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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ultrafast Electron Transfer in Au-Cyanobacteria Hybrid for Solar to Chemical Production

The rise of inorganic-biohybrid organisms for solar-to-chemical production has spurred mechanistic investigations into the dynamics of the biotic-abiotic interface to drive the development of next-generation hybrid systems. The model system, cyanobacteria-gold nanoparticle hybrids, combines a light harvester with a photosynthetic bacterium to drive the reduction of CO2 to glycerol with improved efficiency and increased glycerol production by 14.6%, in comparison to cyanobacteria only. In this work, we report insights into this unique photochemical behavior and propose a charge-transfer pathway from Au nanoparticle to cyanobacteria. Transient absorption (TA) spectroscopy revealed that photoexcited electron transfer rates are on the order of a few ps to the potential electron acceptor in photosystem II. This work represents a promising platform to utilize a conventional spectroscopic methodology to extract insights from more complex biotic-abiotic hybrid systems.

charge transfer↗
DOE OSTI2023

Role of Surface Features on the Initial Dissolution of CH 3 NH 3 PbI 3 Perovskite in Liquid Water: An Ab Initio Molecular Dynamics Study

In this study, the degradation of CH 3 NH 3 PbI 3 (MAPbI 3 ) hybrid organic inorganic perovskite (HOIP) by water has been the major issue hampering its use in commercial perovskites solar cells (PSCs) as MAPbI 3 HOIP have been known to easily degrade in the presence of water molecules. However, even though there have been numerous studies investigating this phenomenon, there is still no consensus on the mechanisms of initial stages of dissolution. Here, we attempt to consolidate differing mechanistic interpretations previously reported in the literature through the use of the first-principles constrained ab-initio molecular dynamics (AIMD) to study the mechanisms, kinetics, and thermodynamics that accompany the degradation of MAPbI 3 HOIP in liquid water. We consider not only the dissolution of the species found on the pristine MAPbI 3 HOIP surfaces, but also the dissolution from defect sites to imitate the successive degradation steps, and propose a sequence of events in the initial phase of MAPbI 3 HOIP dissolution. By comparing the dissolution free energy barrier between surface species of different surficial types, we find that the dominant dissolution mechanisms of surface species varies widely based on the specific surface features adjacent to the dissolving ion. The high sensitivity of dissolution mechanism to surface features has contributed to the many dissolution mechanisms proposed in the literature. In contrast, the dissolution free energy barriers are mainly determined by the dissolving species rather than the type of surfaces, and the type of surfaces the ions are dissolving from are inconsequential toward the dissolution free energy barrier. However, the presence of surface defects such as vacancy sites are found to significantly lower the dissolution free energy barriers. Based on the estimated dissolution free energy barriers from different types of surfaces that we investigated in this study, we proposed that the dissolution of MAPbI 3 HOIP in liquid water originates from surface defect sites that propagate laterally along the surface layer of the MAPbI 3 HOIP crystal.

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

Revealing the Dynamics and Roles of Iron Incorporation in Nickel Hydroxide Water Oxidation Catalysts

We report the surface of an electrocatalyst undergoes dynamic chemical and structural transformations under electro-chemical operating conditions. There is a dynamic exchange of metal cations between the electrocatalyst and electrolyte. Understanding how iron in the electrolyte gets incorporated in the nickel hydroxide electrocatalyst is critical for pinpointing the roles of Fe during water oxidation. Here, we report that iron incorporation and oxygen evolution reaction (OER) are highly coupled, especially at high working potentials. The iron incorporation rate is much higher at OER potentials than that at the OER dormant state (low potentials). At OER potentials, iron incorporation favors electrochemically more reactive edge sites, as visualized by synchrotron X-ray fluorescence microscopy. Using X-ray absorption spectroscopy and density functional theory calculations, we show that Fe incorporation can suppress the oxidation of Ni and enhance the Ni reducibility, leading to improved OER catalytic activity. Our findings provide a holistic approach to understanding and tailoring Fe incorporation dynamics across the electrocatalyst-electrolyte interface, thus controlling catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Aquatic Carbon-Nutrient Dynamics as Emergent Properties of Hydrological, Biogeochemical, and Ecological Interactions: Scientific Advances

