather like PET; and diffusion tensor imaging (DTI) indicates the diffusion of free water along tracts of axons, thereby bringing nerve trunks into view. There are variants on all of these themes, and on others as well. Magnetic Resonance Spectroscopy (MRS), for example, can perform non-invasive ‘virtual biopsies’ that allow identification of certain cancers and other lesions. And an MRI-guided needle biopsy can sample brain tissue from a region only millimeters in dimensions. MRI, however, involves deeper and more complex aspects of physics, technology, and biology than do most other imaging modalities, and it is widely considered to be correspondingly more difficult to learn. We could probably cover all of this rather comprehensively if we had 50 hours available rather than 2 ̶ but, to paraphrase a former Secretary of Defense, you tell your story in the time you have allotted. The four presenters and another physicist, Kevin King from GE, have combined their efforts to co-author a single slide show that describes essentials of MRI as simply as possible. It is obviously far from thorough, but hopefully it will succeed in explaining some of the basics in a simplified but still valid fashion; in providing a taste of the numerous capabilities and complexities of the modality; and in whetting your appetite to learn more. Part I. NMR, and Proton Density MRI of the 1D Patient (Wolbarst), begins with an introductory case study that illustrates a half dozen ways in which MRI provides valuable clinical information. It then explores the nuclear magnetic resonance (NMR) phenomenon, which underlies MRI. NMR can be introduced with either of two approaches. In the first, one thinks (loosely) of the nuclei of hydrogen atoms as (rotating and charged and therefore) magnetic objects, whose spin-axes tend to align in a strong external magnetic field, much like a compass needle. As with the Bohr atom, this spin-up/spin-down picture is a highly abridged version of the full quantum mechanical treatment, but still it leads to some useful, legitimate pictures of the NMR process occurring within a voxel: When RF photons of the correct (Larmor) frequency elevate protons in a fixed magnetic field out of their lower-energy spin state into the upper, the NMR phenomenon is indicated by the detectable absorption of RF power. With the addition of a linear gradient field along a multi-voxel, one-dimensional patient/phantom, as well, we can determine the water content of each compartment – an example of a real MRI study, albeit in 1D. Part I concludes with a discussion of the net magnetization at position x, m0(x), under conditions of dynamic thermal equilibrium, which leads into: Part II. Net Voxel Magnetization, m(x,t); T1-MRI; The MRI Device (Lemen), investigates the biophysics of the form of proton spin relaxation process characterized by the time T1. It then moves on to the creation of an MR image that displays the spatial variation in the values of this clinically relevant parameter, again in 1D. Finally, the design and workings of a clinical MRI machine are sketched, in preparation for: Part III. ‘Classical’ NMR; FID Imaging in 1D via k-Space (Yanasak) presents the second standard approach to NMR and MRI, the classical model. It focuses on the time dependence of the net nuclear magnetization, m(x,t), the overall magnetic field generated by the cohort of protons in the voxel at position x. Quite remarkably, this nuclear net magnetization itself acts in a strong magnetic field like a gyroscope in a gravitational field. This tack is better for explaining Free Induction Decay (FID), which involves a brief introduction to the Fourier transform and k-space. This leads to conventional Spin-Echo (S-E) reconstruction techniques for creating clinical images from raw data, and sets the stage for: Part IV. Spin-Echo; S-E / Spin Warp in a 2D Slice (Price) discusses application of the S- E sequence of radiofrequency pulses and gradient magnetic fields to the 1D patient. T2 is introduced but not explained. This Part also considers how to manipulate the image acquisition parameters so as to generate clinical pictures with contrast dominated by spatial variations in PD, T1, or T2. We conclude by demonstrating the spin-warp approach to imaging in 2D with a simple 2×2, 4-voxel example. Much of this material is presented in more detail in the chapter “MRI of the One-dimensional Patient, Part I”, in Advances in Medical Physics, Vol 5 (2014). Copies are on display at the Medical Physics Publishing booth. Learning Objectives: The participant will learn about the processes of NMR and T1 spin relaxation in a tissue voxel in a uniform magnetic field. The participant will learn about combining spin-up/spin-down NMR and T1 processes with a linear gradient to effect frequency-encoding of voxel spatial position. This approach can be used to create proton density and T1 MRI maps, respectively, of the contents of multi-voxel 1D phantoms. The participant will learn about how the ‘classical’ model of NMR it can generate Free Induction Decay (FID) images of 1D phantoms, which involves the use of the Fourier transform in k-space. This can lead simply into standard Spin-Echo images. The participant will learn about extending Spin-Echo imaging into 2 and more dimensions.

