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NASA NTRS1998

Preliminary Work for Examining the Scalability of Reinforcement Learning

Researchers began studying automated agents that learn to perform multiple-step tasks early in the history of artificial intelligence (Samuel, 1963; Samuel, 1967; Waterman, 1970; Fikes, Hart & Nilsonn, 1972). Multiple-step tasks are tasks that can only be solved via a sequence of decisions, such as control problems, robotics problems, classic problem-solving, and game-playing. The objective of agents attempting to learn such tasks is to use the resources they have available in order to become more proficient at the tasks. In particular, each agent attempts to develop a good policy, a mapping from states to actions, that allows it to select actions that optimize a measure of its performance on the task; for example, reducing the number of steps necessary to complete the task successfully. Our study focuses on reinforcement learning, a set of learning techniques where the learner performs trial-and-error experiments in the task and adapts its policy based on the outcome of those experiments. Much of the work in reinforcement learning has focused on a particular, simple representation, where every problem state is represented explicitly in a table, and associated with each state are the actions that can be chosen in that state. A major advantage of this table lookup representation is that one can prove that certain reinforcement learning techniques will develop an optimal policy for the current task. The drawback is that the representation limits the application of reinforcement learning to multiple-step tasks with relatively small state-spaces. There has been a little theoretical work that proves that convergence to optimal solutions can be obtained when using generalization structures, but the structures are quite simple. The theory says little about complex structures, such as multi-layer, feedforward artificial neural networks (Rumelhart & McClelland, 1986), but empirical results indicate that the use of reinforcement learning with such structures is promising. These empirical results make no theoretical claims, nor compare the policies produced to optimal policies. A goal of our work is to be able to make the comparison between an optimal policy and one stored in an artificial neural network. A difficulty of performing such a study is finding a multiple-step task that is small enough that one can find an optimal policy using table lookup, yet large enough that, for practical purposes, an artificial neural network is really required. We have identified a limited form of the game OTHELLO as satisfying these requirements. The work we report here is in the very preliminary stages of research, but this paper provides background for the problem being studied and a description of our initial approach to examining the problem. In the remainder of this paper, we first describe reinforcement learning in more detail. Next, we present the game OTHELLO. Finally we argue that a restricted form of the game meets the requirements of our study, and describe our preliminary approach to finding an optimal solution to the problem.

Clouse, Jeff↗

DOE OSTI2024

Mitigating Sodium Ordering for Enhanced Solid Solution Behavior in Layered NaNiO 2 Cathodes

Abstract The O‐type layered nickel oxides suffer from undesired cooperative Jahn–Teller distortion stemming from Ni 3+ ions and undergo multiple biphasic structural transformations during the insertion/extraction of large Na + ions, posing a significant challenge to stabilize the structural integrity. We present here a systematic investigation of the impact of substituting 5 % divalent (Mg 2+ ) or trivalent (Al 3+ or Co 3+ ) ions for Ni 3+ to alleviate Na + ion ordering and perturb the Jahn–Teller effect to enhance structural stability. We gauge a fundamental understanding of the Mg−O and Na−O or Mg−O−Na bonding interactions, noting that the ionicity of the Mg−O bond deshields the electronic cloud of oxygen from Na + ions. Furthermore, calculations of the Van Vleck distortion modes reveal a relaxation of NiO 6 octahedra from Jahn–Teller distortion and a reduced electron density at the interlayer with Mg 2+ substitution. Long‐range ( operando X‐ray diffraction) and short‐range (magic angle spinning nuclear magnetic resonance) structural analyses provide insights into reduced ordering, allowing a stable continuous solid solution. Overall, Mg‐substitution results in a high‐capacity retention of ~96 % even after 100 cycles, showcasing the potential of this strategy for overcoming the structural instabilities and enhancing the performance of sodium‐ion batteries.

Sada, Krishnakanth↗

NASA NTRS1989

A nearly-linear computational-cost scheme for the forward dynamics of an N-body pendulum

The dynamic equations of motion of an n-body pendulum with spherical joints are derived to be a mixed system of differential and algebraic equations (DAE's). The DAE's are kept in implicit form to save arithmetic and preserve the sparsity of the system and are solved by the robust implicit integration method. At each solution point, the predicted solution is corrected to its exact solution within given tolerance using Newton's iterative method. For each iteration, a linear system of the form J delta X = E has to be solved. The computational cost for solving this linear system directly by LU factorization is O(n exp 3), and it can be reduced significantly by exploring the structure of J. It is shown that by recognizing the recursive patterns and exploiting the sparsity of the system the multiplicative and additive computational costs for solving J delta X = E are O(n) and O(n exp 2), respectively. The formulation and solution method for an n-body pendulum is presented. The computational cost is shown to be nearly linearly proportional to the number of bodies.

