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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

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

Introduction Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks. Methods We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph). Results The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing. Discussion Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git .

Chen, Xiaoyi↗
DOE OSTI2021

Crystalline Supramolecular Polymers: Dynamics, Chirality, and Function

Inspired by biological systems, supramolecular polymers have emerged over the past three decades as an important way to form functional structures with potential to tune the internal order and dynamics and to create materials with the potential for responsiveness, reconfigurability, and recyclability. We focus here on several recent examples of ordered supramolecular polymers with a significant extent of internal order that results in crystalline molecular packing, or with dynamics that allow them to undergo structural reconfiguration. These examples highlight the spectrum of molecular mobility that the noncovalently bound constituents can experience. Furthermore, these materials have found interesting functions in their interaction with chiral biological systems and in their ability to form materials with interesting optoelectronic and photocatalytic behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Intermittency and Dissipative Structures Arising from Relativistic Magnetized Turbulence

Abstract Kinetic simulations of relativistic turbulence have significantly advanced our understanding of turbulent particle acceleration. Recent progress has highlighted the need for an updated acceleration theory that can account for particle acceleration within the plasma’s coherent structures. Here, we investigate how intermittency modeling connects statistical fluctuations in turbulence to regions of high-energy dissipation. This connection is established by employing a generalized She–Leveque model to characterize the exponents ζ p for the structure functions S p ∝ l ζ p . The fitting of the scaling exponents provides us with a measure of the codimension of the dissipative structures, for which we subsequently determine the filling fraction. We perform our analysis for a range of magnetizations σ and relative fluctuation amplitudes δ B 0 / B 0 . We find that increasing values of σ and δ B 0 / B 0 allow the turbulent cascade to break sheetlike structures into smaller regions of dissipation that resemble chains of flux ropes. However, as their dissipation measure increases, the dissipative regions become less volume filling. With this work, we aim to inform future turbulent acceleration theories that incorporate particle energization from interactions with coherent structures within relativistic turbulence.

Astronomy & Astrophysics↗
DOE OSTI2025

Ligand-Functionalized Polymer Membranes for Selective Ion Separations

Selective ion separations are central to technologies spanning water purification, resource recovery, and clean energy. Conventional polymer membranes, which rely on steric hindrance or Donnan exclusion, struggle to discriminate between chemically similar ions in high-ionic-strength environments. Ligand-functionalized membranes offer a transformative strategy by embedding molecular recognition directly into polymer matrices, enabling selective complexation and transport. Here, this Viewpoint highlights the structure–function relationships underlying ligand-mediated ion separation, emphasizing the interplay of dehydration penalties, ligand coordination, and nanoscale confinement. We discuss design principles, denticity, donor identity, rigidity, and spatial organization, alongside the permeability–selectivity trade-off, multicomponent effects, and stability challenges. Finally, we outline emerging strategies, from bioinspired ligands to computationally guided design, that chart a path toward next-generation membranes for precise and energy-efficient ion separations.

ions↗
DOE OSTI2024

Enhancing Chiroptoelectronic Activity in Chiral 2D Perovskites via Chiral–Achiral Cation Mixing

Rational design of chiral two-dimensional hybrid organic–inorganic perovskites is crucial to achieve chiroptoelecronic, spintronic, and ferroelectric applications. Here, in this study, an efficient way to manipulate the chiroptoelectronic activity of 2D lead iodide perovskites is reported by forming mixed chiral (R- or S-methylbenzylammonium (R-MBA + or S-MBA + )) and achiral (n-butylammonium (nBA + )) cations in the organic layer. The strongest and flipped circular dichroism signals are observed in (R/S-MBA 0.5 nBA 0.5 ) 2 PbI 4 films compared to (R/S-MBA) 2 PbI 4 . Moreover, the (R/S-MBA 0.5 nBA 0.5 ) 2 PbI 4 films exhibit pseudo-symmetric, unchanged circularly polarized photoluminescence peak as temperature increases. First-principles calculations reveal that mixed chiral–achiral cations enhance the asymmetric hydrogen-bonding interaction between the organic and inorganic layers, causing more structural distortion, thus, larger spin-polarized band-splitting than pure chiral cations. Temperature-dependent powder X-ray diffraction and pair distribution function structure studies show the compressed intralayer lattice with enlarged interlayer spacing and increased local ordering. Overall, this work demonstrates a new method to tune chiral and chiroptoelectronic properties and reveals their atomic scale structural origins.

2D perovskites↗
DOE OSTI2023

Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts

Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.

