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At least 1,225 records · Page 68

On the application of the MARTINI coarse-grained model to immersion of a protein in a phospholipid bilayer

An important step in the simulation of a membrane protein in a phospholipid bilayer is the correct immersion of the protein in the bilayer. Crystal structures are determined without the bilayer. Particularly for proteins with monotopic domains, it can be unclear how deeply and in which orientation the protein is being inserted in the membrane. We have previously developed a procedure combining coarse-grain (CG) with all-atom (AA) molecular dynamics (MD) simulations to insert and simulate a cytochrome P450 (CYP) possessing an N-terminal transmembrane helix connected by a flexible linker region to a globular domain that dips into the membrane. The CG simulations provide a computationally efficient means to explore different orientations and conformations of the CYP in the membrane. Converged configurations obtained in the CG simulations are then refined in AA simulations. Here, we tested different variants of the MARTINI CG model, differing in the water model, the treatment of long-range non-bonded interactions, and the implementation (GROMACS 4.5.5 vs 5.0.4), for this purpose. We examined the behavior of the models for simulating a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer in water and for the immersion of CYP3A4 in a POPC bilayer, and compared the CG-MD results with the previously reported experimental and simulation results. We also tested the methodology on a set of four other CYPs. Finally, we propose an optimized protocol for modeling such protein-membrane systems that provides the most plausible configurations and is computationally efficient; this incorporates the standard non-polar water model and the GROMACS 5.0.4 implementation with a reaction field treatment of long-range interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Productivity with Multilaser Rotary Powder Bed Fusion Additive Manufacturing

Laser powder bed fusion (LPBF) enables the fabrication of intricate, geometrically complex structures with a sufficiently fine surface finish for many engineering applications with a diversity of available feedstock metals. However, the production rate of LPBF systems is not well suited for mass production in comparison to traditional manufacturing methods. LPBF systems measure their deposition rates in 100's of grams per hour, while other processes measure in kilograms per hour or even in the case of processes such as forming, stamping, and casting, 100's of kilograms per hour. To be widely adopted in industry for mass production, LPBF requires a new scalable architecture that enables many orders of magnitude improvement in deposition rate, while maintaining the geometry freedom of additive manufacturing. This article explores concepts that could achieve as much as four orders of magnitude increase in the production rate through the application of (1) rotary table kinematic arrangements; (2) a dramatic number of simultaneously operating lasers; (3) reductions of laser optic size; (4) improved scanning techniques; and (5) an optimization of toroidal build plate size. To theoretically demonstrate the possibilities of production improvements, a productivity analysis is proposed for synchronous reluctance motors with relevance to the electric vehicle industry, given the recent increase in the diversity of printable soft magnetic alloys. The analysis provides insights into the impact of the architecture and process parameters necessary to optimize rotary powder bed fusion for mass production.

36 MATERIALS SCIENCE↗

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography [PowerPoint]

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

WE-EF-BRA-04: Evaluation of Dosimetric Uncertainties in Individualized Targeted Radionuclide Therapy (TRT) Treatment Planning Using Pre-Clinical Data

Purpose: Dosimetry for targeted radionuclide therapy (TRT) is moving away from conventional model-based methods towards patient-specific approaches. To address this need, a Monte Carlo (MC) dosimetry platform was developed to estimate patient-specific therapeutic 3D dose distributions based on pre-treatment imaging. However, because a standard practice for patient-specific internal dosimetry has not yet been established, there are many sources of dosimetric uncertainties. The goal of this work was to quantify the sensitivity of various parameters on MC dose estimations. Methods: The ‘diapeutic’ agent, CLR1404, was used as a proof-of-principle compound in this work. CLR1404 can be radiolabeled with either {sup 124}I for PET imaging or {sup 131}I for radiotherapy or SPECT imaging. PET/CT images of 5 mice were acquired out to 240 hrs post-injection of {sup 124}I-CLR1404. The therapeutic {sup 131}I-CLR1404 absorbed dose (AD) distribution was calculated using a Geant4-based MC dosimetry platform. A series of sensitivity studies were performed. The variables that were investigated included the PET/CT voxel resolution, partial volume corrections (PVC), material segmentation, inter-observer contouring variability, and the pre-treatment image acquisition frequency. Results: Resampling the PET/CT voxel size between 0.2–0.8 mm resulted in up to a 13% variation in the mean AD. Application of the PVC increased the mean AD by 0.5–11.2%. Less than 1% differences in ROI mean AD were observed between the tissue segmentation schemes using 4 and 27 different material compositions. Inter-observer contouring variability led to up to a 20% CoV (stdev/mean) in the mean AD between the users. Varying the number and frequency of pre-treatment images used resulted in changes in mean AD up to 176% compared to the case using all 12 images. Conclusion: Voxel resolution, contour segmentation, the image acquisition protocol most significantly impacted patient-specific TRT dosimetry. Further work is needed to develop a standard protocol that optimizes accuracy and efficiency for patient-specific internal dosimetry. BT and JG are affiliated with Cellectar Biosciences which owns the licensing rights to CLR1404 and related compounds.