Chou, Jack C. K.↗

DOE OSTI2024

Mitigating Sodium Ordering for Enhanced Solid Solution Behavior in Layered NaNiO 2 Cathodes

The O-type layered nickel oxides suffer from undesired cooperative Jahn–Teller distortion stemming from Ni 3+ ions and undergo multiple biphasic structural transformations during the insertion/extraction of large Na + ions, posing a significant challenge to stabilize the structural integrity. We present here a systematic investigation of the impact of substituting 5 % divalent (Mg 2+ ) or trivalent (Al 3+ or Co 3+ ) ions for Ni 3+ to alleviate Na + ion ordering and perturb the Jahn–Teller effect to enhance structural stability. Here, we gauge a fundamental understanding of the Mg−O and Na−O or Mg−O−Na bonding interactions, noting that the ionicity of the Mg−O bond deshields the electronic cloud of oxygen from Na + ions. Furthermore, calculations of the Van Vleck distortion modes reveal a relaxation of NiO 6 octahedra from Jahn–Teller distortion and a reduced electron density at the interlayer with Mg 2+ substitution. Long-range (operando X-ray diffraction) and short-range (magic angle spinning nuclear magnetic resonance) structural analyses provide insights into reduced ordering, allowing a stable continuous solid solution. Overall, Mg-substitution results in a high-capacity retention of ~96 % even after 100 cycles, showcasing the potential of this strategy for overcoming the structural instabilities and enhancing the performance of sodium-ion batteries.

25 ENERGY STORAGE↗

DOE OSTI2024

De novo design of buttressed loops for sculpting protein functions

In natural proteins, structured loops have central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that designs tandem repeat proteins with structured loops (9–14 residues) buttressed by extensive hydrogen bonding interactions. Experimental characterization shows that the designs are monodisperse, highly soluble, folded and thermally stable. Crystal structures are in close agreement with the design models, with the loops structured and buttressed as designed. We demonstrate the functionality afforded by loop buttressing by designing and characterizing binders for extended peptides in which the loops form one side of an extended binding pocket. The ability to design multiple structured loops should contribute generally to efforts to design new protein functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Thermodynamic Assessment of the Ternary Alloy System Li-Sn-Zn

The goal of this project is to predict thermodynamics and structure-properties relationships of a series of Li-based alloys for the development of advanced tritium breeding materials that exhibit the beneficial properties of pure lithium while mitigating its chemical reactivity issues for fusion applications. This project makes use of phenomenological thermodynamics based on the CALPHAD (CALculation of PHAse Diagrams), and the use of the Thermo-Calc software (see Appendix A), and experimental calorimetric data and structural characterization for the purpose of validating the data. The initial selection of Sn and Zn as solutes is considered in this first report. Originally Li-Sn alloys have shown promise in meeting tritium breeding ratio (TBR) and energy multiplication requirements. However with the addition of Zn, we expect an improvement in the nuclear, thermal, and chemical requirements of the working fluid. Other substitutes will be considered once neutronic calculations are carried out. Hence the objective of this first task is to carry out a thermodynamic assessment of the Li-Sn-Zn alloy system, as part of the development of a self-consistent and validated thermodynamic database that will include other solute elements for optimizing the properties of blanket materials in fusion-based reactors. This obviously involves the thermodynamic assessment of the three binary subsystems, namely Li-Sn, Li-Zn, and Sn-Zn.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Ambiguities in the hadro-chemical freeze-out of Au+Au collisions at SIS18 energies and how to resolve them

The thermal fit to preliminary HADES data of Au+Au collisions at $\sqrt{s_{NN}}$=2.4 GeV shows two degenerate solutions at T≈50 MeV and T≈70 MeV. The analysis of the same particle yields in a transport simulation of the UrQMD model yields the same features, i.e. two distinct temperatures for the chemical freeze-out. While both solutions yield the same number of hadrons after resonance decays, the feeddown contribution is very different for both cases. This highlights that two systems with different chemical composition can yield the same multiplicities after resonance decays. The nature of these two minima is further investigated by studying the time-dependent particle yields and extracted thermodynamic properties of the UrQMD model. It is confirmed, that the evolution of the high temperature solution resembles cooling and expansion of a hot and dense fireball. The low temperature solution displays an unphysical evolution: heating and compression of matter with a decrease of entropy. These results imply that the thermal model analysis of systems produced in low energy nuclear collisions is ambiguous but can be interpreted by taking also the time evolution and resonance contributions into account.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components

Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Coupled cluster theory on modern heterogeneous supercomputers

This study examines the computational challenges in elucidating intricate chemical systems, particularly through ab-initio methodologies. This work highlights the Divide-Expand-Consolidate (DEC) approach for coupled cluster (CC) theory—a linear-scaling, massively parallel framework—as a viable solution. Detailed scrutiny of the DEC framework reveals its extensive applicability for large chemical systems, yet it also acknowledges inherent limitations. To mitigate these constraints, the cluster perturbation theory is presented as an effective remedy. Attention is then directed towards the CPS (D-3) model, explicitly derived from a CC singles parent and a doubles auxiliary excitation space, for computing excitation energies. The reviewed new algorithms for the CPS (D-3) method efficiently capitalize on multiple nodes and graphical processing units, expediting heavy tensor contractions. As a result, CPS (D-3) emerges as a scalable, rapid, and precise solution for computing molecular properties in large molecular systems, marking it an efficient contender to conventional CC models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

SU-F-J-171: Robust Atlas Based Segmentation of the Prostate and Peripheral Zone Regions On MRI Utilizing Multiple MRI System Vendors

Purpose: Automatically generated prostate MRI contours can be used to aid in image registration with CT or ultrasound and to reduce the burden of contouring for radiation treatment planning. In addition, prostate and zonal contours can assist to automate quantitative imaging features extraction and the analyses of longitudinal MRI studies. These potential gains are limited if the solutions are not compatible across different MRI vendors. The goal of this study is to characterize an atlas based automatic segmentation procedure of the prostate collected on MRI systems from multiple vendors. Methods: The prostate and peripheral zone (PZ) were manually contoured by an expert radiation oncologist on T2-weighted scans acquired on both GE (n=31) and Siemens (n=33) 3T MRI systems. A leave-one-out approach was utilized where the target subject is removed from the atlas before the segmentation algorithm is initiated. The atlas-segmentation method finds the best nine matched atlas subjects and then performs a normalized intensity-based free-form deformable registration of these subjects to the target subject. These nine contours are then merged into a single contour using Simultaneous Truth and Performance Level Estimation (STAPLE). Contour comparisons were made using Dice similarity coefficients (DSC) and Hausdorff distances. Results: Using the T2 FatSat (FS) GE datasets the atlas generated contours resulted in an average DSC of 0.83±0.06 for prostate, 0.57±0.12 for PZ and 0.75±0.09 for CG. Similar results were found when using the Siemens data with a DSC of 0.79±0.14 for prostate, 0.54±0.16 and 0.70±0.9. Contrast between prostate and surrounding anatomy and between the PZ and CG contours for both vendors demonstrated superior contrast separation; significance was found for all comparisons p-value < 0.0001. Conclusion: Atlas-based segmentation yielded promising results for all contours compared to expertly defined contours in both Siemens and GE 3T systems providing fast and automatic segmentation of the prostate. Funding Support, Disclosures, and Conflict of Interest: AS Nelson is a partial owner of MIM Software, Inc. AS Nelson, and A Swallen are current employees at MIM Software, Inc.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2023

Sintering Behaviors of ZrC, NbC, and TaC Mono-and Binary Carbides

Nuclear Thermal Propulsion (NTP) has undergone development as an alternate in-space propulsion system to traditional chemical propulsion methods since the 1950s. In an NTP system, the energy released from fission in the core is utilized as the heat source to directly heat a propellant for propulsion, rather than chemical combustion in a traditional rocket. NTP has many desirable capabilities including flexible mission launch dates and reduced transit times due to it’s capability for high specific impulse. One of the main challenges with NTP systems is the structural integrity of the fuel. The fuel form required in the reactor core must withstand temperatures above 2700 Kelvin. Ceramic-metallic matrix fuel, ceramic-ceramic matrix fuel, and solid solution carbide fuels are the three strongest candidates for the extreme environments. Solid solution carbides have the potential to exhibit promising behavior as a fuel form in an NTP system. Of the multiple refractory metal carbides of interest, here we focus on zirconium carbide (ZrC), niobium carbide (NbC), and tantalum carbide (TaC). ZrC, NbC, and TaC powders were consolidated in monocarbide (ZrC, NbC, and TaC) and bi-carbide (ZrC-NbC, ZrC-TaC, NbC-TaC) forms using spark plasma sintering (SPS). In addition to the pure endpoint carbides, the examined compositions of the various bi-carbides ranged from 25-75 mol%. The sintering temperatures, pressures, and hold times were varied to determine the ideal sintering conditions. Grain size analysis, Archimedes’ density, scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy dispersion spectroscopy (EDS) were used to determine and characterize the grain size, ideal density, porosity, phase stability, and chemical composition of each sample. The data from each sample was then used to generate a Master Sintering Curve (MSC) unique to each monocarbide or bi-carbide.

