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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Small-angle neutron scattering solution structures of NADPH-dependent sulfite reductase

Sulfite reductase (SiR), a dodecameric complex of flavoprotein reductase subunits (SiRFP) and hemoprotein oxidase subunits (SiRHP), reduces sulfur for biomass incorporation. Electron transfer within SiR requires intra- and inter-subunit interactions that are mediated by the relative position of each protein, governed by flexible domain movements. Using small-angle neutron scattering, we report the first solution structures of SiR heterodimers containing a single copy of each subunit. These structures show how the subunits bind and how both subunit binding and oxidation state impact SiRFP’s conformation. Neutron contrast matching experiments on selectively deuterated heterodimers allow us to define the contribution of each subunit to the solution scattering. SiRHP binding induces a change in the position of SiRFP’s flavodoxin-like domain relative to its ferredoxin-NADP + reductase domain while compacting SiRHP’s N-terminus. Reduction of SiRFP leads to a more open structure relative to its oxidized state, re-positioning SiRFP’s N-terminal flavodoxin-like domain towards the SiRHP binding position. These structures show, for the first time, how both SiRHP binding to, and reduction of, SiRFP positions SiRFP for electron transfer between the subunits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Lattice expansion and ligand twist during CO2 adsorption in flexible Cu bipyridine metal–organic frameworks

Flexible metal–organic frameworks (MOFs) can show exceptional selectivity and capacity for adsorption of CO 2 . The incorporation of CO 2 into flexible MOFs that have Cu 2+ coordination centers and organic pillar ligands is accompanied by a distortion of the framework lattice arising from chemical interactions between these components and CO 2 molecules. CO 2 adsorption yields a reproducible lattice expansion that is enabled by the rotation of the pillar ligands. The structures of Cu 2 (pzdc) 2 (bpy) and Cu 2 (pzdc) 2 (bpe), CPL-2 and CPL-5, were evaluated using in situ synchrotron X-ray powder diffraction at room temperature at CO 2 gas pressures up to 50 atm. The structural parameters exhibit hysteresis between pressurization and depressurization. The pore volume within CPL-2 and CPL-5 increases at elevated CO 2 pressure due to a combination of the pillar ligand rotation and the overall expansion of the lattice. Volumetric CO 2 adsorption measurements up to 50 atm reveal adsorption behavior consistent with the structural results, including a rapid uptake of CO 2 at low pressure, saturation above 20 atm, and hysteresis evident as a retention of CO 2 during depressurization. Finally, a significantly greater CO 2 uptake is observed in CPL-5 in comparison with predictions based on CO 2 pressure-induced expansion of the pore volume available for adsorption, indicating that the flexibility of the CPL structures is a key factor in enhancing adsorption capacity.

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

Repairable and Reconfigurable Structured Liquid Circuits

The advance of printed electronics is significantly bolstered by the development of liquid-state electronics that overcome the inherent limitations in flexibility and reconfigurability of solid-state electronics. By integrating the biocompatibility and conductivity of sulfonated polyaniline (S-PANI) and phytic acid (PA) with the reconfigurability of structured liquids, highly conductive all-liquid threads are developed. The dense packing and overlap of PA/S-PANI complexes at an oil/water interface promotes in-plane electron transport, and standard four-point probe measurements of PA/S-PANI interfacial assemblies demonstrate enhanced electrical properties. Notably, the rapid jetting of the ink phase into the matrix phase allows for liquid threads to be printed, enabling the fabrication of large-scale, conductive pathways between two electrodes and liquid circuits. Upon mechanical cleavage of the liquid wires, circuits can be broken, but will easily self-repair using an electric field, making this motif useful in the design of switches as well as restoring conductive pathways in series or in parallel. In conclusion, the demonstrated flexibility and reconfigurability these PA/S-PANI wires possess hold significant promise for their practical use in the design of flexible and adaptive bioelectronics that can be repaired on demand, signifying a transformative step in the evolution of liquid electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A semi-agnostic ansatz with variable structure for variational quantum algorithms

Quantum machine learning—and specifically Variational Quantum Algorithms (VQAs)—offers a powerful, flexible paradigm for programming near-term quantum computers, with applications in chemistry, metrology, materials science, data science, and mathematics. Here, one trains an ansatz, in the form of a parameterized quantum circuit, to accomplish a task of interest. However, challenges have recently emerged suggesting that deep ansatzes are difficult to train, due to flat training landscapes caused by randomness or by hardware noise. This motivates our work, where we present a variable structure approach to build ansatzes for VQAs. Our approach, called VAns (Variable Ansatz), applies a set of rules to both grow and (crucially) remove quantum gates in an informed manner during the optimization. Consequently, VAns is ideally suited to mitigate trainability and noise-related issues by keeping the ansatz shallow. We employ VAns in the variational quantum eigensolver for condensed matter and quantum chemistry applications, in the quantum autoencoder for data compression and in unitary compilation problems showing successful results in all cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

How Accurate Can Crystal Structure Predictions Be for High-Energy Molecular Crystals?