60 APPLIED LIFE SCIENCES↗

TU-EF-BRA-01: NMR and Proton Density MRI of the 1D Patient

NMR, and Proton Density MRI of the 1D Patient - Anthony Wolbarst Net Voxel Magnetization, m(x,t). T1-MRI; The MRI Device - Lisa Lemen ‘Classical’ NMR; FID Imaging in 1D via k-Space - Nathan Yanasak Spin-Echo; S-E/Spin Warp in a 2D Slice - Ronald Price Magnetic resonance imaging not only reveals the structural, anatomic details of the body, as does CT, but also it can provide information on the physiological status and pathologies of its tissues, like nuclear medicine. It can display high-quality slice and 3D images of organs and vessels viewed from any perspective, with resolution better than 1 mm. MRI is perhaps most extraordinary and notable for the plethora of ways in which it can create unique forms of image contrast, reflective of fundamentally different biophysical phenomena. As with ultrasound, there is no risk from ionizing radiation to the patient or staff, since no X-rays or radioactive nuclei are involved. Instead, MRI harnesses magnetic fields and radio waves to probe the stable nuclei of the ordinary hydrogen atoms (isolated protons) occurring in water and lipid molecules within and around cells. MRI consists, in essence, of creating spatial maps of the electromagnetic environments around these hydrogen nuclei. Spatial variations in the proton milieus can be related to clinical differences in the biochemical and physiological properties and conditions of the associated tissues. Imaging of proton density (PD), and of the tissue proton spin relaxation times known as T1 and T2, all can reveal important clinical information, but they do so with approaches so dissimilar from one another that each is chosen for only certain clinical situations. T1 and T2 in a voxel are determined by different aspects of the rotations and other motions of the water and lipid molecules involved, as constrained by the local biophysical surroundings within and between its cells – and they, in turn, depend on the type of tissue and its state of health. Three other common applications of MRI exploit its capability to detect and image distinct movements of fluids: MR angiography (MRA), which rivals CT angiography but often requires no contrast medium, monitors the bulk flow of blood; functional MRI ( f MRI), distinguishes the perfusion of oxygenated blood from that of de-oxygenated, and lights up parts of the brain that are activated by a stimulus, rather like PET; and diffusion tensor imaging (DTI) indicates the diffusion of free water along tracts of axons, thereby bringing nerve trunks into view. There are variants on all of these themes, and on others as well. Magnetic Resonance Spectroscopy (MRS), for example, can perform non-invasive ‘virtual biopsies’ that allow identification of certain cancers and other lesions. And an MRI-guided needle biopsy can sample brain tissue from a region only millimeters in dimensions. MRI, however, involves deeper and more complex aspects of physics, technology, and biology than do most other imaging modalities, and it is widely considered to be correspondingly more difficult to learn. We could probably cover all of this rather comprehensively if we had 50 hours available rather than 2 ̶ but, to paraphrase a former Secretary of Defense, you tell your story in the time you have allotted. The four presenters and another physicist, Kevin King from GE, have combined their efforts to co-author a single slide show that describes essentials of MRI as simply as possible. It is obviously far from thorough, but hopefully it will succeed in explaining some of the basics in a simplified but still valid fashion; in providing a taste of the numerous capabilities and complexities of the modality; and in whetting your appetite to learn more. Part I. NMR, and Proton Density MRI of the 1D Patient (Wolbarst), begins with an introductory case study that illustrates a half dozen ways in which MRI provides valuable clinical information. It then explores the nuclear magnetic resonance (NMR) phenomenon, which underlies MRI. NMR can be introduced with either of two approaches. In the first, one thinks (loosely) of the nuclei of hydrogen atoms as (rotating and charged and therefore) magnetic objects, whose spin-axes tend to align in a strong external magnetic field, much like a compass needle. As with the Bohr atom, this spin-up/spin-down picture is a highly abridged version of the full quantum mechanical treatment, but still it leads to some useful, legitimate pictures of the NMR process occurring within a voxel: When RF photons of the correct (Larmor) frequency elevate protons in a fixed magnetic field out of their lower-energy spin state into the upper, the NMR phenomenon is indicated by the detectable absorption of RF power. With the addition of a linear gradient field along a multi-voxel, one-dimensional patient/phantom, as well, we can determine the water content of each compartment – an example of a real MRI study, albeit in 1D. Part I concludes with a discussion of the net magnetization at position x, m0(x), under conditions of dynamic thermal equilibrium, which leads into: Part II. Net Voxel Magnetization, m(x,t); T1-MRI; The MRI Device (Lemen), investigates the biophysics of the form of proton spin relaxation process characterized by the time T1. It then moves on to the creation of an MR image that displays the spatial variation in the values of this clinically relevant parameter, again in 1D. Finally, the design and workings of a clinical MRI machine are sketched, in preparation for: Part III. ‘Classical’ NMR; FID Imaging in 1D via k-Space (Yanasak) presents the second standard approach to NMR and MRI, the classical model. It focuses on the time dependence of the net nuclear magnetization, m(x,t), the overall magnetic field generated by the cohort of protons in the voxel at position x. Quite remarkably, this nuclear net magnetization itself acts in a strong magnetic field like a gyroscope in a gravitational field. This tack is better for explaining Free Induction Decay (FID), which involves a brief introduction to the Fourier transform and k-space. This leads to conventional Spin-Echo (S-E) reconstruction techniques for creating clinical images from raw data, and sets the stage for: Part IV. Spin-Echo; S-E / Spin Warp in a 2D Slice (Price) discusses application of the S- E sequence of radiofrequency pulses and gradient magnetic fields to the 1D patient. T2 is introduced but not explained. This Part also considers how to manipulate the image acquisition parameters so as to generate clinical pictures with contrast dominated by spatial variations in PD, T1, or T2. We conclude by demonstrating the spin-warp approach to imaging in 2D with a simple 2×2, 4-voxel example. Much of this material is presented in more detail in the chapter “MRI of the One-dimensional Patient, Part I”, in Advances in Medical Physics, Vol 5 (2014). Copies are on display at the Medical Physics Publishing booth. Learning Objectives: The participant will learn about the processes of NMR and T1 spin relaxation in a tissue voxel in a uniform magnetic field. The participant will learn about combining spin-up/spin-down NMR and T1 processes with a linear gradient to effect frequency-encoding of voxel spatial position. This approach can be used to create proton density and T1 MRI maps, respectively, of the contents of multi-voxel 1D phantoms. The participant will learn about how the ‘classical’ model of NMR it can generate Free Induction Decay (FID) images of 1D phantoms, which involves the use of the Fourier transform in k-space. This can lead simply into standard Spin-Echo images. The participant will learn about extending Spin-Echo imaging into 2 and more dimensions.