60 APPLIED LIFE SCIENCES↗

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗

The approximate second order coupled-cluster method based on a size-consistent Brillouin–Wigner partitioning

We present a variant of the approximate second order coupled-cluster method (CC2) with a two-parameter size-consistent Brillouin–Wigner (BW-s) partitioning instead of a Møller–Plesset (MP) partitioning for the unperturbed Hamiltonian, which we refer to as BWs-CC2. The computational complexity of this model scales identically to CC2 with molecular size. Conventional CC2 and its regularized BWs-CC2 variants, as well as conventional MP2 and two of its regularized BW-s2 variants, were assessed on a 535 element database spanning thermochemistry, non-covalent interactions, barrier heights, and isomerization energies. To ensure a well-defined model chemistry, the assessment was performed using internally stable spin-polarized Hartree–Fock (HF) orbitals in the finite aug-cc-pVQZ basis without counterpoise corrections. As a result of using stable orbitals, contrary to conventional wisdom, we find that CC2 substantially outperforms MP2 on molecules with significantly spin contaminated reference orbitals without a significant increase in error on systems with a spin-pure reference, showing the value of its single substitutions. While no single choice of regularization parameters can be optimal for all datasets, we find that BWs-CC2 generally outperforms both CC2 and BW-s2 with a single judicious parameter choice. Additional tests on dipole moments and bond lengths of diatomics provide further support for the utility of this choice. Furthermore, the main outliers and poorest performing cases are associated with large amounts of spin-contamination in the HF reference, which is indicative of systems with either strong correlation or extensive artificial symmetry breaking. Overall, these findings argue that the perception of the quality of the CC2 ground state should be reevaluated and that it can be further improved upon by the soundly based BWs-CC2 variant with the recommended parameter choice.

Correlation energy↗

Determining conductivity and mobility values of individual components in multiphase composite Cu{sub 1.97}Ag{sub 0.03}Se

The intense interest in phase segregation in thermoelectrics as a means to reduce the lattice thermal conductivity and to modify the electronic properties from nanoscale size effects has not been met with a method for separately measuring the properties of each phase assuming a classical mixture. Here, we apply effective medium theory for measurements of the in-line and Hall resistivity of a multiphase composite, in this case Cu{sub 1.97}Ag{sub 0.03}Se. The behavior of these properties with magnetic field as analyzed by effective medium theory allows us to separate the conductivity and charge carrier mobility of each phase. This powerful technique can be used to determine the matrix properties in the presence of an unwanted impurity phase, to control each phase in an engineered composite, and to determine the maximum carrier concentration change by a given dopant, making it the first step toward a full optimization of a multiphase thermoelectric material and distinguishing nanoscale effects from those of a classical mixture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Time-resolved fast-neutron radiography of air-water two-phase flows in a rectangular channel by an improved detection system

In a previous work, we have demonstrated the feasibility of high-frame-rate, fast-neutron radiography of generic air-water two-phase flows in a 1.5 cm thick, rectangular flow channel. The experiments have been carried out at the high-intensity, white-beam facility of the Physikalisch-Technische Bundesanstalt, Germany, using an multi-frame, time-resolved detector developed for fast neutron resonance radiography. The results were however not fully optimal and therefore we have decided to modify the detector and optimize it for the given application, which is described in the present work. Furthermore, we managed to improve the image post-processing methodology and the noise suppression. Using the tailored detector and the improved post-processing, significant increase in the image quality and an order of magnitude lower exposure times, down to 3.33 ms, have been achieved with minimized motion artifacts. Similar to the previous study, different two-phase flow regimes such as bubbly slug and churn flows have been examined. The enhanced imaging quality enables an improved prediction of two-phase flow parameters like the instantaneous volumetric gas fraction, bubble size, and bubble velocities. Instantaneous velocity fields around the gas enclosures can also be more robustly predicted using optical flow methods as previously.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Planarization of Isolated Defects on ICF Target Capsule Surfaces by Pulsed Laser Ablation

Demanding surface quality requirements for inertial confinement fusion (ICF) capsules motivated the development of a pulsed laser ablation method to reduce or eliminate undesirable surface defects. The pulsed laser ablation technique takes advantage of a full surface (4π) capsule manipulation system working in combination with an optical profiling (confocal) microscope. Based on the defect topography, the material removal rate, the laser pulse energy and its beam profile, a customized laser raster pattern is derived to remove the defect. The pattern is a table of coordinates and number of pulses that dictate how the defect will be vaporized until its height is level with the capsule surface. This paper explains how the raster patterns are optimized to minimize surface roughness and how surface roughness after laser ablation is simulated. The simulated surfaces are compared with actual ablated surfaces. Large defects are reduced to a size regime where a tumble finishing process produces very high quality surfaces devoid of high mode defects. The combined polishing processes of laser ablation and tumble finishing have become routine fabrication steps for National Ignition Facility capsule production.

