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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 OSTI2024

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

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

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗
DOE OSTI2020

Macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite with the effects of dissolved carbonates under anoxic conditions

Manganese and its compounds have been extensively researched because of their far-reaching roles in a wide range of biogeochemical processes in natural systems. The (ad)sorption behavior of Mn(II), however, is poorly understood despite its important role as the primary reaction step for surface-catalyzed Mn(II) oxidation that is the principal abiotic process forming various Mn (oxyhydr)oxides in nature. Here, we systematically examined Mn(II) (ad)sorption to one of the most common natural sorbents, goethite, in oxygen- and carbonate-free systems. Traditional sorption edge and isotherm experiments were conducted by varying sorbate-to-sorbent ratio (0.027–15 μmol∙m -2 ) and solution pH (pH 5.0–9.0). The effects of dissolved carbonates on Mn(II) sorption were also assessed in a range of naturally prevalent concentrations (0.5–10 mM NaHCO 3 ). The Mn(II) uptake on goethite followed a typical Langmuir isotherm in the absence of dissolved carbonates, with increasing maximum adsorption capacities (Γ max ) from 0.19 at pH 6.5 to 3.4 μmol∙m -2 at pH 9.0. The presence of dissolved carbonates raised the extent of Mn(II) adsorption, which appeared to be directly correspondent to that of the adsorption of dissolved carbonates. Extended X-ray absorption fine structure (EXAFS) analysis indicated that Mn(II) predominantly formed inner-sphere binuclear bidentate surface complexes. Mn(II) uptake became deviated from the Langmuir model and showed a clear indication of surface precipitation when the Mn(II) sorption density (Γ) exceeded a threshold value in a given solution composition. This secondary Mn(II) phase was identified as rhodochrosite using X-ray diffraction (XRD) and transmission electron microscope (TEM). Furthermore, it would be plausible that a minor fraction of adsorbed Mn(II) coexisted with the secondary rhodochrosite according to a linear combination fitting (LCF) of the X-ray absorption near edge structure (XANES) spectra of Mn reference and samples. These systematic investigations of the macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite provide a critical avenue for disentangling surface-catalytic Mn(II) oxidation processes, which ultimately lead to the formation of diverse Mn (oxyhydr)oxides in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Single Small-Scale Plutonium Redox Reaction System Yields Three Crystallographically-Characterizable Organoplutonium Complexes

Here, an approach to obtaining substantial amounts of data from a hazardous starting material that can only be obtained and handled in small quantities is demonstrated by the investigation of a single small-scale reaction of cyclooctatetraene, C 8 H 8 , with a solution obtained from the reduction of Cp' 3 Pu (Cp' = C 5 H 4 SiMe 3 ) with potassium graphite. This one reaction coupled with oxidation of a product has provided single-crystal X-ray structural data on three organoplutonium compounds as well as information on redox chemistry thereby demonstrating an efficient route to new reactivity and structural information on this highly radioactive element. The crystal structures were obtained from the reduction of C 8 H 8 by a putative Pu(II) complex, (Cp' 3 Pu II ) 1– , generated in situ, to form the Pu(III) cyclooctatetraenide complex, [K(crypt)][(C 8 H 8 ) 2 Pu III ], 1-Pu , and the tetra(cyclopentadienyl) Pu(III) complex, [K(crypt)][Cp' 4 Pu III ], 2-Pu . Oxidation of the sample of 1-Pu with Ag(I) afforded a third organoplutonium complex that has been structurally characterized for the first time, (C 8 H 8 ) 2 Pu IV , 3-Pu . Complexes 1-Pu and 3-Pu contain Pu sandwiched between parallel (C 8 H 8 ) 2– rings. The (Cp' 4 Pu III ) – anion in 2-Pu features three η 5 -Cp' rings and one η 1 -Cp' ring, which is a rare example of a formal Pu–C η 1 -bond. In addition, this study addresses the challenge of small-scale synthesis imparted by radiological and material availability of transuranium isotopes, in particular that of pure metal samples. A route to an anhydrous Pu(III) starting material from the more readily available Pu IV O 2 was developed to facilitate reproducible syntheses and allow complete spectroscopic analysis of 1-Pu and 2-Pu . Pu IV O 2 was converted to Pu III Br 3 (DME) 2 (DME = CH 3 OCH 2 CH 2 OCH 3 ) and subsequently Pu III Br 3 (THF) x , which was used to independently synthesize 1-Pu , 2-Pu , and 3-Pu .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Derivation of A Representative Elementary Volume (REV) for Upscaled Two-Phase Flow in Porous Media

