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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Geometry optimization speedup through a geodesic approach to internal coordinates

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Overall, our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Time evolution of ML-MCTDH wavefunctions. II. Application of the projector splitting integrator

The multi-layer multi-configuration time-dependent Hartree (ML-MCTDH) approach can suffer from numerical instabilities whenever the wavefunction is weakly entangled. These instabilities arise from singularities in the equations of motion (EOMs) and necessitate the use of regularization of the EOMs. The Projector Splitting Integrator (PSI) has previously been presented as an approach for evolving ML-MCTDH wavefunctions that is free of singularities. Here, we will discuss the implementation of the multi-layer PSI with a particular focus on how the steps required relate to those required to implement standard ML-MCTDH. We demonstrate the efficiency and stability of the PSI for large ML-MCTDH wavefunctions containing up to hundreds of thousands of nodes by considering a series of spin-boson models with up to 106 bath modes and find that for these problems, the PSI requires roughly 3–4 orders of magnitude fewer Hamiltonian evaluations and 2–3 orders of magnitude fewer Hamiltonian applications than standard ML-MCTDH and 2–3/1–2 orders of magnitude fewer evaluations/applications than approaches that use improved regularization schemes. Finally, we consider a series of significantly more challenging multi-spin-boson models that require much larger numbers of single-particle functions with wavefunctions containing up to ~1.3×10 9 parameters to obtain accurate dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π-π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single–amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single– and multiple–amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

An in vitro BRAF activation assay elucidates molecular mechanisms driving disassembly of the autoinhibited BRAF state

The RAF kinases (ARAF, BRAF, and CRAF) are essential components of the RAS-ERK signaling pathway, which controls vital cellular processes and is frequently dysregulated in human disease. Notably, mutations that alter BRAF function are prominent drivers of human cancer and certain RASopathy disorders, making BRAF an important target for therapeutic intervention. Despite extensive research, several aspects of BRAF regulation remain unclear. In this study, we developed an in vitro BRAF activation assay using purified autoinhibited BRAF:14-3-3 2 :MEK complexes. Our results show that fully processed, active-state KRAS alone can promote dimer-dependent BRAF activation. Moreover, we found that phosphatidylserine (PS)-containing liposomes synergized with KRAS to promote BRAF activation, achieving activity levels comparable to those observed with BRAF proteins that constitutively dimerize. In contrast, the SMP phosphatase complex had only a minimal effect on BRAF catalytic activity in this system but mediated the dephosphorylation of the negative regulatory pS365 14-3-3 binding site in a manner that was accelerated by the presence of KRAS alone or KRAS and 30% PS liposomes. Finally, we show that inhibitors blocking the BRAF RBD:KRAS interaction were able to suppress the in vitro activation of BRAF, underscoring the critical role of RAS binding in initiating the disassembly of the BRAF autoinhibited state. Thus, this assay provides valuable insights into the steps required for BRAF activation and can serve as an effective screening tool for identifying compounds that may inhibit this process and have therapeutic potential.

BRAF↗
DOE OSTI2023

Modeling Geologic Waste Repository Systems Below Residual Saturation

The heat generated by high-level radioactive waste can pose numerical and physical challenges to subsurface flow and transport simulators if the liquid water content in a region near the waste package approaches residual saturation due to evaporation. Here, residual saturation is the fraction of the pore space occupied by liquid water when the hydraulic connectivity through a porous medium is lost, preventing the flow of liquid water. While conventional capillary pressure models represent residual saturation using asymptotically large values of capillary pressure, here, residual saturation is effectively modeled as a tortuosity effect alone. Treating the residual fluid as primarily dead-end pores and adsorbed films, relative permeability is independent of capillary pressure below residual saturation. To test this approach, PFLOTRAN is then used to simulate thermal-hydrological conditions resulting from direct disposal of a dual-purpose canister in unsaturated alluvium using both conventional asymptotic and revised, smooth models. Importantly, while the two models have comparable results over 100 000 years, the number of flow steps required is reduced by approximately 94%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗
DOE OSTI2020

Efficient and Flexible Sensitivity Matrix Computation for Adaptive Electrical Capacitance Volume Tomography

Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive Electrical Capacitance Volume Tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imaging and an improved resolution. Construction of the sensitivity matrix is a necessary step to obtain flow images. This step requires computation of the electric field inside the sensing domain, which is done via a typical field solver such as the finite element method. In this work, we present an efficient and flexible method to construct the sensitivity matrix for Adaptive Electrical Capacitance Volume Tomography (AECVT) based on individual electrode segment excitations and their judicious combination to form desired matrix elements. We illustrate how the proposed method yields the same sensitivity matrix as the traditional method but at a much lower computational cost. Once all segment contributions are obtained, we also indicate how the proposed method, unlike the traditional approach, can generate the sensitivity matrix on demand for an arbitrary combination of synthetic electrodes and obviating the need for any additional field computations. Finally, we present image reconstruction results for two different experimental scenarios where the mutual capacitance data and the corresponding sensitivity vectors are obtained through the proposed measurement combination scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