36 MATERIALS SCIENCE↗

Next-Generation Materials Design: Quantum Mechanics and Data-Driven Modeling

The future of materials design is rapidly advancing through the combination of quantum mechanics and data-driven modeling. These approaches integrate quantum principles with advanced data analysis, enabling precise insights into material behavior. This talk will highlight recent progress in using these methods for computational design, particularly in high-entropy alloy catalysts, emphasizing the role of hierarchical machine-learning architectures for accurate predictions. Additionally, I will discuss our work on developing machine learning interatomic potentials (MLPs) for single-element metals, metal oxides, and alloys under extreme conditions, focusing on melting behavior and phase properties at high temperatures and pressures. We have also refined our MLP models to capture dynamic surface interactions, such as CO2 and CO adsorption on MgO, using both static and molecular dynamics simulations. These models maintain high accuracy while significantly reducing computational costs compared to first-principles calculations. By enabling efficient and accurate simulations, this work supports broader community adoption, optimizes datasets for materials discovery, and extends the accessible time, size, and environmental conditions beyond the limits of experiments and traditional simulations.

machine learning↗

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗

Correlation consistent basis sets for actinides. II. The atoms Ac and Np–Lr

New correlation consistent basis sets optimized using the all-electron third-order Douglas-Kroll-Hess (DKH3) scalar relativistic Hamiltonian are reported for the actinide elements Ac and Np through Lr. These complete the series of sets reported previously for Th–U [K. A. Peterson, J. Chem. Phys. 142, 074105 (2015); M. Vasiliu et al., J. Phys. Chem. A 119, 11422 (2015)]. The new sets range in size from double- to quadruple-zeta and encompass both those optimized for valence (6s6p5f7s6d) and outer-core electron correlations (valence + 5s5p5d). The final sets have been contracted for both the DKH3 and eXact 2-component (X2C) Hamiltonians, yielding cc-pVnZ-DK3/cc-pVnZ-X2C sets for valence correlation and cc-pwCVnZ-DK3/cc-pwCVnZ-X2C sets for outer-core correlation (n = D, T, Q in each case). In order to test the effectiveness of the new basis sets, both atomic and molecular benchmark calculations have been carried out. In the first case, the first three atomic ionization potentials (IPs) of all the actinide elements Ac–Lr have been calculated using the Feller-Peterson-Dixon (FPD) composite approach, primarily with the multireference configuration interaction (MRCI) method. Excellent convergence towards the respective complete basis set (CBS) limits is achieved with the new sets, leading to good agreement with experiment, where these exist, after accurately accounting for spin-orbit effects using the 4-component Dirac-Hartree-Fock method. For a molecular test, the IP and atomization energy (AE) of PuO 2 have been calculated also using the FPD method but using a coupled cluster approach with spin-orbit coupling accounted for using the 4-component MRCI. The present calculations yield an IP 0 for PuO 2 of 159.8 kcal/mol, which is in excellent agreement with the experimental electron transfer bracketing value of 162 ± 3 kcal/mol. Likewise, the calculated 0 K AE of 305.6 kcal/mol is in very good agreement with the currently accepted experimental value of 303.1 ± 5 kcal/mol. The ground state of PuO 2 is predicted to be the 5 Σ$+\atop{0g}$ state.

74 ATOMIC AND MOLECULAR PHYSICS↗

Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization

The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.

42 ENGINEERING↗

Accelerating Bilevel Optimization With Hierarchical Many-Threaded Parallel Differential Evolution

Bilevel optimization is encountered in many relevant real-world applications. The main feature of this type of problem is that an upper-level optimization problem is constrained by a nested lower-level optimization problem. Because of this nested structure, bilevel problems (BLPs) are usually computationally expensive to solve. Differential evolution (DE) has demonstrated promising results in solving BLPs of relatively small scales. As the problem scale increases, the decision space becomes intrinsically larger, requiring a growing number of function evaluations for the method to work properly. In this context, heavy parallelization and high-performance computing techniques are indispensable to enable the resolution of more complex and challenging optimization problems. Hence, we propose a hierarchical many-threaded parallel DE approach for BLPs, where both levels are parallelized. The computational experiments demonstrate that the parallel implementation achieved runtime speeds ranging from 44 to 2559 times faster than the sequential version on a well-known scalable SMD benchmark test problem when executed on an NVIDIA A100 GPU. The findings indicate that the algorithm’s convergence is strongly influenced by the number of both upper- and lower-level generations. Moreover, the success of experiments with large-scale problems is closely linked to the choice of small population sizes.

Dufek, Amanda S↗

SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT

Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantify image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)

60 APPLIED LIFE SCIENCES↗