Carbon and nutrient dynamics in aquatic systems often emerge as the result of hydrological, biogeochemical, and ecological interactions. Due to the multiscale and multidisciplinary nature of these process interactions, research into aquatic carbon and nutrient dynamics is becoming increasingly interdisciplinary. The motivation for this special issue came from an international workshop titled "Hydro-Biogeochemical Processes: Mechanisms, Coupling, and Impact, " which took place from 27 to 31 October 2015 at China University of Geosciences, Wuhan, China. During this workshop, scientists from various countries and disciplines met to discuss current work and future advances on topics such as the hydro-biogeochemistry of Earth's critical zone, stream-groundwater interaction zones, aquatic ecosystem processes, and dynamics at land-atmosphere, land-ocean, and human-natural interfaces. Contributions to this special issue on "Emergent aquatic carbon-nutrient dynamics as products of hydrological, biogeochemical, and ecological interactions" include papers from authors who attended the workshop and from those who responded to the open solicitation for papers. Finally, our aim in organizing this special issue is to stimulate continued discussion and collaboration across disciplinary boundaries in order to further our collective understanding of aquatic carbon-nutrient dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Phase separation during bulk polymerization of methyl methacrylate

We report on the phase separation of methyl methacrylate (MMA) and poly(methyl methacrylate) (PMMA) during bulk free-radical polymerization. The phase separation is induced when the reaction is initiated at room temperature by the redox reaction of benzoyl peroxide in the presence of an amine. During the reaction, the ratio of MMA and PMMA changes continuously. Separation into MMA-rich and PMMA-rich phases coincides with the onset of the Trommsdorff effect. At room temperature, the interface between the two phases remains, even after drying the remaining monomer. When the sample is annealed above the glass transition temperature Tg, the interface disappears. Due to the frozen dynamics of the polymer chains, subsequent cooling below Tg does not result in further phase separation. This result provides evidence for the existence of rich, thermodynamically stable states, which are typically suppressed due to the frozen dynamics of polymers at temperatures below the Tg, after thermal processing above the Tg.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Facile hermetic TEM grid preparation for molecular imaging of hydrated biological samples at room temperature

Abstract Although structures of vitrified supramolecular complexes have been determined at near-atomic resolution, elucidating in situ molecular structure in living cells remains a challenge. Here, we report a straightforward liquid cell technique, originally developed for real-time visualization of dynamics at a liquid-gas interface using transmission electron microscopy, to image wet biological samples. Due to the scattering effects from the liquid phase, the micrographs display an amplitude contrast comparable to that observed in negatively stained samples. We succeed in resolving subunits within the protein complex GroEL imaged in a buffer solution at room temperature. Additionally, we capture various stages of virus cell entry, a process for which only sparse structural data exists due to their transient nature. To scrutinize the morphological details further, we used individual particle electron tomography for 3D reconstruction of each virus. These findings showcase this approach potential as an efficient, cost-effective complement to other microscopy technique in addressing biological questions at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗
DOE OSTI2021

Effects of interlayer confinement and hydration on capacitive charge storage in birnessite

Nanostructured birnessite exhibits high specific capacitance and nearly ideal capacitive behaviour in aqueous electrolytes, rendering it an important electrode material for low-cost, high-power energy storage devices. The mechanism of electrochemical capacitance in birnessite has been described as both Faradaic (involving redox) and non-Faradaic (involving only electrostatic interactions). To clarify the capacitive mechanism, we characterized birnessite’s response to applied potential using ex situ X-ray diffraction, electrochemical quartz crystal microbalance, in situ Raman spectroscopy and operando atomic force microscope dilatometry to provide a holistic understanding of its structural, gravimetric and mechanical responses. These observations are supported by atomic-scale simulations using density functional theory for the cation-intercalated structure of birnessite, ReaxFF reactive force field-based molecular dynamics and ReaxFF-based grand canonical Monte Carlo simulations on the dynamics at the birnessite–water–electrolyte interface. We show that capacitive charge storage in birnessite is governed by interlayer cation intercalation. We conclude that the intercalation appears capacitive due to the presence of nanoconfined interlayer structural water, which mediates the interaction between the intercalated cation and the birnessite host and leads to minimal structural changes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hot-Carrier Transfer at Photocatalytic Silicon/Platinum Interfaces

Interfacial charge transfer from silicon to heterogeneous catalysts plays a key role in silicon-based photoelectrochemical systems. In general, prior to interfacial charge transfer, carriers that are generated by photons with energies above the bandgap dissipate the excess kinetic energy via hot-carrier cooling, and such energy loss limits the maximum power conversion efficiency. The excess energy of hot-carriers, however, could be utilized through hot-carrier transfer from silicon to the catalysts, but such hot-carrier extraction has not yet been demonstrated. In this work, we exploit transient reflection spectroscopy to interrogate charge transfer at the interface between silicon and platinum. Additionally, quantitative modeling of the surface carrier kinetics indicates that the velocity of charge transfer from silicon to platinum exceeds 2.6 x 10 7 cm s -1 , corresponding to an average carrier temperature of extracted carriers of ~600 K, two times higher than the lattice temperature. The charge transfer velocity can be controllably reduced by inserting silica spacing layers between silicon and platinum.