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

Visualization of the HIV-1 Env glycan shield across scales

The dense array of N-linked glycans on the HIV-1 envelope glycoprotein (Env), known as the “glycan shield,” is a key determinant of immunogenicity, yet intrinsic heterogeneity confounds typical structure–function analysis. Here, we present an integrated approach of single-particle electron cryomicroscopy (cryo-EM), computational modeling, and site-specific mass spectrometry (MS) to probe glycan shield structure and behavior at multiple levels. We found that dynamics lead to an extensive network of interglycan interactions that drive the formation of higher-order structure within the glycan shield. This structure defines diffuse boundaries between buried and exposed protein surface and creates a mapping of potentially immunogenic sites on Env. Analysis of Env expressed in different cell lines revealed how cryo-EM can detect subtle changes in glycan occupancy, composition, and dynamics that impact glycan shield structure and epitope accessibility. Importantly, this identified unforeseen changes in the glycan shield of Env obtained from expression in the same cell line used for vaccine production. Finally, by capturing the enzymatic deglycosylation of Env in a time-resolved manner, we found that highly connected glycan clusters are resistant to digestion and help stabilize the prefusion trimer, suggesting the glycan shield may function beyond immune evasion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Structural Design Variations in Beetle Elytra

Abstract Beetles typically use their protective wing coverings or elytra to shield their membranous hindwings from the environment. Elytra in some terrestrial species have evolved a greater protective role capable of shielding the organism from powerful antagonistic predators. The structure–function relationships of these biological composites identify how architectural and chemical variations of the cuticle are tuned to create light‐weight, impact resistant composites. Specifically, the elytral structures of a tree dwelling beetle capable of flight, Trypoxylus dichotomus , and a terrestrial beetle incapable of flight, Phloeodes diabolicus , are compared to understand how their varied environmental needs forged the elytra to facilitate fight or resist fatal predator strikes. Mechanical and microstructural analysis reveals P . diabolicus has a harder, stiffer elytra that incorporate through‐thickness fibers to resist greater mechanical stresses imposed by bending and puncture. Conversely, the elytra of T . dichotomus have a compliant structure with large voids that facilitates localized deformation. Variations in flexural strength and puncture resistance remain attributed to P . diabolicus possessing a thicker cuticle with a greater degree of cross‐linking and an increased amount of endocuticular layers. These findings may provide useful insight into the design and manufacturing of composite materials for use in light‐weight or energy‐absorbing applications.

Rivera, Jesus↗
DOE OSTI2025

CO 2 Capture Characteristics of Hyperbranched Poly(alkylene imine): A Molecular Dynamics Simulation Approach

This study explores the CO 2 capture characteristics of hyperbranched poly(ethylenimine) (HB-PEI) and poly- (propyleneimine) (HB-PPI) through molecular dynamics simulations using density functional theory-calibrated force fields. Key features such as density, free volume, glass transition temperature, CO 2 /H 2 O distribution, and molecular diffusion are systematically investigated to elucidate structure−function relationships under dry and hydrated conditions. HB-PEI demonstrates a slightly higher density and lower free volume compared to HB-PPI yet shows superior CO 2 capture due to the high amine concentration. Glass transition analysis indicates a higher thermal mobility in HBPEI, enhancing the CO 2 diffusivity. Pair correlation and coordination analyses confirm a stronger affinity of CO 2 with primary and secondary amines, particularly in hydrated environments where water competes with CO 2 for binding sites. Despite its more compact structure, HB-PEI outperformed HB-PPI in CO 2 and H 2 O transport, as confirmed by higher diffusion coefficients across all hydration levels. These findings highlight a critical balance among polymer architecture, amine accessibility, and hydration in designing next-generation solid amine sorbents for efficient direct air capture applications.

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

Out-of-equilibrium processes in crystallization of organic-inorganic perovskites during spin coating

Complex phenomena are prevalent during the formation of materials, which affect their processing-structure-function relationships. Thin films of methylammonium lead iodide (CH 3 NH 3 PbI 3 , MAPI) are processed by spin coating, antisolvent drop, and annealing of colloidal precursors. The structure and properties of transient and stable phases formed during the process are reported, and the mechanistic insights of the underlying transitions are revealed by combining in situ data from grazing-incidence wide-angle X-ray scattering and photoluminescence spectroscopy. Here, we report the detailed insights on the embryonic stages of organic-inorganic perovskite formation. The physicochemical evolution during the conversion proceeds in four steps: i) An instant nucleation of polydisperse MAPI nanocrystals on antisolvent drop, ii) the instantaneous partial conversion of metastable nanocrystals into orthorhombic solvent-complex by cluster coalescence, iii) the thermal decomposition (dissolution) of the stable solvent-complex into plumboiodide fragments upon evaporation of solvent from the complex and iv) the formation (recrystallization) of cubic MAPI crystals in thin film.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Small-𝑥 Factorization in the Target Fragmentation Region

