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Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗

Relativistic non-thermal particle acceleration in two-dimensional collisionless magnetic reconnection

Magnetic reconnection, especially in the relativistic regime, provides an efficient mechanism for accelerating relativistic particles and thus offers an attractive physical explanation for non-thermal high-energy emission from various astrophysical sources. I present a simple analytical model that elucidates key physical processes responsible for reconnection-driven relativistic non-thermal particle acceleration in the large-system, plasmoid-dominated regime in two dimensions. The model aims to explain the numerically observed dependencies of the power-law index $p$ and high-energy cutoff $\gamma _c$ of the resulting non-thermal particle energy spectrum $f(\gamma )$ on the ambient plasma magnetization $\sigma$ , and (for $\gamma _c$ ) on the system size $L$ . In this self-similar model, energetic particles are continuously accelerated by the out-of-plane reconnection electric field $E_{\rm rec}$ until they become magnetized by the reconnected magnetic field and eventually trapped in plasmoids large enough to confine them. The model also includes diffusive Fermi acceleration by particle bouncing off rapidly moving plasmoids. I argue that the balance between electric acceleration and magnetization controls the power-law index, while trapping in plasmoids governs the cutoff, thus tying the particle energy spectrum to the plasmoid distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Charge decay in the spatial afterglow of plasmas and its impact on diffusion regimes

Abstract The spatial afterglow is a region at the boundary of a non-equilibrium plasma where charged species relax into ambient equilibrium. In many applications, the spatial afterglow is the part of the plasma that interacts with surfaces, such as suspended particles or a material substrate. However, compared to the bulk plasma, there has been little effort devoted to studying the properties of the spatial afterglow, and a fundamental analysis has not yet been developed. Here, we apply double Langmuir probe measurements and develop an advection-diffusion-recombination model to provide a detailed description of charged species in the spatial afterglow over a wide range of pressures, temperatures, plasma dimensions, and flow rates. We find that the density of charged species in the spatial afterglow decays by orders of magnitude, which leads to a transition from ambipolar to free diffusion. These insights can be used to explain or predict experimental observations of phenomena, such as the charging of dust grains and the dose of charged species to a biomaterial.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Binary small molecule organic nanoparticles exhibit both direct and diffusion-limited ultrafast charge transfer with NIR excitation

In this study, we describe a facile, one-step synthesis of a binary organic nanoparticle composed completely of NIR-absorbing small molecules, a quatterylene diimide and a vanadyl napthalocyanine, using Flash Nanoprecipitation. We show that the molecules are co-encapsulated within an amphiphilic block copolymer shell by observing distinct ultrafast dynamics in the binary nanoparticles compared to nanoparticles of their individual components, which we rationalize as a photoinduced charge transfer. We then draw similarities between the charge transfer dynamics studied in our system and the charge dissociation process in macroscale organic bulk heterojunction blends for OPV applications by assigning the ultrafast time component (~10 ps) to direct interfacial charge transfer and the slow component (70–200 ps) to diffusion limited charge transfer. This discovery can inspire the development of mixed-composition nanoparticles with new functionality for optoelectronic and theranostic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Resonant charge-exchange involving excited helium atoms and reactive transport of local thermodynamic equilibrium helium plasma

The cross sections for charge-exchange and charge-transfer processes are evaluated for collisions of helium ions with parent-atoms in ground and excited states, with the principal quantum number n= 1-5, in the collision energy range from thermal up to 10 eV. Corresponding diffusion-type collision integrals are derived, and the role of 'abnormal' transport of electronically excited states on the reactive thermal conductivity of equilibrium helium plasma, at atmospheric pressure, estimated in the frame of a simplified approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Generation of parasitic axial flow by drift wave turbulence with broken symmetry: Theory and experiment

Detailed measurements of intrinsic axial flow generation parallel to the magnetic field in the controlled shear decorrelation experiment linear plasma device with no axial momentum input are presented and compared to theory. The results show a causal link from the density gradient to drift-wave turbulence with broken spectral symmetry and development of the axial mean parallel flow. As the density gradient steepens, the axial and azimuthal Reynolds stresses increase and radially sheared azimuthal and axial mean flows develop. A turbulent axial momentum balance analysis shows that the axial Reynolds stress drives the radially sheared axial mean flow. The turbulent drive (Reynolds power) for the azimuthal flow is an order of magnitude greater than that for axial flow, suggesting that the turbulence fluctuation levels are set by azimuthal flow shear regulation. The direct energy exchange between axial and azimuthal mean flows is shown to be insignificant. Therefore, the axial flow is parasitic to the turbulence-zonal flow system and is driven primarily by the axial turbulent stress generated by that system. The non-diffusive, residual part of the axial Reynolds stress is found to be proportional to the density gradient and is formed due to dynamical asymmetry in the drift-wave turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Shielding of the azimuthal magnetic field by the anode plasma in a relativistic self-magnetic-pinch diode