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

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
DOE OSTI2024

Electronic conductivity in metal-graphene composites: the role of disordered carbon structures, defects, and impurities

Abstract This paper explores the transport properties of aluminum-carbon composite material via ab initio methods. Interfacial and electronic dynamics of the aluminum-graphene interface structure were investigated using models of amorphous graphene added to an aluminum matrix. We examine the impact on electronic conduction caused by the presence of nitrogen impurities within the interfacial amorphous graphene layer. We elucidate the conduction mechanisms by using a projection of the electronic conductivity into space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructural Pattern Formation during Far-from-Equilibrium Alloy Solidification

We introduce a new phase-field formulation of rapid alloy solidification that quantitatively in- corporates non-equilibrium effects at the solid-liquid interface over a very wide range of interface velocities. Simulations identify a new dynamical instability of dendrite tip growth driven by solute trapping at velocities approaching the absolute stability limit. They also reproduce the formation of the widely observed banded microstructures, revealing how this instability triggers transitions between dendritic and microsegregation-free solidification. Predicted band spacings agree quantita- tively with observations in rapidly solidified Al-Cu thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2020

FICH: Feature instability cavitation history [Slides]

We seek to improve our ability to predict and understand the Richtmyer-Meshkov (RM) unstable dynamics of explosively shocked isolated features interfaced with vacuum or gases, and an HE products cavity. Explosively shocked features form as 2D or 3D RM phenomena. Liquid cavitation cause cavitation bubbles when shockwaves collide, and cavitation waves from wave interactions with isolated features form that source mass into the RM unstable sheets or spikes, and the cavitation waves may slice through bulk material into the HE products cavity.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

MST-8 Colloquium: The Effect of Microstructure on the Spall Strength and Damage of 1045 Steel [Slides]

Three different microstructures of the same steel alloy were investigated to study the influence of microstructure on spall strength and damage. Microstructure influences spall behavior within the explored dynamic regime. Second phase morphology, interphase interface characteristics, and grain boundary character shown to influence spall behavior. Continued understanding of microstructure’s influence on spall and damage needed for targeted material design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Keeping LAMMPS cutting edge

Since its inception 30 years ago, LAMMPS has grown to be a world-class molecular dynamics code and a cornerstone of computational materials science research. This project aimed to keep LAMMPS at the forefront of molecular dynamics simulations by adapting LAMMPS to the latest developments in machine learning technology and hardware. Initially, the project set out to provide a unified implementation of active learning for efficient training data generation in LAMMPS, but the research trajectory pivoted to address more immediate and impactful opportunities. On the hardware side, recent record-breaking molecular dynamics simulations were developed on the Cerebras wafer-scale AI chip, and this project has developed an interface between LAMMPS and the hardware-specific molecular dynamics code to accelerate and simplify development and user adoption. On the software side, PyTorch’s Ahead-of-Time (AOT) compilation features promised increased performance for state-of-the-art equivariant neural network potentials, and this project laid the groundwork for their adoption in LAMMPS, resulting in a nearly 20x acceleration in extreme cases. Combined with a comprehensive benchmark study of LAMMPS across all current exascale systems, this project has reinforced LAMMPS’s role as a versatile, high-performance tool for current and future materials science applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning Enabled Advanced Electron Tomography for Resolving Chemical Inhomogeneity and Materials Dynamics in Lithium-Ion Battery Electrodes

The objective of this project is to develop machine learning-assisted electron microscopy, together with three-dimensional, cryogenic, and in-situ imaging techniques, for resolving chemical inhomogeneity and materials dynamics in lithium battery electrodes and interfaces. The project aims to expand the spatial, temporal, and dimensional resolution of transmission electron microscopy and to enable quantitative analysis of beam-sensitive battery materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Toward understanding the dimensional crossover of canonical spin-glass thin films

Spin-glass thin films exhibit many features different from the bulk. The freezing temperatures of spin-glass films are suppressed for reduced thickness and follow the Kenning relation. The dynamics are altered near the vacuum interface. These phenomena are closely related to the lower critical dimension of spin glasses, the spin-glass correlation length, and the dimensional crossover from d = 3 to d = 2. In this article, we review the experimental facts and theoretical perspectives for spin-glass thin films. We focus on canonical spin-glass systems with the Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction between magnetic impurities in a nonmagnetic host. Open questions to be addressed are emphasized.

interfacial effects↗