2.7 Å cryo-EM structure of rotavirus core protein VP3, a unique capping machine with a helicase activity

In many viruses, including rotavirus (RV), the major pathogen of infantile gastroenteritis, capping of viral messenger RNAs is a pivotal step for efficient translation of the viral genome. In RV, VP3 caps the nascent transcripts synthesized from the genomic dsRNA segments by the RV polymerase VP1 within the particle core. Here, from cryo–electron microscopy, x-ray crystallography, and biochemical analyses, we show that VP3 forms a stable tetrameric assembly with each subunit having a modular domain organization, which uniquely integrates five distinct enzymatic steps required for capping the transcripts. In addition to the previously known guanylyl- and methyltransferase activities, we show that VP3 exhibits hitherto unsuspected RNA triphosphatase activity necessary for initiating transcript capping and RNA helicase activity likely required for separating the RNA duplex formed transiently during endogenous transcription. From our studies, we propose a new mechanism for how VP3 inside the virion core caps the nascent transcripts exiting from the polymerase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

LIM1TR: Lithium-Ion Modeling with 1-D Thermal Runaway (V.1.0)

LIM1TR (Lithium-Ion Modeling with 1-D Thermal Runaway) is an open-source code that uses the finite volume method to simulate heat transfer and chemical kinetics on a quasi 1-D domain. The target application of this software is to simulate thermal runaway in systems of lithium-ion batteries. The source code for LIM1TR can be found at https://github.com/ajkur/lim1tr. This user guide details the steps required to create and run simulations with LIM1TR starting with setting up the Python environment, generating an input file, and running a simulation. Additional details are provided on the output of LIM1TR as well as extending the code with custom reaction models. This user guide concludes with simple example analyses of common battery thermal runaway scenarios. The corresponding input files and processing scripts can be found in the “Examples” folder in the on-line repository, with select input files included in the appendix of this document.

25 ENERGY STORAGE↗
DOE OSTI2023

Disruption Mitigation Solutions for Long Pulse Tokamaks (Final Technical Report)

The project "Disruption Mitigation Solutions for Long Pulse Tokamaks" was a collaborative effort between ORNL, GA, and UCSD. The main goal of the project was to study the injection of shattered cryogenic pellets (SPI) as a method of reducing wall damage from global tokamak plasma instabilities called disruptions. This work was primarily carried out in the JET tokamak in the UK. The team already had extensive experience studying PSI in the medium sized DIII-D tokamak in the US, but adding data from the larger JET tokamak enabled more confident extrapolation to the even larger planned ITER tokamak in France. Each of the collaborating institutions focused on different aspects of SPI disruption mitigation. The UCSD collaboration focused on the volume recombination of post-disruption runaway electron (RE) beams by massive hydrogen injection. Disruptions can sometimes result in the formation of toroidal (ring shaped) beams of highly energetic (relativistic) electron beams, which can cause serious local wall damage, even in present-day tokamaks. A promising method to reduce wall damage from the RE beams is to inject massive amounts of H 2 or D 2 into the beams using SPI. although the precise method by which the injected H 2 reducses RE wall damage is still being investigated, it seems clear that a necessary and required step for the reduction to occur is for the H 2 injection to cause volume recombination (free electron density reduction) of the background cold plasma surrounding the fast electron beam. The UCSD collaboration focused on answering the question of if this recombination could be achievable in the future reactor-size tokamak ITER using realistic levels of H 2 injection. A model capturing the most essential physics was developed and was constrained using both DIII-D and JET data. This model was then used to extrapolate to ITER. It was predicted that RE beam recombination should be achievable in ITER, although in the worst-case scenari (a 10 MA Re beam in ITER), recombination is barely achieved within the maximum allowed levels of H 2 injection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Post-growth Recrystallization by Halides for High Throughput CIGS Photovoltaics

The objective of this project in broad terms was to address the capital equipment expense associated with Cu(In,Ga)Se 2 (CIGS) as a material for photovoltaic devices. This project has demonstrated a new method for processing CIGS using metal halides to recrystallize and enhance the quality of the final materials. A wide spectrum of metal halides were examined. Of these Cu and In chlorides and AgBr were found to be most effective; and, of these, AgBr was found to produce exemplary results. Cu and In chlorides were found to produce undesirable changes in film composition. The project demonstrated over 16% efficiency in a CIGS device deposited at 10x the standard rate of ~1 μm/hr and with a >100°C reduction in maximum temperature to 450°C. The entire deposition of the absorber layer including the recrystallization step required only 15 minutes, which is a 4x decrease in processing time.

14 SOLAR ENERGY↗
DOE OSTI2023

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗
DOE OSTI2022

HME MicroCT Data Acquisition, Processing and Data Request Overview

This document is a short summary of the steps required for MicroCT evaluation of a specimen. This includes data acquisition through image analysis, for the Explosives Threat Assessment (ETA) program. Expected outputs for each stage are outlined. Information and data shall be shipped to LLNL as described herein.

