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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection

Protein-ligand docking is a computational method for identifying drug leads. The method is capable of narrowing a vast library of compounds down to a tractable size for downstream simulation or experimental testing and is widely used in drug discovery. While there has been progress in accelerating scoring of compounds with artificial intelligence, few works have bridged these successes back to the virtual screening community in terms of utility and forward-looking development. We demonstrate the power of high-speed ML models by scoring 1 billion molecules in under a day (50 k predictions per GPU seconds). We showcase a workflow for docking utilizing surrogate AI-based models as a pre-filter to a standard docking workflow. Our workflow is ten times faster at screening a library of compounds than the standard technique, with an error rate less than 0.01% of detecting the underlying best scoring 0.1% of compounds. Our analysis of the speedup explains that another order of magnitude speedup must come from model accuracy rather than computing speed. In order to drive another order of magnitude of acceleration, we share a benchmark dataset consisting of 200 million 3D complex structures and 2D structure scores across a consistent set of 13 million “in-stock” molecules over 15 receptors, or binding sites, across the SARS-CoV-2 proteome. We believe this is strong evidence for the community to begin focusing on improving the accuracy of surrogate models to improve the ability to screen massive compound libraries 100 × or even 1000 × faster than current techniques and reduce missing top hits. The technique outlined aims to be a fast drop-in replacement for docking for screening billion-scale molecular libraries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
DOE OSTI2022

Anion-exchange membranes with internal microchannels for water control in CO 2 electrolysis

Electrochemical reduction of carbon dioxide (CO 2 R) poses substantial promise to convert abundant feedstocks (water and CO 2 ) to value-added chemicals and fuels using solely renewable energy. However, recent membrane-electrode assembly (MEA) devices that have been demonstrated to achieve high rates of CO 2 R are limited by water management within the cell, due to both consumption of water by the CO 2 R reaction and electro-osmotic fluxes that transport water from the cathode to the anode. Additionally, crossover of potassium (K + ) ions poses concern at high current densities where saturation and precipitation of the salt ions can degrade cell performance. Herein, a device architecture incorporating an anion-exchange membrane (AEM) with internal water channels to mitigate MEA dehydration is proposed and demonstrated. A macroscale, two-dimensional continuum model is used to assess water fluxes and local water content within the modified MEA, as well as to determine the optimal channel geometry and composition. The modified AEMs are then fabricated and tested experimentally, demonstrating that the internal channels can both reduce K + cation crossover as well as improve AEM conductivity and therefore overall cell performance. This work demonstrates the promise of these materials, and operando water-management strategies in general, in handling some of the major hurdles in the development of MEA devices for CO 2 R.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Broadband cross polarization for ultra-wideline magic-angle spinning NMR

Over the past decade, there has been a sustained interest in using frequency-swept (FS) pulses for the efficient acquisition of wideline and ultra-wideline (UW) NMR powder patterns. Such experiments are typically conducted under static conditions, employing both direct- and indirect-excitation methods (i.e., WCPMG and BRAIN-CP/WCPMG, respectively). Recently, Koppe et al. demonstrated that the WCPMG pulse sequence can be used to efficiently acquire wideline and UW NMR spectra with spinning sideband (SSB) manifolds under magic-angle spinning (MAS) conditions, capitalizing on the increased signal-to-noise ratios (SNR) afforded by MAS. To date, there have been only a few instances of broadband cross-polarization (CP) experiments using FS pulses under MAS conditions and no applications to systems exhibiting wideline and/or ultra-wideline powder patterns, despite the clear advantages these experiments could offer. Herein, we demonstrate that FS pulses selectively applied to a single sideband of the S spin can be used for efficient 1 H-S polarization transfer to S = 1/2 nuclides with large anisotropic chemical shift interactions at slow to moderate MAS rates. The Hartmann–Hahn matching conditions in BRAIN-CP/WCPMG-MAS experiments bear similarity to those of standard CP sequences, yet operate over UW frequency ranges and only require low-amplitude RF pulses on the S channel. Crucial to the success of the BRAIN-CP/WCPMG-MAS experiment is careful calibration of the RF amplitude, transmitter offset, and effective frequency sweep of the FS pulse applied to the S spins at a given MAS rate. Thus, by means of numerical simulations and experimental testing, we provide recommendations for the parameterization and setup of BRAIN-CP/WCPMG-MAS experiments for their most efficient use. Results showcasing the capability of the BRAIN-CP/WCPMG-MAS pulse sequence are presented, including applications to 119 Sn, 195 Pt, and 103 Rh NMR.