nuclear thermal propulsion↗

DOE OSTI2026

Development of Magnesium Borane Containing Solutions of Furans and Pyrroles as Reversible Liquid Hydrogen Carriers (Final Technical Report)

The objective of this project was the development of a two-way liquid hydrogen carrier having a greater energy efficiency and lower delivery costs than either existing hydrogen carriers or conventional compressed H 2 gas transport technology. It was hypothesized that a hydrogen carrier consisting of solutions of furans and pyrroles containing Mg(BH 4 ) 2 and pincer complex catalyst, would have more than twice the volumetric available hydrogen density of the conventional two-way liquid hydrogen carrier, methylcyclohexane. Most notably the envisioned liquid hydrogen carrier would: 1) maintain high product selectivity through multiple cycles of dehydrogenation and hydrogenation; and 2) undergo rapid dehydrogenation and re-hydrogenation. The project was specifically aimed at the demonstration of at least one LOHC solution of Mg(BH 4 ) 2 and pincer catalyst that releases ≥ 50 g H 2 /L at ≤ 200 °C upon dehydrogenation and undergoes ≥ 25% rehydrogenation under 100 atm of H 2 at ≤ 200 °C.

08 HYDROGEN↗

NASA NTRS2006

Interoperable Solution for Test Execution in Various I&T Environments

When there is spacecraft collaboration between several industry partners, there is an inherent difference in integration and test (I&T) methodologies, which creates a challenge for verifying flight systems during the development phase. To converge the differing I&T methodologies, considerations were required for multiple project areas such as Flight System Testbed (FST), Assembly, Test, and Launch Operations (ATLO), and Spacecraft Simulator environments. This paper details the challenges and approaches of the JPL's effort in engineering a solution to testing the flight system with the Mission Operations Ground System while maintaining the comparability with testing methods of the industry partners.

integration↗

DOE OSTI2023

Operation Optimization using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

SU-G-TeP1-15: Toward a Novel GPU Accelerated Deterministic Solution to the Linear Boltzmann Transport Equation

Purpose: To develop a Graphic Processor Unit (GPU) accelerated deterministic solution to the Linear Boltzmann Transport Equation (LBTE) for accurate dose calculations in radiotherapy (RT). A deterministic solution yields the potential for major speed improvements due to the sparse matrix-vector and vector-vector multiplications and would thus be of benefit to RT. Methods: In order to leverage the massively parallel architecture of GPUs, the first order LBTE was reformulated as a second order self-adjoint equation using the Least Squares Finite Element Method (LSFEM). This produces a symmetric positive-definite matrix which is efficiently solved using a parallelized conjugate gradient (CG) solver. The LSFEM formalism is applied in space, discrete ordinates is applied in angle, and the Multigroup method is applied in energy. The final linear system of equations produced is tightly coupled in space and angle. Our code written in CUDA-C was benchmarked on an Nvidia GeForce TITAN-X GPU against an Intel i7-6700K CPU. A spatial mesh of 30,950 tetrahedral elements was used with an S4 angular approximation. Results: To avoid repeating a full computationally intensive finite element matrix assembly at each Multigroup energy, a novel mapping algorithm was developed which minimized the operations required at each energy. Additionally, a parallelized memory mapping for the kronecker product between the sparse spatial and angular matrices, including Dirichlet boundary conditions, was created. Atomicity is preserved by graph-coloring overlapping nodes into separate kernel launches. The one-time mapping calculations for matrix assembly, kronecker product, and boundary condition application took 452±1ms on GPU. Matrix assembly for 16 energy groups took 556±3s on CPU, and 358±2ms on GPU using the mappings developed. The CG solver took 93±1s on CPU, and 468±2ms on GPU. Conclusion: Three computationally intensive subroutines in deterministically solving the LBTE have been formulated on GPU, resulting in two orders of magnitude speedup. Funding support from Natural Sciences and Engineering Research Council and Alberta Innovates Health Solutions. Dr. Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Coalescence of silver clusters by immersion in diluted HF solution