60 APPLIED LIFE SCIENCES↗

TU-EF-BRA-02: Longitudinal Proton Spin Relaxation and T1-Imaging

NMR, and Proton Density MRI of the 1D Patient - Anthony Wolbarst Net Voxel Magnetization, m(x,t). T1-MRI; The MRI Device - Lisa Lemen ‘Classical’ NMR; FID Imaging in 1D via k-Space - Nathan Yanasak Spin-Echo; S-E/Spin Warp in a 2D Slice - Ronald Price Magnetic resonance imaging not only reveals the structural, anatomic details of the body, as does CT, but also it can provide information on the physiological status and pathologies of its tissues, like nuclear medicine. It can display high-quality slice and 3D images of organs and vessels viewed from any perspective, with resolution better than 1 mm. MRI is perhaps most extraordinary and notable for the plethora of ways in which it can create unique forms of image contrast, reflective of fundamentally different biophysical phenomena. As with ultrasound, there is no risk from ionizing radiation to the patient or staff, since no X-rays or radioactive nuclei are involved. Instead, MRI harnesses magnetic fields and radio waves to probe the stable nuclei of the ordinary hydrogen atoms (isolated protons) occurring in water and lipid molecules within and around cells. MRI consists, in essence, of creating spatial maps of the electromagnetic environments around these hydrogen nuclei. Spatial variations in the proton milieus can be related to clinical differences in the biochemical and physiological properties and conditions of the associated tissues. Imaging of proton density (PD), and of the tissue proton spin relaxation times known as T1 and T2, all can reveal important clinical information, but they do so with approaches so dissimilar from one another that each is chosen for only certain clinical situations. T1 and T2 in a voxel are determined by different aspects of the rotations and other motions of the water and lipid molecules involved, as constrained by the local biophysical surroundings within and between its cells – and they, in turn, depend on the type of tissue and its state of health. Three other common applications of MRI exploit its capability to detect and image distinct movements of fluids: MR angiography (MRA), which rivals CT angiography but often requires no contrast medium, monitors the bulk flow of blood; functional MRI ( f MRI), distinguishes the perfusion of oxygenated blood from that of de-oxygenated, and lights up parts of the brain that are activated by a stimulus, rather like PET; and diffusion tensor imaging (DTI) indicates the diffusion of free water along tracts of axons, thereby bringing nerve trunks into view. There are variants on all of these themes, and on others as well. Magnetic Resonance Spectroscopy (MRS), for example, can perform non-invasive ‘virtual biopsies’ that allow identification of certain cancers and other lesions. And an MRI-guided needle biopsy can sample brain tissue from a region only millimeters in dimensions. MRI, however, involves deeper and more complex aspects of physics, technology, and biology than do most other imaging modalities, and it is widely considered to be correspondingly more difficult to learn. We could probably cover all of this rather comprehensively if we had 50 hours available rather than 2 ̶ but, to paraphrase a former Secretary of Defense, you tell your story in the time you have allotted. The four presenters and another physicist, Kevin King from GE, have combined their efforts to co-author a single slide show that describes essentials of MRI as simply as possible. It is obviously far from thorough, but hopefully it will succeed in explaining some of the basics in a simplified but still valid fashion; in providing a taste of the numerous capabilities and complexities of the modality; and in whetting your appetite to learn more. Part I. NMR, and Proton Density MRI of the 1D Patient (Wolbarst), begins with an introductory case study that illustrates a half dozen ways in which MRI provides valuable clinical information. It then explores the nuclear magnetic resonance (NMR) phenomenon, which underlies MRI. NMR can be introduced with either of two approaches. In the first, one thinks (loosely) of the nuclei of hydrogen atoms as (rotating and charged and therefore) magnetic objects, whose spin-axes tend to align in a strong external magnetic field, much like a compass needle. As with the Bohr atom, this spin-up/spin-down picture is a highly abridged version of the full quantum mechanical treatment, but still it leads to some useful, legitimate pictures of the NMR process occurring within a voxel: When RF photons of the correct (Larmor) frequency elevate protons in a fixed magnetic field out of their lower-energy spin state into the upper, the NMR phenomenon is indicated by the detectable absorption of RF power. With the addition of a linear gradient field along a multi-voxel, one-dimensional patient/phantom, as well, we can determine the water content of each compartment – an example of a real MRI study, albeit in 1D. Part I concludes with a discussion of the net magnetization at position x, m0(x), under conditions of dynamic thermal equilibrium, which leads into: Part II. Net Voxel Magnetization, m(x,t); T1-MRI; The MRI Device (Lemen), investigates the biophysics of the form of proton spin relaxation process characterized by the time T1. It then moves on to the creation of an MR image that displays the spatial variation in the values of this clinically relevant parameter, again in 1D. Finally, the design and workings of a clinical MRI machine are sketched, in preparation for: Part III. ‘Classical’ NMR; FID Imaging in 1D via k-Space (Yanasak) presents the second standard approach to NMR and MRI, the classical model. It focuses on the time dependence of the net nuclear magnetization, m(x,t), the overall magnetic field generated by the cohort of protons in the voxel at position x. Quite remarkably, this nuclear net magnetization itself acts in a strong magnetic field like a gyroscope in a gravitational field. This tack is better for explaining Free Induction Decay (FID), which involves a brief introduction to the Fourier transform and k-space. This leads to conventional Spin-Echo (S-E) reconstruction techniques for creating clinical images from raw data, and sets the stage for: Part IV. Spin-Echo; S-E / Spin Warp in a 2D Slice (Price) discusses application of the S- E sequence of radiofrequency pulses and gradient magnetic fields to the 1D patient. T2 is introduced but not explained. This Part also considers how to manipulate the image acquisition parameters so as to generate clinical pictures with contrast dominated by spatial variations in PD, T1, or T2. We conclude by demonstrating the spin-warp approach to imaging in 2D with a simple 2×2, 4-voxel example. Much of this material is presented in more detail in the chapter “MRI of the One-dimensional Patient, Part I”, in Advances in Medical Physics, Vol 5 (2014). Copies are on display at the Medical Physics Publishing booth. Learning Objectives: The participant will learn about the processes of NMR and T1 spin relaxation in a tissue voxel in a uniform magnetic field. The participant will learn about combining spin-up/spin-down NMR and T1 processes with a linear gradient to effect frequency-encoding of voxel spatial position. This approach can be used to create proton density and T1 MRI maps, respectively, of the contents of multi-voxel 1D phantoms. The participant will learn about how the ‘classical’ model of NMR it can generate Free Induction Decay (FID) images of 1D phantoms, which involves the use of the Fourier transform in k-space. This can lead simply into standard Spin-Echo images. The participant will learn about extending Spin-Echo imaging into 2 and more dimensions.