Relative permeability plays an important role in the upscaling of multiphase flow in porous media from the pore scale to the Darcy scale. The entire concept of relative permeability is contingent on the existence of a representative elementary volume (REV). As we move to smaller samples to measure relative permeability, such as with digital core analysis, the concept of a classical REV has become increasingly unlikely when using the conventional approach to defining a representative volume. The “‘conventional”’ understanding of an REV is that a large enough volume must be considered such that spatial variability averages out. In digital rock methods, such as pore-scale simulations based on micro-computed tomography (CT) images, the domain size is typically 2 to 4 mm. This is approximately the length scale of a single-phase flow REV using the classic REV approach. However, the single-phase perspective does not consider the complex dynamics and fluctuations often observed in multiphase flow systems, even at centimeter-scale experiments and/or simulations. A fundamental question is, therefore, whether the domain size commonly used in digital rock simulations can provide a consistent energy budget such that the concept of relative permeability exists. Based on first principles, relative permeability accounts for the rate of energy dissipated in a stationary process. If the dynamics are fluctuating, the energy dissipated can vary but will average out over a long enough timescale. The key to determining the validity of the relative permeability is the timescale of the measurement, not the spatial scale. The conventional REV theory assumes that spatial, temporal, and ensemble averages are equivalent in an ergodic system, but it does not provide a way to test this assumption. We provide a formal way to identify the timescale where the relative permeability accurately captures energy dissipation as a way to validate relative permeability measurements and quantitatively assess their accuracy. This result will be tested for a practical SCAL test, determining how long a flow experiment needs to be run to accurately characterize the rate of energy dissipation by the flow. The outcome will be a best practice guide for the determination of relative permeability from core-scale experiments and/or digital core simulations that ensure the energy budget is fully accounted for in the relative permeability coefficient.

Mcclure, James [Virginia Tech, Blacksburg]↗
DOE OSTI2023

Cryogenic X-ray crystallographic studies of biomacromolecules at Turkish Light Source " Turkish DeLight "

X-ray crystallography is a robust and powerful structural biology technique that provides high-resolution atomic structures of biomacromolecules. Scientists use this technique to unravel mechanistic and structural details of biological macromolecules (e.g., proteins, nucleic acids, protein complexes, protein-nucleic acid complexes, or large biological compartments). Since its inception, single-crystal cryocrystallography has never been performed in Türkiye due to the lack of a single-crystal X-ray diffractometer. The X-ray diffraction facility recently established at the University of Health Sciences, Istanbul, Türkiye will enable Turkish and international researchers to easily perform high-resolution structural analysis of biomacromolecules from single crystals. Here, we describe the technical and practical outlook of a state-of-the-art home-source X-ray, using lysozyme as a model protein. The methods and practice described in this article can be applied to any biological sample for structural studies. Therefore, this article will be a valuable practical guide from sample preparation to data analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X-Ray Electron Density Maps

Here, proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand , to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox.

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

Chemical imaging of individual stratospheric particles sampled over North America

The increasing size, severity, and frequency of wildfires have led to dramatic increases in particulate matter concentrations in the troposphere. Severe wildfires can generate intense convective systems capable of transporting large quantities of biomass burning organic aerosols (BBOA) to the upper troposphere and lower stratosphere (UTLS). Chemically complex organic matter and light-absorbing carbonaceous material is introduced into stratospheric regions that were historically isolated from direct surface emissions. In this study, stratospheric particles were sampled over North America during the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) campaign, an aircraft-based research project designed to characterize convective perturbation in the UTLS. Particle samples collected from six research flights during summer 2022 were analyzed using Computer-Controlled Scanning Electron Microscopy and Scanning Transmission X-ray Microscopy to investigate particle size distributions, morphology, chemical composition, and mixing state of stratospheric particles along transects across the continental United States and adjacent Pacific Ocean airspace. Analysis revealed that all sampled particles contained detectable levels of carbon, with most exhibiting organic volume fractions of 0.37 ± 0.20. Notably, about 5% of the particles also contained soot inclusions, which indicates the presence of refractory black carbon transported to stratospheric altitudes and provides direct evidence of wildfire-derived black carbon reaching the UTLS. Typical particle morphology exhibits organic shells over soot and inorganic cores and suggests secondary processing and aging of BBOA during transport to and within the UTLS. These findings provide compelling evidence that wildfire emissions play a critical role in affecting the long-term composition and radiative properties of stratospheric particles.