The galvanic displacement deposition of silver on H-terminated Si (100) in the time scale of seconds is instantaneous and characterized by a cluster density of 10{sup 11}-10{sup 12} cm{sup −2}. The amount of deposited Ag follows a t{sup 1/2} dependence in agreement with a Cottrell diffusion limited mechanism. At the same time, during the deposition, the cluster density reduces by a factor 5. This behavior is in contrast with the assumption of immobile clusters. We show in the present work that coalescence and aggregation occur also in the samples immersed in the diluted hydrofluoric acid (HF) solution without the presence of Ag{sup +}. Clusters agglomerate according to a process of dynamic coalescence, typical of colloids, followed by atomic redistribution at the contact regions with the generation of multiple internal twins and stacking-faults. The normalized size distributions in terms of r/r{sub mean} follow also the prediction of the Smoluchowski ripening mechanism. No variation of the cluster density occurs for samples immersed in pure H{sub 2}O solution. The different behavior might be associated to the strong attraction of clusters to oxide-terminated Si surface in presence of water. The silver clusters are instead weakly bound to hydrophobic H-terminated Si in presence of HF. HF causes then the detachment of clusters and a random movement on the silicon surface with mobility of about 10{sup −13} cm{sup 2}/s. Attractive interaction (probably van der Waals) among particles promotes coarsening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

The J-elongated conformation of β 2 -glycoprotein I predominates in solution: Implications for our understanding of antiphospholipid syndrome

β 2 -Glycoprotein I (β 2 GPI) is an abundant plasma protein displaying phospholipid-binding properties. Because it binds phospholipids, it is a target of antiphospholipid antibodies (aPLs) in antiphospholipid syndrome (APS), a life-threatening autoimmune thrombotic disease. Indeed, aPLs prefer membrane-bound β 2 GPI to that in solution. β 2 GPI exists in two almost equally populated redox states: oxidized, in which all the disulfide bonds are formed, and reduced, in which one or more disulfide bonds are broken. Furthermore, β 2 GPI can adopt multiple conformations (i.e. J-elongated, S-twisted, and O-circular). While strong evidence indicates that the J-form is the structure bound to aPLs, which conformation exists and predominates in solution remains controversial, and so is the conformational pathway leading to the bound state. Here, we report that human recombinant β 2 GPI purified under native conditions is oxidized. Moreover, under physiological pH and salt concentrations, this oxidized form adopts a J-elongated, flexible conformation, not circular or twisted, in which the N-terminal domain I (DI) and the C-terminal domain V (DV) are exposed to the solvent. Consistent with this model, binding kinetics and mutagenesis experiments revealed that in solution the J-form interacts with negatively charged liposomes and with MBB2, a monoclonal anti-DI antibody that recapitulates most of the features of pathogenic aPLs. We conclude that the preferential binding of aPLs to phospholipid-bound β 2 GPI arises from the ability of its preexisting J-form to accumulate on the membranes, thereby offering an ideal environment for aPL binding. We propose that targeting the J-form of β 2 GPI provides a strategy to block pathogenic aPLs in APS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mixed gain detector configurations for time-resolved X-ray solution scattering

X-ray detection at X-ray free-electron lasers is challenging in part due to the XFEL's extremely short and intense X-ray pulses. Experimental measurements are further complicated by the large fluctuations inherent to the self-amplified spontaneous emission process producing the X-rays. At the Linac Coherent Light Source the ePix10ka2M detector offers multiple gain modes, and auto-ranging between these, to increase the dynamic range while retaining low noise. For diffuse scattering techniques, such as time-resolved X-ray solution scattering, where the shape of the scattering pattern largely does not change between exposures, a fixed mix of different gain modes offers many of the same advantages as auto-ranging. We find that configuring individual ASICs in separate gain modes does not impact the intensity linearity of the gain response and has a limited effect on the effective dynamic range in regions with different gain mode settings while avoiding the complexities of auto-ranging. Small (<5%) non-linear gain contributions arise when pixels on the same ASIC are configured in different gain modes. We present a configuration scheme that is designed to select the optimal mixed gain configuration to minimize effects of saturation in the high-/medium-gain region, while maximizing the number of pixels with higher gain to improve the signal-to-noise ratio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