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Results for “Complex chemical systems”

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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation-guided analysis of resonant soft X-ray scattering for determining the microstructure of triblock copolymers

Resonant soft X-ray scattering (RSoXS) probes structure with chemical sensitivity that is useful for determining the morphology of multiblock copolymers. However, the hyperspectral scattering data produced by this technique can be challenging to interpret. Here, in this study, we use computational scattering simulations to extract the microstructure of a model triblock copolymer from the energy-dependent scattering from RSoXS. An ABC triblock terpolymer formed from poly(4-methylcaprolactone) (P4MCL), poly(2,2,2-trifluoroethylacrylate) (PTFEA), and poly (dodecylacrylate) (PDDA), P4MCL-block-PTFEA-block-PDDA, was synthesized as the model triblock system. Through quantitative evaluation of simulated scattering data from a physics-informed set of candidate structure models against experimental RSoXS data, we find the best agreement with hexagonally packed core–shell cylinders. This result is also consistent with electron-density reconstruction from hard X-ray scattering data evaluated against electron-density maps generated with the same model set. These results demonstrate the utility of simulation-guided scattering analysis to study complex microstructures that are challenging to image by microscopy.

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

Harnessing ionic complexity: A modeling approach for hierarchical ionic circuit design

Since the 1950s, soft ionic devices have evolved from individual components to an expanding library of sensors, actuators, signal transmitters, and processors. However, integrating these components into complex, multifunctional systems remains challenging due to the nonintuitive and nonlinear interactions between ionic elements. In this work, we address these fundamental challenges by developing a lumped element model that enables interrogation of the physics that governs ionic circuits, as well as rapid design and optimization. Our model captures features specific to ionic charge carriers, while preserving the hierarchical design flexibility and computational efficiency of traditional circuit modeling. We demonstrate that our model can not only fit individual device behavior but also accurately predict the behavior of larger circuits formed by combining those devices. Additionally, we show how our tool utilizes the intrinsic nonlinearities of ionic systems to enable extended functionality, revealing how factors such as ion enrichment, ion leakage, and polymer charge density influence performance. Lastly, we present a fully ionic power supply, sensor, control system, and actuator for a soft robot that adapts its motion in response to environmental salt, illustrating the tool’s potential to accelerate advancements in chemical sensing, biointerfacing, biomimetic systems, and adaptive materials.

42 ENGINEERING↗
DOE OSTI2021

System Modeling of the HTTR and Economic Dispatch Model of the Secondary System

High Temperature Gas-cooled Reactors (HTGRs) can be used for the generation of electricity and their process heat can be used to improve the efficiency of chemical processes such as hydrogen production. The JAEA-operated High-Temperature engineering Test Reactor (HTTR-GT/H2) is exploring using the reactor for electricity and hydrogen production. A RELAP5-3D model of the HTTR-GT/H2 secondary system has been developed using design information. The various components and heat exchangers in the secondary system were modeled and results were compared to the design conditions. The results for the sole-power generation mode were shown to fit the design conditions very well. The largest temperature difference was on the order of 7 K, and the largest pressure difference was on the order of 0.05 MPa. The results for the hydrogen cogeneration mode did not match the design conditions nearly as well. The largest temperature difference was about 39 K and the largest pressure difference was about 0.27 MPa at the compressor outlet. The larger differences for the hydrogen cogeneration mode are attributed to the various complex components and the flow being split in the secondary loop. A transient reduction in heat removal capability of the secondary system was investigated. Reactor temperatures are anticipated to rise as a result. The core reactivity response due to this increase in temperature is investigated and is expected to add negative reactivity to the reactor. An economic dispatch model was developed for a nuclear-driven iodine-sulfur cycle system to determine hydrogen sale prices that would make such a system profitable. The study focuses on the development of the economic model and the role that input data plays on final calculated values. It was found that the input electricity prices, whether using historical data or a host of synthetic time histories, produce significantly different breakeven hydrogen sale prices. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗
DOE OSTI2026

Single‐Step Recovery of Water from Stable Crude Oil‐Water Emulsion Using Surface Engineered Hybrid Inorganic‐Polymer Membranes