Sharpe, Steven [Purdue Univ., West Lafayette, IN (↗
DOE OSTI2018

Survey of DAKOTA's V&V Capabilities in the Simulation of Residual Stresses in a Simple Composite Structure

Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses can result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, a process modeling methodology was developed and implemented into Sandia National Laboratories' SIERRA/SolidMechanics code. This method can be used to predict the process-induced stresses in any composite structure, regardless of material composition or geometric complexity. However, to develop confidence in these predictions, they must be rigorously validated. Specifically, sensitivity studies should be completed to define which model parameters are critical to the residual stress predictions. Then, the uncertainty associated with those critical parameters should be quantified and processed through the model to develop stress-state predictions encompassing the most important sources of physical variability. Numerous sensitivity analysis and uncertainty quantification methods exist, each offering specific strengths and weaknesses. Therefore, the objective of this study is to compare the performance of several accepted sensitivity analysis and uncertainty quantification methods during the manufacturing process simulation of a composite structure. The examined methods include simple sampling techniques as well as more sophisticated surrogate approaches. The computational costs are assessed for each of the examined methods, and the results of the study indicate that the surrogate approaches are the most computationally efficient validation methods and are ideal for future residual stress investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High Strain Response and Dielectric Properties of Bi 1/2 (Na 0.78 K 0.22 ) 1/2 TiO 3 Ceramics Doped with (Fe 1/2 Nb 1/2 ) 4+

Environmentally friendly piezoceramics Bi 1/2 (Na 0.78 K 0.22 ) 1/2 Ti 1-x (Fe 1/2 Nb 1/2 ) x O 3 (BNKT-FN) with FeNb (FN) ratios 0, 0.01, 0.02, 0.03 and 0.04 were synthesized via conventional solid-state reaction (CSSR). X-ray diffraction (XRD) analysis revealed that the FN complexes were completely dissolved in BNKT perovskite and the structural transition occurred from ferroelectric to relaxor state. The average grain sizes for x = 0, 0.01, 0.02, 0.03 and 0.04 were found to be 0.34 μm, 0.35 μm, 0.38 μm, 0.32 μm and 0.39 μm, respectively. It is observed that the grain size increased with the addition of FN, except for x = 0.03. Here, the coercive field (E c ) and remnant polarization (P r ) of the system were decreased with increasing FN concentration and the highest E c of 21.1 kV/cm and P r of 29.2 μC/cm 2 were noted for the base pure sample. In addition, the increase of FN content steadily broadened the dielectric anomaly at maximum dielectric constant temperature (T m ) in the BNKT-FN system. Consequently, unipolar normalized strain (S max /E max ) was found to be enhanced monotonically achieving the highest value of around 654 pm/V (x = 0.02). These properties suggest that the investigated system could be a promising eco-friendly candidate for piezoelectric actuators and many other applications requiring high piezoelectric induced strain.