Molecular crystals have shallow potential energy landscapes, with multiple local minima separated by very small differences in total energy. Predicting molecular packing and molecular conformation in the crystal generally requires ab initio methods of high accuracy, especially when polymorphs are involved. We used dispersion-corrected density functional theory (DFT-D) to assess the capabilities of an evolutionary algorithm (EA) for the crystal structure prediction (CSP) of well-known but challenging high-energy molecular crystals (HMX, RDX, CL-20, and FOX-7). While providing the EA with the experimental conformation of the molecule quickly re-discovers the experimental packing, it is more realistic to start instead from a naïve, flat, or neutral initial conformation, which reflects the limited experimental knowledge we generally have in the computational design of molecular crystals. By doing so, and using fully flexible molecules in fully variable unit cells, we show that the experimental structures can be predicted in fewer than 20 generations. Nonetheless, one must be aware that some molecular crystals have naturally hindered evolutions, requiring as many attempts as there are space groups of interest to predict their structures, and some may require the accuracy of all-electron calculations to discriminate between closely ranked structures. To save resources in this computationally demanding process, we showed that a hybrid xTB/DFT-D approach could be considered in a subsequent study to push the limits of CSP beyond 200+ atoms and for cocrystals.

42 ENGINEERING↗
DOE OSTI2020

Structures of FOX-4 Cephamycinase in Complex with Transition-State Analog Inhibitors

Boronic acid transition-state analog inhibitors (BATSIs) are partners with β-lactam antibiotics for the treatment of complex bacterial infections. Herein, microbiological, biochemical, and structural findings on four BATSIs with the FOX-4 cephamycinase, a class C β-lactamase that rapidly hydrolyzes cefoxitin, are revealed. FOX-4 is an extended-spectrum class C cephalosporinase that demonstrates conformational flexibility when complexed with certain ligands. Like other β-lactamases of this class, studies on FOX-4 reveal important insights into structure–activity relationships. We show that SM23, a BATSI, shows both remarkable flexibility and affinity, binding similarly to other β-lactamases, yet retaining an IC 50 value < 0.1 μM. Our analyses open up new opportunities for the design of novel transition-state analogs of class C enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework

Metal–organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly into the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni. First-principles molecular dynamics (FPMD) simulations offer the desired accuracy in modeling this flexibility but are limited by their extensive computational demands, rendering them impractical for long simulations. Conversely, classical force field-based simulations offer computational efficiency but lack the necessary accuracy. Here, to break this accuracy-efficiency trade-off, we have developed machine learning interatomic potentials trained on energies and forces from FPMD to model the framework flexibility of NbOFFIVE-1-Ni in the presence of water over nanosecond time scales. Furthermore, by integrating MLIP-driven molecular dynamics (MLIP-MD) with grand canonical Monte Carlo (GCMC) simulations, we further incorporated framework flexibility into adsorption predictions, yielding water adsorption isotherms that better align with experimental data compared to those of conventional GCMC simulations. These advances offer new opportunities for the design and optimization of MOFs in gas storage and separation applications.

adsorption↗
DOE OSTI2021

Hydrogen-Bonding Reinforced Flexible Composite Electrodes for Enhanced Energy Storage