ABSTRACT Separating crude oil from water remains one of the most stubborn challenges in environmental remediation, especially for surfactant‐stabilized emulsions that resist conventional demulsification methods. Here, we report a scalable strategy for achieving near‐zero‐discharge separation of crude oil emulsions using a single superhydrophilic membrane. By applying low‐temperature atomic layer deposition (ALD) of various metal oxides onto activated polyvinylidene fluoride (PVDF) membranes, we create atomically precise surface‐engineered (SE) membranes that maintain an exceptionally strong hydration layer at the membrane‐feed interface, even at high oil loadings. Among the various metal oxides, TiO 2 ‐modified SE membranes exhibit superior interfacial water stability, enabling sustained dewatering of complex crude oil‐water emulsions with >98% separation efficiency and >97% water recovery, compared to only 24.6% water recovery for the pristine membrane. This separation performance surpasses conventional hydrophilic membranes and is comparable to complex Janus channel membrane systems, demonstrating near‐complete emulsion separation using a single membrane. This low‐temperature membrane surface engineering process with atomic‐level precision and potential for scalability via roll‐to‐roll fabrication is promising for industrial‐scale, energy‐efficient water treatment and oil spill remediation applications.

Sengupta, Bratin [Applied Materials Division Argon↗
DOE OSTI2020

Impact of wet-dry cycling on the phase behavior and compartmentalization properties of complex coacervates

Abstract Wet-dry cycling on the early Earth is thought to have facilitated production of molecular building blocks of life, but its impact on self-assembly and compartmentalization remains largely unexplored. Here, we investigate dehydration/rehydration of complex coacervates, which are membraneless compartments formed by phase separation of polyelectrolyte solutions. Solution compositions are identified for which tenfold water loss results in maintenance, disappearance, or appearance of coacervate droplets. Systems maintaining coacervates throughout the dehydration process are further evaluated to understand how their compartmentalization properties change with drying. Although added total RNA concentrations increase tenfold, RNA concentration within coacervates remains steady. Exterior RNA concentrations rise, and exchange rates for encapsulated versus free RNAs increase with dehydration. We explain these results in light of the phase diagram, with dehydration-driven ionic strength increase being particularly important in determining coacervate properties. This work shows that wet-dry cycling can alter the phase behavior and protocell-relevant functions of complex coacervates.

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

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Rapid Initial-State Preparation for the Quantum Simulation of Strongly Correlated Molecules

Studies on quantum algorithms for ground-state energy estimation often assume perfect ground-state preparation; however, in reality the initial state will have imperfect overlap with the true ground state. Here, we address that problem in two ways: by faster preparation of matrix-product-state (MPS) approximations and by more efficient filtering of the prepared state to find the ground-state energy. We show how to achieve unitary synthesis with a Toffoli complexity about 7 × lower than that in prior work and use that to derive a more efficient MPS-preparation method. For filtering, we present two different approaches: sampling and binary search. For both, we use the theory of window functions to avoid large phase errors and minimize the complexity. We find that the binary-search approach provides better scaling with the overlap at the cost of a larger constant factor, such that it will be preferred for overlaps less than about 0.003 . Finally, we estimate the total resources to perform ground-state energy estimation of Fe - S cluster systems, including the Fe Mo cofactor by estimating the overlap of different MPS initial states with potential ground states of the Fe Mo cofactor using an extrapolation procedure. With a modest MPS bond dimension of 4000 , our procedure produces an estimate of approximately 0.9 overlap squared with a candidate ground state of the Fe Mo cofactor, producing a total resource estimate of 7.3 × 10 10 Toffoli gates; neglecting the search over candidates and assuming the accuracy of the extrapolation, this validates prior estimates that have used perfect ground-state overlap. This presents an example of a practical path to prepare states of high overlap in a challenging-to-compute chemical system. Published by the American Physical Society 2025

Berry, Dominic W. (ORCID:0000000334461449)↗
DOE OSTI2021

Polarization Effects in Water-Mediated Selective Cation Transport across a Narrow Transmembrane Channel