In relativistic electron beam diodes, the self-generated magnetic field causes electron-beam focusing at the center of the anode. Generally, plasma is formed all over the anode surface during and after the process of the beam focusing. In this work, we use visible-light Zeeman-effect spectroscopy for the determination of the magnetic field in the anode plasma in the Sandia 10 MV, 200 kA (RITS-6) electron beam diode. The magnetic field is determined from the Zeeman-dominated shapes of the Al III 4 s –4 p and C IV 3 s –3 p doublet emissions from various radial positions. Near the anode surface, due to the high plasma density, the spectral line-shapes are Stark-dominated, and only an upper limit of the magnetic field can be determined. The line-shape analysis also yields the plasma density. The data yield quantitatively the magnetic-field shielding in the plasma. In conclusion, the magnetic-field distribution in the plasma is compared to the field-diffusion prediction and found to be consistent with the Spitzer resistivity, estimated using the electron temperature and charge-state distribution determined from line intensity ratios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pulsed power accelerator surface Joule heating models

Understanding the effects of contaminant plasmas generated within the Z machine at Sandia is critical to understanding current loss mechanisms. The plasmas are generated at the accelerator electrode surfaces and include desorbed species found in the surface and substrate of the walls. These desorbed species can become ionized. The timing and location of contaminant species desorbed from the wall surface depend non-linearly on the local surface temperature. For accurate modeling, it is necessary to utilize wall heating models to estimate the amount and timing of material desorption. One of these heating mechanisms is Joule heating. In this paper, we propose several extended semi-analytic magnetic diffusion heating models for computing surface Joule heating and demonstrate their effects for several representative current histories. We quantitatively assess under what circumstances these extensions to classical formulas may provide a validatable improvement to the understanding of contaminant desorption timing.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Laser Shock Fresh Fuel Bond Strength Studies

Laser-based characterization of base monolithic U-10Mo fuel is being conducted by the USHPRR Fuel Qualification project to support fabrication development and ensure the fuel maintains mechanical integrity and does not delaminate during normal operating conditions. Characterization involves laser shock experiments, combined with laser-based ultrasonic scanning, to evaluate the bonding integrity and relative strength of interfaces within fuel plates. This report documents fresh fuel studies that were carried out on a series of fuel plates manufactured at Los Alamos National Laboratory in which various, controlled levels of interfacial contamination were intentionally introduced into the fuel plates during fabrication in order to vary the bond strength. Additional scoping studies were conducted on several developmental fuel plates supplied by the USHPRR Fuel Fabrication Pillar in which the Zr diffusion barrier was applied to the U-Mo foils by electroplating and plasma spraying. The electroplating and plasma spraying processes are being evaluated as potential alternatives to the baseline co-rolling fabrication process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of moisture ingress from the perimeter of photovoltaic modules: Evaluation of moisture ingress

Many thin film photovoltaic (PV) technologies can be sensitive to corrosion induced by the presence of water vapor in the packaging materials. Typically impermeable front and backsheets are used in conjunction with an edge-seal around the perimeter to prevent water vapor ingress. These edge-seal materials are often made of a polyisobutylene resin filled with desiccant, which dramatically increases the time for moisture to reach sensitive module components. While edge-seals can prevent moisture ingress, even the lowest diffusivity transparent encapsulant materials are insufficient for the lifetime of a module. To evaluate the performance of edge-seal and encapsulant materials in a manner that simulates their function in a PV module, an optical method was devised where ingress is detected by reaction of a Ca film with water. Using this method, we have exposed test samples to heat and humidity allowing quantitative comparison of different edge-seal and encapsulant materials. Next, we use measurements of polymer diffusivity and solubility to evaluate the ability to model this moisture ingress. Here, we find good agreement between these two methods highlighting the much greater ability of polyisobutylene materials to keep moisture out as compared with typical encapsulant materials used in the PV industry.

14 SOLAR ENERGY↗

Statistical investigations on nitrogen-vacancy center creation

Quantum information technologies require networks of interacting defect bits. Color centers, especially the nitrogen vacancy (NV{sup −}) center in diamond, represent one promising avenue, toward the realisation of such devices. The most successful technique for creating NV{sup −} in diamond is ion implantation followed by annealing. Previous experiments have shown that shallow nitrogen implantation (<10 keV) results in NV{sup −} centers with a yield of 0.01%–0.1%. We investigate the influence of channeling effects during shallow implantation and statistical diffusion of vacancies using molecular dynamics and Monte Carlo simulation techniques. Energy barriers for the diffusion process were calculated using density functional theory. Our simulations show that 25% of the implanted nitrogens form a NV center, which is in good agreement with our experimental findings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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↗