60 APPLIED LIFE SCIENCES↗

TU-EF-BRA-03: Free Induction Decay (without the Decay) and Spin-Echo Imaging

NMR, and Proton Density MRI of the 1D Patient - Anthony Wolbarst Net Voxel Magnetization, m(x,t). T1-MRI; The MRI Device - Lisa Lemen ‘Classical’ NMR; FID Imaging in 1D via k-Space - Nathan Yanasak Spin-Echo; S-E/Spin Warp in a 2D Slice - Ronald Price Magnetic resonance imaging not only reveals the structural, anatomic details of the body, as does CT, but also it can provide information on the physiological status and pathologies of its tissues, like nuclear medicine. It can display high-quality slice and 3D images of organs and vessels viewed from any perspective, with resolution better than 1 mm. MRI is perhaps most extraordinary and notable for the plethora of ways in which it can create unique forms of image contrast, reflective of fundamentally different biophysical phenomena. As with ultrasound, there is no risk from ionizing radiation to the patient or staff, since no X-rays or radioactive nuclei are involved. Instead, MRI harnesses magnetic fields and radio waves to probe the stable nuclei of the ordinary hydrogen atoms (isolated protons) occurring in water and lipid molecules within and around cells. MRI consists, in essence, of creating spatial maps of the electromagnetic environments around these hydrogen nuclei. Spatial variations in the proton milieus can be related to clinical differences in the biochemical and physiological properties and conditions of the associated tissues. Imaging of proton density (PD), and of the tissue proton spin relaxation times known as T1 and T2, all can reveal important clinical information, but they do so with approaches so dissimilar from one another that each is chosen for only certain clinical situations. T1 and T2 in a voxel are determined by different aspects of the rotations and other motions of the water and lipid molecules involved, as constrained by the local biophysical surroundings within and between its cells – and they, in turn, depend on the type of tissue and its state of health. Three other common applications of MRI exploit its capability to detect and image distinct movements of fluids: MR angiography (MRA), which rivals CT angiography but often requires no contrast medium, monitors the bulk flow of blood; functional MRI ( f MRI), distinguishes the perfusion of oxygenated blood from that of de-oxygenated, and lights up parts of the brain that are activated by a stimulus, rather like PET; and diffusion tensor imaging (DTI) indicates the diffusion of free water along tracts of axons, thereby bringing nerve trunks into view. There are variants on all of these themes, and on others as well. Magnetic Resonance Spectroscopy (MRS), for example, can perform non-invasive ‘virtual biopsies’ that allow identification of certain cancers and other lesions. And an MRI-guided needle biopsy can sample brain tissue from a region only millimeters in dimensions. MRI, however, involves deeper and more complex aspects of physics, technology, and biology than do most other imaging modalities, and it is widely considered to be correspondingly more difficult to learn. We could probably cover all of this rather comprehensively if we had 50 hours available rather than 2 ̶ but, to paraphrase a former Secretary of Defense, you tell your story in the time you have allotted. The four presenters and another physicist, Kevin King from GE, have combined their efforts to co-author a single slide show that describes essentials of MRI as simply as possible. It is obviously far from thorough, but hopefully it will succeed in explaining some of the basics in a simplified but still valid fashion; in providing a taste of the numerous capabilities and complexities of the modality; and in whetting your appetite to learn more. Part I. NMR, and Proton Density MRI of the 1D Patient (Wolbarst), begins with an introductory case study that illustrates a half dozen ways in which MRI provides valuable clinical information. It then explores the nuclear magnetic resonance (NMR) phenomenon, which underlies MRI. NMR can be introduced with either of two approaches. In the first, one thinks (loosely) of the nuclei of hydrogen atoms as (rotating and charged and therefore) magnetic objects, whose spin-axes tend to align in a strong external magnetic field, much like a compass needle. As with the Bohr atom, this spin-up/spin-down picture is a highly abridged version of the full quantum mechanical treatment, but still it leads to some useful, legitimate pictures of the NMR process occurring within a voxel: When RF photons of the correct (Larmor) frequency elevate protons in a fixed magnetic field out of their lower-energy spin state into the upper, the NMR phenomenon is indicated by the detectable absorption of RF power. With the addition of a linear gradient field along a multi-voxel, one-dimensional patient/phantom, as well, we can determine the water content of each compartment – an example of a real MRI study, albeit in 1D. Part I concludes with a discussion of the net magnetization at position x, m0(x), under conditions of dynamic thermal equilibrium, which leads into: Part II. Net Voxel Magnetization, m(x,t); T1-MRI; The MRI Device (Lemen), investigates the biophysics of the form of proton spin relaxation process characterized by the time T1. It then moves on to the creation of an MR image that displays the spatial variation in the values of this clinically relevant parameter, again in 1D. Finally, the design and workings of a clinical MRI machine are sketched, in preparation for: Part III. ‘Classical’ NMR; FID Imaging in 1D via k-Space (Yanasak) presents the second standard approach to NMR and MRI, the classical model. It focuses on the time dependence of the net nuclear magnetization, m(x,t), the overall magnetic field generated by the cohort of protons in the voxel at position x. Quite remarkably, this nuclear net magnetization itself acts in a strong magnetic field like a gyroscope in a gravitational field. This tack is better for explaining Free Induction Decay (FID), which involves a brief introduction to the Fourier transform and k-space. This leads to conventional Spin-Echo (S-E) reconstruction techniques for creating clinical images from raw data, and sets the stage for: Part IV. Spin-Echo; S-E / Spin Warp in a 2D Slice (Price) discusses application of the S- E sequence of radiofrequency pulses and gradient magnetic fields to the 1D patient. T2 is introduced but not explained. This Part also considers how to manipulate the image acquisition parameters so as to generate clinical pictures with contrast dominated by spatial variations in PD, T1, or T2. We conclude by demonstrating the spin-warp approach to imaging in 2D with a simple 2×2, 4-voxel example. Much of this material is presented in more detail in the chapter “MRI of the One-dimensional Patient, Part I”, in Advances in Medical Physics, Vol 5 (2014). Copies are on display at the Medical Physics Publishing booth. Learning Objectives: The participant will learn about the processes of NMR and T1 spin relaxation in a tissue voxel in a uniform magnetic field. The participant will learn about combining spin-up/spin-down NMR and T1 processes with a linear gradient to effect frequency-encoding of voxel spatial position. This approach can be used to create proton density and T1 MRI maps, respectively, of the contents of multi-voxel 1D phantoms. The participant will learn about how the ‘classical’ model of NMR it can generate Free Induction Decay (FID) images of 1D phantoms, which involves the use of the Fourier transform in k-space. This can lead simply into standard Spin-Echo images. The participant will learn about extending Spin-Echo imaging into 2 and more dimensions.