We report despite the progress in modeling complex molecular systems of ever-increasing complexity, a quantitatively accurate computational treatment of ion permeation through narrow membrane channels remains challenging. An important factor to reach this goal is induced electronic polarization, which is likely to impact the permeation rate of small ions through narrow molecular pores. In this work, we extended the recently developed polarizable force field based on the classical Drude oscillators to assess the role of induced polarization effects on the energetics of sodium and potassium ion transport across the gramicidin A (gA) ion channel. The inclusion of induced polarization lowers barriers present in 1D potential of mean force (PMF) for cation permeation by ~50% compared to those obtained with the additive force field. Conductance properties calculated with 1D PMFs from Drude simulations are in better agreement with experimental results. Polarization of single-file water molecules and protein atoms forming the narrow pore has a direct impact on the free-energy barriers and cation-specific solid-state NMR chemical shifts. Sensitivity analysis indicates that small changes to water–channel interactions can alter the free energy barrier for ion permeation. These results, illustrating polarization effects present in the complex electrostatic environment of the gA channel, have broad implications for revising proposed mechanisms of ion permeation and selectivity in a variety of ion channels.

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

Embedded Sensors in Additively Manufactured Silicon Carbide

Silicon carbide (SiC) components are being considered for a wide range of nuclear applications due to their high-temperature strength retention, low neutron absorption, chemical inertness, and dimensional stability under neutron irradiation. However, machining and joining of SiC components have traditionally limited its application to relatively simple geometries. Recent work has demonstrated additive manufacturing of complex, high-purity, crystalline SiC components using a combination of binder jet printing and densification via chemical vapor infiltration (CVI). The process lends itself to embedding of fuel, absorbers, moderators, and sensors at strategic locations within a component. The latter could allow for enhanced in situ performance monitoring of limiting fuel temperatures, self-shielded neutron flux, and potentially spatially distributed strain within complex SiC components if sensors can be successfully embedded during CVI. This work describes (1) methods for embedding sensors; (2) thermodynamic analyses and material compatibility testing for identifying sensors capable of surviving high temperatures and exposure to hydrogen and hydrogen chloride during CVI; and (3) nuclear applications for embedded sensors, including potential failure modes during fabrication and during reactor operation. Molybdenum-sheathed thermocouples were successfully embedded in a complex SiC component, whereas niobium-sheathed high-temperature irradiation-resistant thermocouples started to drift as soon as the reactant gases were introduced and ultimately failed during CVI due to severe constrained expansion, potentially resulting from niobium hydride formation in the low-temperature region of the CVI system. Optical fibers were successfully embedded in SiC, but further work is needed to protect the fragile fiber leads after their protective coatings are removed during CVI.

thermocouples↗
DOE OSTI2025

Predicting Quantum Criticality in Single-Crystalline Ce 2 Ru 3 Ge 5

Strongly correlated f-electron systems are known to host exotic quantum states, such as quantum criticality, complex order parameters, and unconventional superconductivity. However, the appearance of these exotic states is difficult to predict, making the study of quantum critical behavior challenging, especially in ferromagnetic materials. Herein, we report a structure–property map for Ce 2 M 3 X 5 (M = transition metal; X = main group element) that aids in the targeted design of materials likely to exhibit quantum criticality. Guided by this map, we report on the synthesis of single-crystalline Ce 2 Ru 3 Ge 5 and provide, for the first time, magnetic susceptibility, heat capacity, resistivity, and magnetoresistance measurements on single crystals. Here, we observe a weak ferromagnetic-like response at 7.5 K, which is contrasted with the bulk ferromagnetic ordering that appears in polycrystalline samples. Non-Fermi liquid behavior is seen in the temperature dependent electrical resistivity and heat capacity of the single crystals, suggesting proximity to a ferromagnetic quantum critical point without chemical or physical pressure. Given the contrast with previous reports of polycrystals, these results lead us to propose that single crystalline Ce 2 Ru 3 Ge 5 is intrinsically tuned into the vicinity of a ferromagnetic quantum critical point.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pressure-Thresholded Response in Cylindrically Shocked Cyclotrimethylene Trinitramine (RDX)