The lack of advanced electrode materials is one of the main factors hindering the development of flexible rechargeable aqueous batteries (RABs) for high specific energy density and structural stability. It is also challenging to achieve high-capacity performance for both the positive and negative electrodes simultaneously. In this work, it is demonstrated that, by smartly designing the composite structures of positive and negative electrodes via one-step electrodeposition strategy, the energy storage performance of the RAB is largely enhanced. For positive electrode material synthesis, Co-Cu double hydroxides (Co-Cu-DH) nanosheets are skillfully rooted into electroreduced graphene oxide (eRG) via hydrogen bonding, in which graphene oxide reduction, Co-Cu-DH nucleation/growth, and formation of hydrogen bonding between Co-Cu-DH and eRG simultaneously occur. Moreover, when a RAB based on Co-Cu-DH@eRG//FeOOH@eRG using the same composite design strategy is established, a wide operating voltage window of ≈1.8 V, a high specific energy density of ≈142.8 Wh kg –1 at ≈890 W kg –1 , and long-term cyclic stability (88.5% of capacity retention after 12 000 cycles) are obtained. This study presents a general compositing strategy for the development of advanced electrode materials, and it is expected to stimulate future material synthesis/design in RABs toward the goal of high energy density storage.

25 ENERGY STORAGE↗
DOE OSTI2025

Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach

Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel meta-algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local space-time dependencies to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. For causal discovery, CaStLe flexibly accepts any appropriately adapted time series causal discovery algorithm to recover local causal structures. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. Regularities in local space-time dependencies are transformed into informative spatial replicates, which actually improve CaStLe's performance when applied to ever-larger spatial grids. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We provide validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of geophysics-inspired benchmarks while identifying the method's limitations and domains where its assumptions may not hold.

Nichol, J. Jake [Univ. of New Mexico, Albuquerque,↗
DOE OSTI2025

Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide

Understanding how local distortions determine the functional properties of high entropy materials, containing five or more elements at the same crystallographic site, is an open challenge. We address this for a compositionally complex spinel oxide (Mn 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )Cr 2 O 4 (A 5 Cr 2 O 4 ). By comparatively examining extended X-ray absorption fine structure on A 5 Cr 2 O 4 and its parent counterparts, ACr 2 O 4 , along with density functional theory calculations for multiple configurations, we find that the element-specific distortions go beyond the first neighbor. Specifically, the strong Jahn-Teller distortion present in CuCr 2 O 4 is found to be completely suppressed in A 5 Cr 2 O 4 even locally. Instead, there is a broad distribution of Cu-O and Cu-Cr bond distances, while other A-O distances acquire certain specific values. This study demonstrates the additional flexibility of a cationic sublattice in maintaining a uniform long-range structure, in contrast to previous reports showing only the accommodative anionic sublattice. The mean-field magnetic interactions of A 5 Cr 2 O 4 exhibit a striking resemblance to those of NiCr 2 O 4 , despite the presence of multiple magnetic ions and variable bond lengths. This originates from the comparability of bond lengths around Cr in both materials. Our study paves the way for a deeper understanding of the impact of local structural distortions on the physical properties of compositionally complex quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hierarchical domain structures in buckled ferroelectric free sheets

Flat elastic sheets tend to display wrinkles and folds. From pieces of clothing down to two-dimensional crystals, these corrugations appear in response to strain generated by sheet compression or stretching, thermal or mechanical mismatch with other elastic layers, or surface tension. Extensively studied in metals, polymers and, — more recently — in van der Waals exfoliated layers, with the advent of thin single crystal freestanding films of complex oxides, researchers are now paying attention to novel microstructural effects induced by bending ferroelectric-ferroelastics, where polarization is strongly coupled to lattice deformation. Here we show that wrinkle undulations in BaTiO3 sheets bonded to a viscoelastic substrate transform into a buckle delamination geometry when transferred onto a rigid substrate. Using spatially resolved techniques at different scales (Raman, scanning probe and electron microscopy), we show how these delaminations in the free BaTiO3 sheets display a self-organization of ferroelastic domains along the buckle profile that strongly differs from the more studied sinusoidal wrinkle geometry. Moreover, we disclose the hierarchical distribution of a secondary set of domains induced by the misalignment of these folding structures from the preferred in-plane crystallographic orientations. Our results disclose the relevance of the morphology and orientation of buckling instabilities in ferroelectric free sheets, for the stabilization of different domain structures, pointing to new routes for domain engineering of ferroelectrics in flexible oxide sheets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microcavity-Modified Emission from Rare-Earth Ion-Based Molecular Complexes