Kimball, James J. [Florida State University, Talla↗
DOE OSTI2026

Discovery of hydrogen storage molecules using large language models and machine learning

Accelerating the discovery of new molecules with targeted properties is a central challenge in molecular design. In this contribution, we present an AI-driven molecular discovery framework that integrates Large Language Models (LLMs) for generative molecular design with Machine Learning (ML)-based screening to identify novel Liquid Organic Hydrogen Carrier (LOHC) candidates. Using the developed framework, LOHC molecules were systematically generated, evaluated, and refined iteratively, combining LLM-guided molecular generation and ML-predicted hydrogenation enthalpies (Δ H ), under physicochemical property constraints such as optimal melting points (MP), desired hydrogen storage capacity (wt% H 2 ), and synthetic accessibility (SA) scores. This approach enabled the discovery of 42 new LOHC candidates in two distinct campaigns, one seeded with experimentally known and another with previously computationally identified LOHCs, respectively. Although we began with different numbers of starting molecules (31 vs . 7 seed molecules), both runs yielded a comparable number of viable candidates, suggesting an influence of chemically intuitive seed molecule selection for success. Selected LOHC molecules, such as 3-methyl pyridine, 1-ethylnapthalene, 1,1-diphenylethane, and benzofuran, were experimentally tested and compared with benchmark LOHCs (toluene and 9-ethylcarbazole) for hydrogenation using a series of commercial supported metal catalysts. The order of conversion into fully hydrogenated products at 200 °C was 3-methyl pyridine (100%) > 9-ethyl carbazole (86.4%) > 2,3-benzofuran (74%) > 1,1-diphenylethane (66.9%) > 1-ethylnapthalene (66.7%) > toluene (57%), further validating the AI-guided molecular design. This study demonstrates promise of LLM-driven molecular design in conjunction with ML-based screening for accelerated discovery and design of molecules.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2024

Design considerations of series type hybrid circuit breaker (S‐HCB)

Abstract The series‐type direct current (DC) hybrid circuit breaker (S‐HCB) concept was previously reported to offer better performance than solid‐state circuit breakers (SSCB) and hybrid circuit breakers (HCB). S‐HCB offers low conduction power loss like an HCB and ‐scale interruption time, which is even faster than an SSCB. It uses a pulse transformer to isolate the lower‐voltage high‐inductance power electronic circuit from the high‐voltage, low‐inductance main power loop. This paper provides analysis of the impact of the S‐HCB circuit components on the overall system performance and a scalable S‐HCB design guide for different DC system voltage and current ratings. In addition, system energy flow analysis is performed in the time domain to provide an understanding of how energy is delivered, dissipated, and released throughout the entire fault interruption process. The S‐HCB prototype was experimentally tested at 3 kV/30 A and 6 kV/150A with the results showing the interruption of the low fault current of 30 A and the high fault current of 150 A within 8 and maintaining the fault current at a near zero value for 300 to enable an arcless opening of a series mechanical switch. The key design challenges of S‐HCB at high voltage and high current ratings were discussed and possible solutions to mitigate those challenges were introduced.

Alashi, Mahmoud↗
DOE OSTI2020

Implementation of a Talbot–Lau x-ray deflectometer diagnostic platform for the OMEGA EP laser

A Talbot–Lau X-ray Deflectometer (TXD) was implemented in the OMEGA EP laser facility to characterize the evolution of an irradiated foil ablation front by mapping electron densities >10 22 cm -3 by means of Moiré deflectometry. The experiment used a short-pulse laser (30–100 J, 10 ps) and a foil copper target as an x-ray backlighter source. In the first experimental tests performed to benchmark the diagnostic platform, grating survival was demonstrated and x-ray backlighter laser parameters that deliver Moiré images were described. Finally, the necessary modifications to accurately probe the ablation front through TXD using the EP-TXD diagnostic platform are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational catalyst discovery: Active classification through myopic multiscale sampling