We demonstrate a strongly thresholded response in cyclotrimethylene trinitramine (RDX) when it is cylindrically shocked using a novel waveguide geometry. Using ultrafast single-shot multi-frame imaging, we demonstrate that <100 μm diameter single crystals of RDX embedded in a polymer host deform along preferential planes for >100 ns after the shock first arrives in the crystal. We use in situ imaging and time-resolved photoemission to demonstrate that short-lived chemistry occurs with complex deformation pathways. Using scanning electron microscopy and ultra-small-angle X-ray scattering, we demonstrate that the shock-induced dynamics leave behind porous crystals, with pore shapes and sizes that change significantly with shock pressure. A threshold pressure of ~12 GPa at the center of convergence separated the single-mode planar crystal deformations from the chemistry-coupled multi-plane dynamics at higher pressures. Our observations indicate preferential directions for deformation in our cylindrically shocked system, despite the applied stress along many different crystallographic planes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

X-ray quantification of oxygen groups on diamond surfaces for quantum applications

Abstract Identifying the surface chemistry of diamond materials is increasingly important for device applications, especially quantum sensors. Oxygen-related termination species are widely used because they are naturally abundant, chemically stable, and compatible with stable nitrogen vacancy centres near the diamond surface. Diamond surfaces host a mixture of oxygen-related species, and the precise chemistry and relative coverage of different species can lead to dramatically different electronic properties, with direct consequences for near-surface quantum sensors. However, it is challenging to unambiguously identify the different groups or quantify the relative surface coverage. Here we show that a combination of x-ray absorption and photoelectron spectroscopies can be used to quantitatively identify the coverage of carbonyl functional groups on the { 100 } diamond surface. Using this method we reveal an unexpectedly high fraction of carbonyl groups ( > 9%) on a wide range of sample surfaces. Furthermore, through a combination of ab initio calculations and spectroscopic studies of engineered surfaces, we reveal unexpected complexities in the x-ray spectroscopy of oxygen terminated diamond surfaces. Of particular note, we find the binding energies of carbonyl-related groups on diamond differs significantly from other organic systems, likely resulting in previous misestimation of carbonyl fractions on diamond surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities

We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.

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

Functional lipid pairs as building blocks of phase-separated membranes

Biological membranes exhibit a great deal of compositional and phase heterogeneity due to hundreds of chemically distinct components. As a result, phase separation processes in cell membranes are extremely difficult to study, especially at the molecular level. It is currently believed that the lateral membrane heterogeneity and the formation of domains, or rafts, are driven by lipid–lipid and lipid–protein interactions. Nevertheless, the underlying mechanisms regulating membrane heterogeneity remain poorly understood. In the present work, we combine inelastic X-ray scattering with molecular dynamics simulations to provide direct evidence for the existence of strongly coupled transient lipid pairs. These lipid pairs manifest themselves experimentally through optical vibrational (a.k.a. phononic) modes observed in binary (1,2-dipalmitoyl- sn -glycero-3-phosphocholine [DPPC]–cholesterol) and ternary (DPPC–1,2-dioleoyl- sn -glycero-3-phosphocholine/1-palmitoyl-2-oleoyl-glycero-3-phosphocholine [DOPC/POPC]–cholesterol) systems. The existence of a phononic gap in these vibrational modes is a direct result of the finite size of patches formed by these lipid pairs. The observation of lipid pairs provides a spatial (subnanometer) and temporal (subnanosecond) window into the lipid–lipid interactions in complex mixtures of saturated/unsaturated lipids and cholesterol. Our findings represent a step toward understanding the lateral organization and dynamics of membrane domains using a well-validated probe with a high spatial and temporal resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

In situ coherent x-ray scattering reveals polycrystalline structure and discrete annealing events in strongly coupled nanocrystal superlattices

Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials of increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the self-assembly kinetics in these systems have been elucidated and related to the product characteristics, the weak interparticle bonding interactions suggest the superstructures formed could continue to order within the solution long after the primary nucleation and growth have occurred, even though the mechanism of annealing remains to be elucidated. Here, we use a combination of Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy to create real-space maps of supercrystalline order along with a real-time view of the strain fluctuations in aging strongly coupled nanocrystal superlattices while they remain suspended and immobilized in solution. By combining the results, we deduce that the self-assembled superstructures are polycrystalline, initially comprising multiple nucleation sites, and that shear avalanches at grain boundaries continue to increase crystallinity long after growth has substantially slowed. This multimodal approach should be generalizable to characterize a breadth of materials in their native chemical environments, thus extending the reach of high-resolution coherent x-ray characterization to the benefit of a much wider range of physical systems. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