60 APPLIED LIFE SCIENCES↗

TU-EF-BRA-04: Into 2, 3, and 4 Dimensions

NMR, and Proton Density MRI of the 1D Patient - Anthony Wolbarst Net Voxel Magnetization, m(x,t). T1-MRI; The MRI Device - Lisa Lemen ‘Classical’ NMR; FID Imaging in 1D via k-Space - Nathan Yanasak Spin-Echo; S-E/Spin Warp in a 2D Slice - Ronald Price Magnetic resonance imaging not only reveals the structural, anatomic details of the body, as does CT, but also it can provide information on the physiological status and pathologies of its tissues, like nuclear medicine. It can display high-quality slice and 3D images of organs and vessels viewed from any perspective, with resolution better than 1 mm. MRI is perhaps most extraordinary and notable for the plethora of ways in which it can create unique forms of image contrast, reflective of fundamentally different biophysical phenomena. As with ultrasound, there is no risk from ionizing radiation to the patient or staff, since no X-rays or radioactive nuclei are involved. Instead, MRI harnesses magnetic fields and radio waves to probe the stable nuclei of the ordinary hydrogen atoms (isolated protons) occurring in water and lipid molecules within and around cells. MRI consists, in essence, of creating spatial maps of the electromagnetic environments around these hydrogen nuclei. Spatial variations in the proton milieus can be related to clinical differences in the biochemical and physiological properties and conditions of the associated tissues. Imaging of proton density (PD), and of the tissue proton spin relaxation times known as T1 and T2, all can reveal important clinical information, but they do so with approaches so dissimilar from one another that each is chosen for only certain clinical situations. T1 and T2 in a voxel are determined by different aspects of the rotations and other motions of the water and lipid molecules involved, as constrained by the local biophysical surroundings within and between its cells – and they, in turn, depend on the type of tissue and its state of health. Three other common applications of MRI exploit its capability to detect and image distinct movements of fluids: MR angiography (MRA), which rivals CT angiography but often requires no contrast medium, monitors the bulk flow of blood; functional MRI ( f MRI), distinguishes the perfusion of oxygenated blood from that of de-oxygenated, and lights up parts of the brain that are activated by a stimulus, rather like PET; and diffusion tensor imaging (DTI) indicates the diffusion of free water along tracts of axons, thereby bringing nerve trunks into view. There are variants on all of these themes, and on others as well. Magnetic Resonance Spectroscopy (MRS), for example, can perform non-invasive ‘virtual biopsies’ that allow identification of certain cancers and other lesions. And an MRI-guided needle biopsy can sample brain tissue from a region only millimeters in dimensions. MRI, however, involves deeper and more complex aspects of physics, technology, and biology than do most other imaging modalities, and it is widely considered to be correspondingly more difficult to learn. We could probably cover all of this rather comprehensively if we had 50 hours available rather than 2 ̶ but, to paraphrase a former Secretary of Defense, you tell your story in the time you have allotted. The four presenters and another physicist, Kevin King from GE, have combined their efforts to co-author a single slide show that describes essentials of MRI as simply as possible. It is obviously far from thorough, but hopefully it will succeed in explaining some of the basics in a simplified but still valid fashion; in providing a taste of the numerous capabilities and complexities of the modality; and in whetting your appetite to learn more. Part I. NMR, and Proton Density MRI of the 1D Patient (Wolbarst), begins with an introductory case study that illustrates a half dozen ways in which MRI provides valuable clinical information. It then explores the nuclear magnetic resonance (NMR) phenomenon, which underlies MRI. NMR can be introduced with either of two approaches. In the first, one thinks (loosely) of the nuclei of hydrogen atoms as (rotating and charged and therefore) magnetic objects, whose spin-axes tend to align in a strong external magnetic field, much like a compass needle. As with the Bohr atom, this spin-up/spin-down picture is a highly abridged version of the full quantum mechanical treatment, but still it leads to some useful, legitimate pictures of the NMR process occurring within a voxel: When RF photons of the correct (Larmor) frequency elevate protons in a fixed magnetic field out of their lower-energy spin state into the upper, the NMR phenomenon is indicated by the detectable absorption of RF power. With the addition of a linear gradient field along a multi-voxel, one-dimensional patient/phantom, as well, we can determine the water content of each compartment – an example of a real MRI study, albeit in 1D. Part I concludes with a discussion of the net magnetization at position x, m0(x), under conditions of dynamic thermal equilibrium, which leads into: Part II. Net Voxel Magnetization, m(x,t); T1-MRI; The MRI Device (Lemen), investigates the biophysics of the form of proton spin relaxation process characterized by the time T1. It then moves on to the creation of an MR image that displays the spatial variation in the values of this clinically relevant parameter, again in 1D. Finally, the design and workings of a clinical MRI machine are sketched, in preparation for: Part III. ‘Classical’ NMR; FID Imaging in 1D via k-Space (Yanasak) presents the second standard approach to NMR and MRI, the classical model. It focuses on the time dependence of the net nuclear magnetization, m(x,t), the overall magnetic field generated by the cohort of protons in the voxel at position x. Quite remarkably, this nuclear net magnetization itself acts in a strong magnetic field like a gyroscope in a gravitational field. This tack is better for explaining Free Induction Decay (FID), which involves a brief introduction to the Fourier transform and k-space. This leads to conventional Spin-Echo (S-E) reconstruction techniques for creating clinical images from raw data, and sets the stage for: Part IV. Spin-Echo; S-E / Spin Warp in a 2D Slice (Price) discusses application of the S- E sequence of radiofrequency pulses and gradient magnetic fields to the 1D patient. T2 is introduced but not explained. This Part also considers how to manipulate the image acquisition parameters so as to generate clinical pictures with contrast dominated by spatial variations in PD, T1, or T2. We conclude by demonstrating the spin-warp approach to imaging in 2D with a simple 2×2, 4-voxel example. Much of this material is presented in more detail in the chapter “MRI of the One-dimensional Patient, Part I”, in Advances in Medical Physics, Vol 5 (2014). Copies are on display at the Medical Physics Publishing booth. Learning Objectives: The participant will learn about the processes of NMR and T1 spin relaxation in a tissue voxel in a uniform magnetic field. The participant will learn about combining spin-up/spin-down NMR and T1 processes with a linear gradient to effect frequency-encoding of voxel spatial position. This approach can be used to create proton density and T1 MRI maps, respectively, of the contents of multi-voxel 1D phantoms. The participant will learn about how the ‘classical’ model of NMR it can generate Free Induction Decay (FID) images of 1D phantoms, which involves the use of the Fourier transform in k-space. This can lead simply into standard Spin-Echo images. The participant will learn about extending Spin-Echo imaging into 2 and more dimensions.

60 APPLIED LIFE SCIENCES↗

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗

The 2017 terahertz science and technology roadmap

Science and technologies based on terahertz frequency electromagnetic radiation (100 GHz–30 THz) have developed rapidly over the last 30 years. For most of the 20th Century, terahertz radiation, then referred to as sub-millimeter wave or far-infrared radiation, was mainly utilized by astronomers and some spectroscopists. Following the development of laser based terahertz time-domain spectroscopy in the 1980s and 1990s the field of THz science and technology expanded rapidly, to the extent that it now touches many areas from fundamental science to 'real world' applications. For example THz radiation is being used to optimize materials for new solar cells, and may also be a key technology for the next generation of airport security scanners. While the field was emerging it was possible to keep track of all new developments, however now the field has grown so much that it is increasingly difficult to follow the diverse range of new discoveries and applications that are appearing. At this point in time, when the field of THz science and technology is moving from an emerging to a more established and interdisciplinary field, it is apt to present a roadmap to help identify the breadth and future directions of the field. The aim of this roadmap is to present a snapshot of the present state of THz science and technology in 2017, and provide an opinion on the challenges and opportunities that the future holds. To be able to achieve this aim, we have invited a group of international experts to write 18 sections that cover most of the key areas of THz science and technology. We hope that The 2017 Roadmap on THz science and technology will prove to be a useful resource by providing a wide ranging introduction to the capabilities of THz radiation for those outside or just entering the field as well as providing perspective and breadth for those who are well established. Lastly, we also feel that this review should serve as a useful guide for government and funding agencies.