Despite the remarkable optical properties of rare-earth ion materials, their applications as light sources and in quantum technologies are often hindered by their long lifetimes and weak emission. Leveraging the natural compatibility of rare-earth ion molecular complexes with photonic structures, here we modify their photoluminescence properties by coupling them to a flexible open Fabry-Perot cavity. The full in situ tunability of the Fabry-Perot cavity allows fine control over its cavity modes and the achievement of resonant coupling between the rare-earth ion emission and the cavity modes. This configuration allows us to achieve a maximum photoluminescence enhancement factor of 30 and accelerate the decay rate up to two orders of magnitude. Our pump-power-dependent spectroscopic studies of the emitter-cavity system suggest that the cavity-modified emission is primarily caused by amplified spontaneous emission. These results suggest that integrating rare-earth ion molecular complexes with photonic structures could be a viable approach for the effective tuning of their optical properties. This natural compatibility, together with their versatile molecular structures and the resultant electronic states, renders rare-earth ion molecular complexes a potential alternative material platform for lighting and quantum applications.

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

Protein structural changes on a CubeSat under rocket acceleration profile

Catalyzing life-sustaining reactions, proteins are composed by 20 different amino acids that fold into a compact yet flexible three-dimensional architecture, which dictates what their function(s) might be. Determining the spatial arrangement of the atoms, the protein’s 3D structure, enables key advances in fundamental and applied research. Protein crystallization is a powerful technique to achieve this. Unlike Earth’s crystallization experiments, biomolecular crystallization in space in the absence of gravitational force is actively sought to improve crystal growth techniques. However, the effects of changing gravitational vectors on a protein solution reaching supersaturation remain largely unknown. Here, we have developed a low-cost crystallization cell within a CubeSat payload module to exploit the unique experimental conditions set aboard a sounding rocket. We designed a biaxial gimbal to house the crystallization experiments and take measurements on the protein solution in-flight with a spectrophotometry system. After flight, we used X-ray diffraction analysis to determine that flown protein has a structural rearrangement marked by loss of the protein’s water and sodium in a manner that differs from crystals grown on the ground. We finally show that our gimbal payload module design is a portable experimental setup to take laboratory research investigations into exploratory space flights.

42 ENGINEERING↗
DOE OSTI2024

Tuning Catalytically Active Single Sites in Nonstoichiometric, Mixed Metal Oxides for Oxygen Electrocatalysis (Final Technical Report)

The objective of the proposed work is to employ controlled synthesis, advanced characterization, detailed electrochemical testing and theoretical calculations to develop a framework that would guide the design of robust, non-stoichiometric mixed metal oxides for oxygen electrocatalysis. In this research plan, we focus around the idea of tuning the metal ion composition and environment to create single atom centers with the utmost electrocatalytic activity. We hypothesized that tuning the cationic sites in nonstoichiometric mixed metal oxides will lead to single 4d/5d metal surface sites with optimal catalytic activity for low temperature oxygen reduction (ORR) and oxygen evolution (OER) at solid/liquid interfaces. We will focus on different crystal structures of these oxides including Ruddlesden-Popper (R-P) oxides, simple perovskites and pyrochlores due to their flexibility in accommodating different metal cation dopants, and the fact that they represent variations in the cationic arrangements in non-stoichiometric mixed metal oxide structures, which will lead to an understanding of how bulk crystal structure effects catalytic activity and stability of these systems.

08 HYDROGEN↗
DOE OSTI2023

Advanced techniques in automated high-resolution scanning transmission electron microscopy

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. As a result, the system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

4D-STEM↗
DOE OSTI2023

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗
DOE OSTI2024

Charge‐Programmable Photopolymers for 3D Electronics via Additive Manufacturing

Charge‐programmed 3D printing enables the fabrication of 3D electronics with lightweight and high precision via selective patterning of metals. This selective metal deposition is catalyzed by Pd nanoparticles that are specifically immobilized onto the charged surface and promises to fabricate a myriad of complex electronic devices with self‐sensing, actuation, and structural elements assembled in a designed 3D layout. However, the achievable property space and the material‐performance correlation of the charge‐programmed printing remain unexplored. Herein, a series of photo‐curable resins are designed for unveiling how the charge and crosslink densities synergistically impact the nanocatalyst‐guided selective deposition in catalytic efficiency and properties of the 3D printed charge‐programmed architectures, leading to high‐quality 3D patterning of solid and liquid metals. The findings offer a wide tunability of the structural properties of the printed electronics, ranging from stiff to extreme flexibility. Capitalizing on these results, the printing and successful application of an ultralight‐weight and deployable 3D multi‐layer antenna system operating at an ultrahigh‐frequency of 19 GHz are demonstrated.

36 MATERIALS SCIENCE↗