42 ENGINEERING↗
DOE OSTI2024

NuMI/LBNF Horn and Stripline Welding

Focusing horns for secondary particles are critical components for creating a stable beam of neutrinos. These components need to survive in a harsh environment and withstand high stresses. Extending the lifetime of the horns is critical as spare fabrication takes approximately two years and has many subcomponents with strict quality control. Two key aspects of the fabrication process include the inner conductor CNC TIG welding and the friction stir welding of the stripline pieces. The process for welding requires steps such as sample welding, x-ray imaging, and tensile pull tests. Having a perfect weld retains as much of the original strength of the base metal and reduces the risk of failure. As FNAL ramps up in power to 2.4MW, the lifetime of the horn and stripline will more heavily rely on continuing to have high quality welding procedures and thorough quality assurance.

Orea, Adrian↗
DOE OSTI2025

Determining the Axes of a Range-Doppler Image

Synthetic aperture radar (SAR) images formed with dechirp-on-receive data collection and rectangular format processing algorithm are the result of a two-dimensional discrete Fourier transform (DFT) applied to sampled data. There are several steps required to compute the range and Doppler values associated with each pixel in a SAR range-Doppler image. This memo walks readers through the process.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Findings from Large Bench-Scale Testing of Denitration Electrolyzers for the EDCGe Project

This report highlights the key findings and outcomes relevant to the processability of waste supernatant at Hanford using a denitration electrolyzer. The Electrosynthesis Company issued a Phase 1 report to the Savannah River National Laboratory (SRNL), summarizing the evaluation of large bench-scale denitration electrolyzers to support the electrochemical denitration and caustic generation (EDCGe) project. The Electrosynthesis Company’s report (attached as Appendix A) provides insights into the initial steps required to implement an electrolyzer system at Hanford. Phase 1 experiments focused on validating the denitration electrolyzer’s performance, operating parameters, and reaction products. The robustness of the electrochemical denitration process was demonstrated by two electrolyzer flow cell systems (a 100 cm 2 ElectroCell MP and a 150 cm 2 NESI NS01 cell), both of which achieved significant nitrate and nitrite removal (>50%) with a current efficiency of ~95% for both systems. Higher current densities (500 mA cm –2 ) improved nitrate and nitrite removal rates compared to lower current densities (333 mA cm –2 ), while maintaining a current efficiency of ~94%. The NS01 cell achieved a nitrate species removal rate of ~0.41 mol h –1 at 5 kA m –2 (equiv. to 500 mA cm –2 ). The primary reaction product was ammonia (NH 3 ), constituting 78.3–91.6% of the products (excluding OH – formation). NH 3 was predominantly retained in the catholyte liquid phase rather than being off-gassed. Additionally, the NS01 cell reported an NH 3 generation rate of ~0.36 mol h –1 at 5 kA m –2 . Other gas formation included ~7% N 2 , ~7% H 2 , and trace amounts of N 2 O. The estimated power requirement (extrapolated from the 0.015 m 2 cell data) for a full-scale denitration electrolyzer is approximated to be ~1.6 MW (DC-only) to treat 50% of nitrate and nitrite in a waste stream and generates ~2.1 kmol h –1 of NH 3 with an initial concentration of 4 M NO 3 – /NO 2 – at 300 gal h –1 . Simulated waste containing aluminate, carbonate, oxalate, and halogens exhibited no adverse effects on denitration performance. A preliminary experiment comparing alkaline anolyte (5 M NaOH) with a nickel based anode to acidic media (2 M H 2 SO 4 ) with a DSA-O 2 anode showed a lower operating voltage and generated less H 2 than the acid media. Maintaining a stable 5 M OH – concentration in the anolyte through periodic additions of caustic did not significantly impact denitration performance. This operational mode will be required for long-term experiments. All the experiments demonstrated that electrochemical denitration is a promising approach for treating nitrate and nitrite in simulated waste streams, achieving significant conversion and robustness across varying experimental conditions and electrochemical cell configurations. Lastly, the ability to generate a nearly pure NH 3 stream may prove advantageous for processing at other locations within the Hanford site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Altered ß-cell Prohormone Processing and Secretion in Type 1 Diabetes

Analysis of data from clinical cohorts and more recently from human pancreatic tissue, indicate that defects in prohormone processing are an early and persistent component of type 1 diabetes pathogenesis. In this Perspectives article, we review the current state of knowledge of alterations in islet prohormone expression and processing in type 1 diabetes, and consider the clinical impact of these findings. Lingering questions, including pathologic etiologies and consequences of altered prohormone expression and secretion in type 1 diabetes, and the natural history of circulating prohormone production in health and disease are considered. Finally, key steps required to move forward in this area are outlined, including longitudinal testing of relevant clinical populations, studies that probe the genetics of altered prohormone processing, the need for combined functional and histologic testing of human pancreatic tissues, continued interrogation of the intersection between prohormone processing and autoimmunity, and optimal assays or approaches for analysis. Successful resolution of these questions may offer the potential to use altered prohormone processing as a pathogenic anchor that can be used to cluster different endotypes enveloping a large set of variables, and inform therapeutic strategies aimed at personalized intervention in the natural history of type 1 diabetes.

Islets, Insulin, Proinsulin, Islet Amyloid Polypep↗