42 ENGINEERING↗

Computational model for simulation small testing launcher, technical solution

The purpose of this paper is to present some aspects regarding the computational model and technical solutions for multistage suborbital launcher for testing (SLT) used to test spatial equipment and scientific measurements. The computational model consists in numerical simulation of SLT evolution for different start conditions. The launcher model presented will be with six degrees of freedom (6DOF) and variable mass. The results analysed will be the flight parameters and ballistic performances. The discussions area will focus around the technical possibility to realize a small multi-stage launcher, by recycling military rocket motors. From technical point of view, the paper is focused on national project 'Suborbital Launcher for Testing' (SLT), which is based on hybrid propulsion and control systems, obtained through an original design. Therefore, while classical suborbital sounding rockets are unguided and they use as propulsion solid fuel motor having an uncontrolled ballistic flight, SLT project is introducing a different approach, by proposing the creation of a guided suborbital launcher, which is basically a satellite launcher at a smaller scale, containing its main subsystems. This is why the project itself can be considered an intermediary step in the development of a wider range of launching systems based on hybrid propulsion technology, which may have a major impact in the future European launchers programs. SLT project, as it is shown in the title, has two major objectives: first, a short term objective, which consists in obtaining a suborbital launching system which will be able to go into service in a predictable period of time, and a long term objective that consists in the development and testing of some unconventional sub-systems which will be integrated later in the satellite launcher as a part of the European space program. This is why the technical content of the project must be carried out beyond the range of the existing suborbital vehicle programs towards the current technological necessities in the space field, especially the European one.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The onset of ion heating during magnetic reconnection with a strong guide field

The onset of the acceleration of ions during magnetic reconnection is explored via particle-in-cell simulations in the limit of a strong ambient guide field that self-consistently and simultaneously follow the motions of protons and α particles. Heating parallel to the local magnetic field during reconnection with a guide field is strongly reduced compared with the reconnection of anti-parallel magnetic fields. The dominant heating of thermal ions during guide field reconnection results from pickup behavior of ions during their entry into reconnection exhausts and dominantly produces heating perpendicular rather than parallel to the local magnetic field. Pickup behavior requires that the ion transit time across the exhaust boundary (with a transverse scale of the order of the ion sound Larmor radius) be short compared with the ion cyclotron period. This translates into a threshold in the strength of reconnecting magnetic field that favors the heating of ions with high mass-to-charge. A simulation with a broad initial current layer produces a reconnecting system in which the amplitude of the reconnecting magnetic field just upstream of the dissipation region increases with time as reconnection proceeds. The sharp onset of perpendicular heating when the pickup threshold is crossed is documented. A comparison of the time variation of the parallel and perpendicular ion heating with that predicted based on the strength of the reconnecting field establishes the scaling of ion heating with ambient parameters both below and above the pickup threshold. The relevance to observations of ion heating in the solar corona is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spin and orbital metallic magnetism in rhombohedral trilayer graphene

We provide a theoretical interpretation of the metallic broken spin-valley (flavor) symmetry states recently discovered in hole-doped rhombohedral trilayer (ABC) graphene in large electric displacement fields. Our conclusions about the phase diagram and phase transitions combine insights from ABC graphene electronic structure models and mean-field theory, and are guided by the precise magneto-oscillation Fermi-surface-area measurements of recent experiments. We find that the principle of momentum-space condensation plays a key role in determining Fermi-surface reconstructions enabled by broken flavor symmetries when the single-particle bands imply thin annular Fermi seas. The reconstructed Fermi sea consists of one large outer Fermi-surface-enclosed majority-flavor states in reciprocal-space area A maj and one or more small inner holelike Fermi-surface-enclosed minority-flavor states in A min that are primarily responsible for nematic order. The competing ground states (valley-Ising, valley-XY, and spin-polarized state) have different A maj /A min and exchange energy maximizes this ratio and selects valley-XY nematic metal as the lowest-energy state. Here, we discuss how the nematic pockets explain the observed fractionalization of quantum oscillation frequencies, and propose anisotropic transport and the nonlinear Hall effect as additional observables.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

TURBULENT MAGNETOHYDRODYNAMIC RECONNECTION MEDIATED BY THE PLASMOID INSTABILITY

It has been established that the Sweet–Parker current layer in high Lundquist number reconnection is unstable to the super-Alfvénic plasmoid instability. Past two-dimensional magnetohydrodynamic simulations have demonstrated that the plasmoid instability leads to a new regime where the Sweet–Parker current layer changes into a chain of plasmoids connected by secondary current sheets, and the averaged reconnection rate becomes nearly independent of the Lundquist number. In this work, a three-dimensional simulation with a guide field shows that the additional degree of freedom allows plasmoid instabilities to grow at oblique angles, which interact and lead to self-generated turbulent reconnection. The averaged reconnection rate in the self-generated turbulent state is of the order of a hundredth of the characteristic Alfvén speed, which is similar to the two-dimensional result but is an order of magnitude lower than the fastest reconnection rate reported in recent studies of externally driven three-dimensional turbulent reconnection. Kinematic and magnetic energy fluctuations both form elongated eddies along the direction of the local magnetic field, which is a signature of anisotropic magnetohydrodynamic turbulence. Both energy fluctuations satisfy power-law spectra in the inertial range, where the magnetic energy spectral index is in the range from −2.3 to −2.1, while the kinetic energy spectral index is slightly steeper, in the range from −2.5 to −2.3. The anisotropy of turbulence eddies is found to be nearly scale-independent, in contrast with the prediction of the Goldreich–Sridhar theory for anisotropic turbulence in a homogeneous plasma permeated by a uniform magnetic field.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraints for stellar electron-capture rates on 86 Kr via the 86 Kr(t, 3 He +γ) 86 Br reaction and the implications for core-collapse supernovae