We report the recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the field of computational catalyst discovery. First, calculating macro-scale catalyst properties is not straightforward when using ensembles of atomic-scale calculations [e.g., density functional theory (DFT)]. We attempt to address this issue by creating a multi-scale model that estimates bulk catalyst activity using adsorption energy predictions from both DFT and machine learning models. The second issue is that many catalyst discovery efforts seek to optimize catalyst properties, but optimization is an inherently exploitative objective that is in tension with the explorative nature of early-stage discovery projects. In other words, why invest so much time finding a “best” catalyst when it is likely to fail for some other, unforeseen problem? We address this issue by relaxing the catalyst discovery goal into a classification problem: “What is the set of catalysts that is worth testing experimentally?” Here, we present a catalyst discovery method called myopic multiscale sampling, which combines multiscale modeling with automated selection of DFT calculations. It is an active classification strategy that seeks to classify catalysts as “worth investigating” or “not worth investigating” experimentally. Our results show an ~7–16 times speedup in catalyst classification relative to random sampling. These results were based on offline simulations of our algorithm on two different datasets: a larger, synthesized dataset and a smaller, real dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Fluid structure interaction of a subaqueous pendulum: Analyzing the effect of wake correction via large eddy simulations

The dynamic behavior of a subaqueous cylindrical pendulum and corresponding flow dynamics are investigated. The objectives were twofold: (i) to examine whether the two-dimensional model equations sufficiently capture the three-dimensional dynamics and (ii) to investigate the emerging three-dimensional vortical flow structures. Large eddy simulations with two-way coupling fluid structure interaction were carried out using the immersed boundary method to simulate the motion of the pendulum and its interactions with the initially stagnant water. The resulting pendulum motion is compared against measured data obtained in a series of experimental tests to validate the simulation results and the model equations with and without wake corrections. An analysis of the flow vorticity revealed the development of a vortex ring during the first swing and the formation of tip vortices. The evolution of the vortex rings emerging from the motion of the subaqueous cylindrical pendulum was visualized using Q-criteria showing a reasonable agreement with vortical structures observed in the experiment using particle imaging velocimetry. The hydrodynamic moments acting on the simulated pendulum and the moments calculated from the model equations are analyzed. Using the insights from these numerical simulations, a modification of the wake correction is proposed to enhance the accuracy of the rate of decay and period. The transient effect of coherent flow on pendulum dynamics, especially the added mass effect, is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Platform for probing radiation transport properties of hydrogen at conditions found in the deep interiors of red dwarfs

We describe an experimental concept at the National Ignition Facility for specifically tailored spherical implosions to compress hydrogen to extreme densities (up to ∼800× solid density, electron number density ne∼4×1025 cm−3) at moderate temperatures (T∼200 eV), i.e., to conditions, which are relevant to the interiors of red dwarf stars. The dense plasma will be probed by laser-generated x-ray radiation of different photon energy to determine the plasma opacity due to collisional (free–free) absorption and Thomson scattering. The obtained results will benchmark radiation transport models, which in the case for free–free absorption show strong deviations at conditions relevant to red dwarfs. This very first experimental test of free–free opacity models at these extreme states will help to constrain where inside those celestial objects energy transport is dominated by radiation or convection. Moreover, our study will inform models for other important processes in dense plasmas, which are based on electron–ion collisions, e.g., stopping of swift ions or electron–ion temperature relaxation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Tuning perovskite nanocrystal superlattices for superradiance in the presence of disorder

The cooperative emission of interacting nanocrystals is an exciting topic fueled by recent reports of superfluorescence and superradiance in assemblies of perovskite nanocubes. Several studies estimated that coherent coupling is localized to a small fraction of nanocrystals (10 -7 –10 -3 ) within the assembly, raising questions about the origins of localization and ways to overcome it. In this work, we examine single-excitation superradiance by calculating radiative decays and the distribution of superradiant wave function in two-dimensional CsPbBr 3 nanocube superlattices. The calculations reveal that the energy disorder caused by size distribution and large interparticle separations reduces radiative coupling and leads to the excitation localization, with the energy disorder being the dominant factor. The single-excitation model clearly predicts that, in the pursuit of cooperative effects, having identical nanocubes in the superlattice is more important than achieving a perfect spatial order. The monolayers of large CsPbBr 3 nanocubes (L NC = 10–20 nm) are proposed as model systems for experimental tests of superradiance under conditions of non-negligible size dispersion, while small nanocubes (L NC = 5–10 nm) are preferred for realizing the Dicke state under ideal conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

A compact low-level RF control system for advanced concept compact electron linear accelerator