We consider the differential cross-section for single-inclusive jet production with transverse momentum 𝑃 ⊥ in deep inelastic scattering at small Bjorken 𝑥 Bj , mediated by a virtual photon with virtuality 𝑄 2 . Unlike most studies at small 𝑥, which focus on particle production in the current fragmentation region, we investigate the kinematic regime where the jet is produced in the target fragmentation hemisphere of the Breit frame, and with 𝑃 ⊥ ≪ 𝑄. For a longitudinally polarized photon, we demonstrate that this cross section is not power suppressed in 𝑃 ⊥ /𝑄 and we derive a factorized expression in terms of extended quark and gluon jet fracture functions. Our formula, valid at next-to-leading order in 𝛼 𝑠 at small 𝑥, is akin to the Altarelli-Martinelli identity for the longitudinal DIS structure function. Numerical estimates show that the extended quark jet fracture function is the most sensitive to saturation effects in large nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Tethering Effects in Oligomer-Based Metal–Organic Frameworks

Metal–organic frameworks (MOFs) can be con- structed using conventional molecular linkers or polymeric linkers (polyMOFs), but the relationship and relative properties of these related materials remain understudied. As an intermediate between these two extremes, a library of oligomeric ligand precursors (dimers, trimers) was used to prepare a series of oligomeric-linker MOFs (oligoMOFs) based on the prototypical IRMOF-1 system. IRMOF-1 was found to be remarkably tolerant to a wide variety of oligomeric linkers, the use of which greatly enhanced the MOF yield and prevented framework interpenetration. Tether length-dependent ordering of ligand and metal cluster orientations was also observed in these oligoMOFs. Improved low-humidity stability was found in oligoIRMOF-1 samples, with surface area preservation varying as a function of tether length and a complete suppression of crystalline hydrolysis products for all oligoIRMOF-1 materials. Furthermore, these findings pave the way toward a better understanding of the structure–function relationships between monomeric, oligomeric, and polymeric MOFs and highlight an underutilized strategy for tuning MOF properties.

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

Exact reaction coordinates for flap opening in HIV-1 protease

The primary goal of protein science is to understand how proteins function, which requires understanding the functional dynamics responsible for transitions between different functional structures of a protein. A central concept is the exact reaction coordinates that can determine the value of committor for any protein configuration, which provide the optimal description of functional dynamics. Despite intensive efforts, identifying the exact reaction coordinates (RCs) in complex molecules remains a formidable challenge. Using the recently developed generalized work functional, we report the discovery of the exact RCs for an important functional process—the flap opening of HIV-1 protease. Our results show that this process has six RCs, each one is a linear combination of ~240 backbone dihedrals, providing the precise definition of collectivity and cooperativity in the functional dynamics of a protein. Applying bias potentials along each RC can accelerate flap opening by 10 3 to 10 4 folds. The success in identifying the RCs of a protein with 198 residues represents a significant progress beyond that of the alanine dipeptide, currently the only other complex molecule for which the exact RCs for its conformational changes are known. Our results suggest that the generalized work functional (GWF) might be the fundamental operator of mechanics that controls protein dynamics.

Science & Technology - Other Topics↗
DOE OSTI2021

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure–function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Finally, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Surface Charge at an Oil/Water Interface Promoting the Enhancement and Assignment of Water Combination Bands

Given the different polarities and distinct chemical structures, it is no wonder that oil and water are incompatible neighbors. They can be forced to cooperate if provided sufficient energy or a suitable intermediary. Emulsions are the result of such a cooperation, where an emulsifying agent (the intermediary) in the form of a surfactant or a cocktail of surface stabilizing compounds allows for the ‘mixing’ of oil and water. Surfactant stabilized emulsions that are nanoscale in size (nanoemulsions) have caught the attention of many because of their newly discovered use in the synthesis of nanomaterials, oil recovery, drug delivery, and food science. Unlike smaller emulsions (e.g. microemulsions with 2-20 nm diameters), very little is known about the molecular level properties of nanoemulsions (NEs) whose diameters are in the 100-500 nm range. One thing that is well known is the macroscopic properties of droplets from these two size regimes are dramatically different, often for reasons not yet fully understood. Nanoemulsions do not form spontaneously and require an external shear beyond ordinary procedures used to create micelles. This shear is required to overcome the effects of surface tension and create droplets in the nanoscale regime. Once formed, however, they can be stable for long periods of time, making them very attractive for commercial and pharmaceutical products requiring a long shelf life. What is not well known is the interfacial molecular processes that lead to the formation and stability of nanoemulsions including those stabilized by surfactants and/or polymers. Such knowledge is important in understanding the molecular structure-function relationship that assists in predicting what additives and solvents are necessary for a specific application. Key to advancing nanoemulsion utility is to develop the needed molecular-level understanding of the structure and bonding interactions present at the surface of these soft nanoparticles.

36 MATERIALS SCIENCE↗