Background: In the late stages of stellar core collapse just prior to core bounce, electron captures on medium-heavy nuclei drive deleptonization. Therefore, simulations require the use of accurate reaction rates. Nuclei with neutron number near N=50 above atomic number Z=28 play an important role. Rates presently used in astrophysical simulations rely primarily on a relatively simple single-state approximation. In order to improve the accuracy of the astrophysical simulations, experimental data are needed to test the electron-capture rates and to guide the development of better theoretical models and astrophysical simulations. Purpose: The purpose of the present work was to measure the Gamow-Teller transition strength from 86 Kr to 86 Br, to derive the stellar electron-capture rates based on the extracted strengths, and to compare the derived rates with rates based on shell-model and quasiparticle random-phase approximation (QRPA) Gamow-Teller strengths calculations, as well as the single-state approximation. An additional purpose was to test the impact of using improved electron-capture rates on the late evolution of core-collapse supernovae. Method: The Gamow-Teller strengths from 86 Kr were extracted from the 86 Kr(t, 3 He +γ) charge-exchange reaction at 115MeV/u. The electron-capture rates were calculated as a function of stellar density and temperature. Besides the case of 86 Kr, the electron-capture rates based on the QRPA calculations were calculated for 78 additional isotopes near N=50 above Z=28. The impact of using these rates instead of those based on the single-state approximation is studied in a spherically symmetrical simulation of core collapse just prior to bounce. Results: The derived electron-capture rates on 86 Kr from the experimental Gamow-Teller strength distribution are much smaller than the rates estimated based on the single-state approximation. Rates based on Gamow-Teller strengths estimated in shell-model and QRPA calculations are more accurate. The core-collapse supernova simulation with electron-capture rates based on the QRPA calculations indicate a significant reduction in the deleptonization during the collapse phase. Conclusions: It is important to utilize microscopic theoretical models that are tested by experimental data to constrain and estimate Gamow-Teller strengths and derived electron-capture rates for nuclei near N=50 that are inputs for astrophysical simulations of core-collapse supernovae and their multimessenger signals, such as the emission of neutrinos and gravitational waves.

79 ASTRONOMY AND ASTROPHYSICS↗

Effect of the solenoid in various conditions of the laser ion source at Brookhaven National Laboratory

In the laser ion source (LIS) at the Brookhaven National Laboratory (BNL), a solenoid is used to guide the laser ablation plasma and modulate the extracted beam current. Many types of ion species are guided. In some cases, the plasma plume is injected into the solenoid away from the solenoidal axis. To investigate the effects of the solenoid on the beam extracted from the plasma that has different properties, the beam current was measured in the setup of the LIS at the BNL. The beam current of Li, Al, Si, Fe, and Au increased when the magnetic field was applied. For most of the species the peak current and the total charge within a single beam pulse increased around 10 times with a magnetic field less than 100 G. In addition, for some species the rate of increase of the peak currents became smaller when the magnetic flux densities were larger than certain values depending on the species. In this case, the current waveforms were distorted. At the same magnetic field value, the field was more effective on lighter species than on heavier ones. When plasma was injected offset from the axis of the solenoid, peak current and total charge became half of those without offset. The experimental data are useful for the operation of the LIS at the BNL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science