25 ENERGY STORAGE↗
DOE OSTI2018

Applicability of the thin-film approximation in terahertz photoconductivity measurements

Thin mesoporous photoconductive layers are critically important for efficient water-spitting solar cells. A detailed understanding of photoconductivity in these materials can be achieved via terahertz transient absorption measurements. Such measurements are commonly interpreted using the thin-film approximation. We compare this approximation with a numerical solution of the transfer function without approximations using experimental results for thin-film mesoporous tin oxide (SnO 2 ) samples which range in thickness from 3.3 to 12.6 µm. These samples were sensitized with either a ruthenium polypyridyl complex or a porphyrin dye. The two sensitizers have markedly different absorption coefficients, resulting in penetration depths of 15 µm and 1 µm, respectively. The thin-film approximation results are in good agreement with the numerical work-up for the short penetration length dye. For the longer penetration length samples, the thin-film formula fails even for thicknesses of only 3 µm ≈ λ/100. The imaginary part of the conductivity calculated using the thin-film formula was significantly larger in magnitude than the value without approximations. This discrepancy between the commonly used thin-film approximation and the numerical solution demonstrates the need for a careful analysis of the thin-film formula.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

SO(3)-invariant PCA with application to molecular data

Principal component analysis (PCA) is a fundamental technique for dimensionality reduction and denoising; however, its application to three-dimensional data with arbitrary orientations -- common in structural biology -- presents significant challenges. A naive approach requires augmenting the dataset with many rotated copies of each sample, incurring prohibitive computational costs. In this paper, we extend PCA to 3D volumetric datasets with unknown orientations by developing an efficient and principled framework for SO(3)-invariant PCA that implicitly accounts for all rotations without explicit data augmentation. By exploiting underlying algebraic structure, we demonstrate that the computation involves only the square root of the total number of covariance entries, resulting in a substantial reduction in complexity. We validate the method on real-world molecular datasets, demonstrating its effectiveness and opening up new possibilities for large-scale, high-dimensional reconstruction problems.

Fraiman, Michael [Tel Aviv Univ., Tel Aviv (Israel↗
DOE OSTI2022

Finite Element Modeling of Electrochemical Polishing of Niobium in Hydrofluoric-Sulfuric Acid Electrolyte

Niobium (Nb) used in superconducting radio-frequency cavities requires smooth surface to achieve optimal performance. In this work, a finite element model that coupled electrochemistry, heat transfer, and fluid dynamics was developed to investigate the electrochemical polishing mechanisms of Nb, using experimentally measured polarization results of coupon samples as validations. The current and potential distribution, oxide growth kinetics of Nb in a complex cavity geometry was investigated as a function of temperature and coolant flow. A low temperature coolant with intermediate flow rate was found to reduce surface current and ensure oxide uniformity. These results could shed light on the design of future particle accelerators.

SRF accelerator cavity↗
DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗
DOE OSTI2018

Plakophilin3 loss leads to an increase in lipocalin2 expression, which is required for tumour formation

Highlights: • Plakophilin3 loss leads to an increase in LCN2 expression in multiple cell types. • The increase in LCN2 expression is dependent on the activity of p38 MAPK. • Plakophilin3 inhibits LCN2 expression by restricting p38 MAPK to the cytoplasm. • The increase in LCN2 expression is required for tumour formation upon plakophilin3 loss. An increase in tumour formation and metastasis are observed upon plakophilin3 (PKP3) loss. To identify pathways downstream of PKP3 loss that are required for increased tumour formation, a gene expression analysis was performed, which demonstrated that the expression of lipocalin2 (LCN2) was elevated upon PKP3 loss and this is consistent with expression data from human tumour samples suggesting that PKP3 loss correlates with an increase in LCN2 expression. PKP3 loss leads to an increase in invasion, tumour formation and metastasis and these phenotypes were dependent on the increase in LCN2 expression. The increased LCN2 expression was due to an increase in the activation of p38 MAPK in the HCT116 derived PKP3 knockdown clones as LCN2 expression decreased upon inhibition of p38 MAPK. The phosphorylated active form of p38 MAPK is translocated to the nucleus upon PKP3 loss and is dependent on complex formation between p38 MAPK and PKP3. WT PKP3 inhibits LCN2 reporter activity in PKP3 knockdown cells but a PKP3 mutant that fails to form a complex with p38 MAPK cannot suppress LCN2 promoter activity. Further, LCN2 expression is decreased upon loss of p38β, but not p38α, in the PKP3 knockdown cells. These results suggest that PKP3 loss leads to an increase in the nuclear translocation of p38 MAPK and p38β MAPK is required for the increase in LCN2 expression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations

Abstract Motivation Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. Results We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. Availability and implementation It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Du, Lin (ORCID:0009000289869812)↗
DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