A compact low-level RF (LLRF) control system based on RF system-on-chip (RFSoC) technology has been designed for the Advanced Concept Compact Electron Linear-accelerator (ACCEL) program, which has challenging requirements in both RF performance and size, weight, and power consumption (SWaP). The compact LLRF solution employs the direct RF sampling technique of RFSoC, which samples the RF signals directly without any analog upconversion and downconversion. Compared with the conventional heterodyne based architecture used for the LLRF system of a linear accelerator (LINAC), the elimination of analog mixers can significantly reduce the size and weight of the system, especially with LINAC requiring a larger number of RF channels. Based on the requirements of ACCEL, a prototype LLRF platform has been developed, and the control schemes have been proposed. The prototype LLRF system demonstrated magnitude and phase fluctuation levels below 1% and 1° on the flattop of a 2 μs RF pulse. The LLRF control schemes proposed for ACCEL are implemented with a prototype hardware platform. In conclusion, this paper will introduce the new compact LLRF solution and summarize a selection of experimental test results of the prototype itself and with the accelerating structure cavities designed for ACCEL.

Liu, C. [SLAC National Accelerator Laboratory (SLA↗
DOE OSTI2025

The role of sample–window coupling in shock temperature experiments

Radiometric studies of opaque materials under shock compression probe a sample–window interface that may be very different than the bulk state. Subtle experimental details, particularly an initial sample–window gap vs an adhesively bonded stack, have tremendous influence on measured temperature. This work experimentally tests gapped vs bonded targets and theoretically investigates observed differences in the measured temperature. The results indicate that perturbations created by a thin adhesive are smaller than those suggested by a previous work, whereas sample–window gaps alter the measured state more significantly than that previously realized.

Adhesives↗
DOE OSTI2026

Design and simulation of a muon detector to characterize geological overburden

This study presents the design, construction, and simulation of a mobile muon detector tailored for geological overburden characterization. The detector employs plastic scintillator paddles with silicon photomultipliers (SiPMs) and a QuarkNet data acquisition system, offering a portable solution suitable for remote field deployment. The simulator’s modular aluminum frame allows for adjustable geometry and directional sensitivity, while its battery system supports over a week of autonomous operation. Preliminary experimental tests confirmed that its muon flux measurements were consistent with theoretical expectations. A comprehensive simulation framework using Geant4 and CORSIKA was developed to model detector response and overburden effects. Analytical and Monte Carlo methods were used to assess quadrant resolution and infer muon directionality. This work lays the foundation for future overburden mapping and supports the development of reconstruction algorithms for geological applications.

72 - PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins

Significance Here we present an unprecedented multiscale simulation platform that enables modeling, hypothesis generation, and discovery across biologically relevant length and time scales to predict mechanisms that can be tested experimentally. We demonstrate that our predictive simulation-experimental validation loop generates accurate insights into RAS-membrane biology. Evaluating over 100,000 correlated simulations, we show that RAS–lipid interactions are dynamic and evolving, resulting in: 1) a reordering and selection of lipid domains in realistic eight-lipid bilayers, 2) clustering of RAS into multimers correlating with specific lipid fingerprints, 3) changes in the orientation of the RAS G-domain impacting its ability to interact with effectors, and 4) demonstration that RAS–RAS G-domain interfaces are nonspecific in these putative signaling domains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Balance of Plant Modeling and Real-Time Hardware-in-the-Loop Integration with the Microreactor Automated Control System

The advent of novel microreactor technology has driven a focused effort to explore safety and efficiency improvements that can be achieved through the use of automated system control. Development of control strategies, especially for initial demonstration, requires an adequate surrogate environment to safely research failure modes and control integration with realistic hardware delay. However, efficiency gains from control strategies are improved when the scope of controller action is expanded to include system-level dynamics such as downstream heat extraction and mass flow. For this reason, a balance-of-plant (BOP) model of a representative microreactor system has been developed using the TRANsient Simulation Framework of Reconfigurable Models library in Modelica. This model captures a reactor and primary NaK coolant loop that represent corresponding system components of the Microreactor Applications Research Validation and EvaLuation (MARVEL) design as well as a secondary coolant loop and heat extraction representative of the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET). This model configuration allows for hardware-in-the-loop (HIL) integration with microreactor automated control system (MACS) hardware in real time through a Python-based gRPC client. Real-time simulation of model performance with emulated hardware and communication delay suggests that under independent proportional-integral-derivative control of BOP model drum dynamics and downstream heat extraction, stable power load following is achievable. A slight delay in load following, filtering of high-frequency dynamics, and localized temperature fluctation suggest room for improvement through the development of higher-level control strategies. The simulated coupling of the MAGNET facility lays the groundwork for future digital twin analysis with a coupled MACS-MAGNET HIL demonstration.

McConnell, Jono [ORNL] (ORCID:0000000238984741)↗