FIVE TRANSFORMATIVE OPPORTUNITIES FOR DISCOVERY SCIENCE As a result of this effort, it has become clear that the progress made to date on the five Grand Challenges has created a springboard for seizing five new Transformative Opportunities that have the potential to further transform key technologies involving matter and energy. These five new Transformative Opportunities and the evidence supporting them are discussed in this new report, “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science.” Mastering Hierarchical Architectures and Beyond-Equilibrium Matter Complex materials and chemical processes transmute matter and energy, for example from CO2 and water to chemical fuel in photosynthesis, from visible light to electricity in solar cells and from electricity to light in light emitting diodes (LEDs) Such functionality requires complex assemblies of heterogeneous materials in hierarchical architectures that display time-dependent away-from-equilibrium behaviors. Much of the foundation of our understanding of such transformations however, is based on monolithic single- phase materials operating at or near thermodynamic equilibrium. The emergent functionalities enabling next-generation disruptive energy technologies require mastering the design, synthesis, and control of complex hierarchical materials employing dynamic far-from-equilibrium behavior. A key guide in this pursuit is nature, for biological systems prove the power of hierarchical assembly and far- from-equilibrium behavior. The challenges here are many: a description of the functionality of hierarchical assemblies in terms of their constituent parts, a blueprint of atomic and molecular positions for each constituent part, and a synthesis strategy for (a) placing the atoms and molecules in the proper positions for the component parts and (b) arranging the component parts into the required hierarchical structure. Targeted functionality will open the door to significant advances in the harvesting, transforming (e.g., reducing CO2, splitting water, and fixing nitrogen), storing, and use of energy to create new materials, manufacturing processes, and technologies—the lifeblood of human societies and economic growth. Beyond Ideal Materials and Systems: Understanding the Critical Roles of Heterogeneity, Interfaces, and Disorder Real materials, both natural ones and those we engineer, are usually a complex mixture of compositional and structural heterogeneities, interfaces, and disorder across all spatial and temporal scales. It is the fluctuations and disorderly states of these heterogeneities and interfaces that often determine the system’s properties and functionality. Much of our fundamental scientific knowledge is based on “ideal” systems, meaning materials that are observed in “frozen” states or represented by spatially or temporally averaged states. Too often, this approach has yielded overly simplistic models that hide important nuances and do not capture the complex behaviors of materials under realistic conditions. These behaviors drive vital chemical transformations such as catalysis, which initiates most industrial manufacturing processes, and friction and corrosion, the parasitic effects of which cost the U.S. economy billions of dollars annually. Expanding our scientific knowledge from the relative simplicity of ideal, perfectly ordered, or structurally averaged materials to the true complexity of real-world heterogeneities, interfaces, and disorder should enable us to realize enormous benefits in the materials and chemical sciences, which translates to the energy sciences, including solar and nuclear power, hydraulic fracturing, power conversion, airframes, and batteries. Harnessing Coherence in Light and Matter Quantum coherence in light and matter is a measure of the extent to which a wave field vibrates in unison with itself at neighboring points in space and time. Although this phenomenon is expressed at the atomic and electronic scales, it can dominate the macroscopic properties of materials and chemical reactions such as superconductivity and efficient photosynthesis. In recent years, enormous progress has been made in recognizing, manipulating, and exploiting quantum coherence. This progress has already elucidated the role that symmetry plays in protecting coherence in key materials, taught us how to use light to manipulate atoms and molecules, and provided us with increasingly sophisticated techniques for controlling and probing the charges and spins of quantum coherent systems. With the arrival of new sources of coherent light and electron beams, thanks in large part to investments by the U.S. Department of Energy’s Office of Basic Energy Sciences (BES), there is now an opportunity to engineer coherence in heterostructures that incorporate multiple types of materials and to control complex, multistep chemical transformations. This approach will pave the way for quantum information processing and next-generation photovoltaic cells and sensors. Revolutionary Advances in Models, Mathematics, Algorithms, Data, and Computing Science today is benefiting from a convergence of theoretical, mathematical, computational, and experimental capabilities that put us on the brink of greatly accelerating our ability to predict, synthesize, and control new materials and chemical processes, and to understand the complexities of matter across a range of scales. Imagine being able to chart a path through a vast sea of possible new materials to find a select few with desired properties. Instead of the time-honored forward approach, in which materials with desired properties are found through either trial-and-error experiments or lucky accidents, we have the opportunity to inversely design and create new materials that possess the properties we desire. The traditional approach has allowed us to make only a tiny fraction of all the materials that are theoretically possible. The inverse design approach, through the harmonious convergence of theoretical, mathematical, computational, and experimental capabilities, could usher in a virtual cornucopia of new materials with functionalities far beyond what nature can provide. Similarly, enhanced mathematical and computational capabilities significantly enhance our ability to extract physical and chemical insights from vastly larger data streams gathered during multimodal and multidimensional experiments using advanced characterization facilities. Exploiting Transformative Advances in Imaging Capabilities across Multiple Scales Historically, improvements in imaging capabilities have always resulted in improved understanding of scientific phenomena. A prime challenge today is finding ways to reconstruct raw data, obtained by probing and mapping matter across multiple scales, into analyzable images. BES investments in new and improved imaging facilities, most notably synchrotron x-ray sources, free-electron lasers, electron microscopes, and neutron sources, have greatly advanced our powers of observation, as have substantial improvements in laboratory- scale technologies. Furthermore, BES is now planning or actively discussing exciting new capabilities. Taken together, these advances in imaging capabilities provide an opportunity to expand our ability to observe and study matter from the 3D spatial perspectives of today to true “4D” spatially and temporally resolved maps of dynamics that allow quantitative predictions of time-dependent material properties and chemical processes. The knowledge gained will impact data storage, catalyst design, drug delivery, structural materials, and medical implants, to name just a few key technologies. ENABLING SUCCESS Seizing each of these five Transformative Opportunities, as well as accelerating further progress on Grand Challenge research, will require specific, targeted investments from BES in the areas of synthesis, meaning the ability to make the materials and architectures that are envisioned; instrumentation and tools, a category that includes theory and computation; and human capital, the most important asset for advancing the Grand Challenges and Transformative Opportunities. While “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science” could be viewed as a sequel to the original Grand Challenges report, it breaks much new ground in its assessment of the scientific landscape today versus the scientific landscape just a few years ago. In the original Grand Challenges report, it was noted that if the five Grand Challenges were met, our ability to direct matter and energy would be measured only by the limits of human imagination. This new report shows that, prodded by those challenges, the scientific community is positioned today to seize new opportunities whose impacts promise to be transformative for science and society, as well as dramatically accelerate progress in the pursuit of the original Grand Challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An extended action for the effective field theory of dark energy: a stability analysis and a complete guide to the mapping at the basis of EFTCAMB

We present a generalization of the effective field theory (EFT) formalism for dark energy and modified gravity models to include operators with higher order spatial derivatives. This allows the extension of the EFT framework to a wider class of gravity theories such as Hořava gravity. We present the corresponding extended action, both in the EFT and the Arnowitt-Deser-Misner (ADM) formalism, and proceed to work out a convenient mapping between the two, providing a self contained and general procedure to translate a given model of gravity into the EFT language at the basis of the Einstein-Boltzmann solver EFTCAMB. Putting this mapping at work, we illustrate, for several interesting models of dark energy and modified gravity, how to express them in the ADM notation and then map them into the EFT formalism. We also provide for the first time, the full mapping of GLPV models into the EFT framework. We next perform a thorough analysis of the physical stability of the generalized EFT action, in absence of matter components. We work out viability conditions that correspond to the absence of ghosts and modes that propagate with a negative speed of sound in the scalar and tensor sector, as well as the absence of tachyonic modes in the scalar sector. Finally, we extend and generalize the phenomenological basis in terms of α-functions introduced to parametrize Horndeski models, to cover all theories with higher order spatial derivatives included in our extended action. We elaborate on the impact of the additional functions on physical quantities, such as the kinetic term and the speeds of propagation for scalar and tensor modes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Midterm Results after Uterine Artery Embolization Versus MR-Guided High-Intensity Focused Ultrasound Treatment for Symptomatic Uterine Fibroids

Purpose: To compare the rate of reintervention and midterm changes in symptom severity (SS) and Total health-related quality of life (HRQoL) scores after uterine artery embolization (UAE) and magnetic resonance-guided high-intensity focused ultrasound (MR-g HIFU) for symptomatic uterine fibroids. Methods: Eighty women (median age 38.3 years), equally eligible for MR-g HIFU and UAE who underwent one of both treatments between 2002 and 2009 at our institution, were included. The primary end point of the study was defined as the rate of reintervention after both therapies. The secondary outcome was defined as changes in SS and Total HRQoL scores after treatment. SS and Total HRQoL scores before treatment and at midterm follow-up (median 13.3 months) were assessed by the uterine fibroid symptom and quality-of-life questionnaire (UFS-QoL) and compared. Results: The rate of reintervention was significantly lower after UAE than after MR-g HIFU (p = 0.002). After both treatments, SS and Total HRQoL scores improved significantly from baseline to follow-up (UAE: p < 0.001, p < 0.001; MR-g HIFU: p = 0.002, p < 0.001). Total HRQoL scores were significantly higher after UAE than after MR-g HIFU (p = 0.032). Changes in the SS scores did not differ significantly for both treatments (p = 0.061). Conclusion: UAE and MR-g HIFU significantly improved the health-related quality of life of women with symptomatic uterine fibroids. After UAE, the change in Total HRQoL score improvement was significantly better, and a significantly lower rate of reintervention was observed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