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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Revealing a Pathway for Low-Temperature Recrystallization in Germanium

Thermally activated annealing in semiconductors faces inherent limitations, such as dopant diffusion. Here, a nonthermal pathway is demonstrated for a complete structural restoration in predamaged germanium via ionization-induced recovery. By combining experiments and modeling, this study reveals that the energy transfer of only 2.4 keV nm −1 from incident ions to target electrons can effectively annihilate pre-existing defects and restore the original crystalline structure at room temperature. Moreover, it is revealed that the irradiation-induced crystalline-to-amorphous (c/a) transformation in Ge is reversible, a phenomenon previously considered unattainable without additional thermal energy imposed during irradiation. For partially damaged Ge, the overall damage fraction decreases exponentially with increasing fluence. Surprisingly, the recovery process in preamorphized Ge starts with defect recovery outside the amorphous layer and a shrinkage of the amorphous thickness. After this initial stage, the remaining damage decreases slowly with increasing fluence, but full restoration of the pristine state is not achieved. These differences in recovery are interpreted in the framework of structural differences in the initial defective layers that affect recovery kinetics. This study provides new insights on reversing the c/a transformation in Ge using highly-ionizing irradiation and has broad implications across materials science, radiation damage mitigation, and fabrication of Ge-based devices.

athermal recovery↗
DOE OSTI2023

Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells

Abstract Simultaneously optimizing the processing parameters of functional thin films remains a challenge. The design and utilization of a fully automated platform called SPINBOT is presented for the engineering of solution‐processed functional thin films. The SPINBOT is capable of performing experiments with high sampling variability through the unsupervised processing of hundreds of substrates with exceptional experimental control. Through the iterative optimization process enabled by the Bayesian optimization (BO) algorithm, the SPINBOT explores an intricate parameter space, continuously improving the quality and reproducibility of the produced thin films. This machine learning (ML)‐guided reliable SPINBOT platform enables the acceleration of the optimization process of perovskite solar cells via a simple photoluminescence characterization of films. As a result, this study arrives at an optimal film that, when processed into a solar cell in an ambient atmosphere, immediately yields a champion power conversion efficiency (PCE) of 21.6% with satisfactory performance reproducibility. The unsealed devices retain 90% of their initial efficiency after 1100 h of continuous operation at 60–65 °C under metal‐halide lamps. It is anticipated that the integration of robotic platforms with the intelligent algorithm will facilitate the widespread adoption of effective autonomous experimentation to address the evolving needs and constraints within the materials science research community.

14 SOLAR ENERGY↗
DOE OSTI2022

Overcoming the Intrinsic Limitations of Fast Charging Lithium‐Ion Batteries Using Integrated Acoustic Streaming

A lithium‐ion battery's maximum charge rate and energy density are intrinsically limited by the ion diffusion rate in the electrolyte. Most research focuses on materials science solutions to this problem, with gradual improvement over the years. A mechanical solution is proposed to integrate an MHz‐order frequency surface acoustic wave (SAW) device into an existing 1.8 Ah multilayered Li‐ion pouch cell to enhance the ion diffusion rate and the overall battery performance. Both the charging rate and cycling lifetime are improved from SAW. At a 6C (10 min) charge and C/3 discharge rate, typical of electric vehicle applications, integrating SAW into the Li‐ion cell doubles the energy density and maintains at least 72% of the battery's initial capacity after 2000 cycles. Moreover, using SAW quantifiably reduces battery degradation in these conditions as determined by optical imaging, scanning electron microscopy, X‐ray diffraction, and neutron diffraction. The use of SAW appears to offer a method to avoid undesirable Li metal plating on the graphite anode during charging, and leads to a much longer battery lifetime and good charge capacity, all despite rapid charging.

Huang, An↗
DOE OSTI2025

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

σ-Aromaticity-Induced Stabilization of Heterometallic Supertetrahedral Clusters [Zn 6 Ge 16 ] 4– and [Cd 6 Ge 16 ] 4–

Here, the largest heterometallic supertetrahedral clusters, [Zn 6 Ge 16 ] 4– and [Cd 6 Ge 16 ] 4– , were directly self-assembled through highly-charged [Ge 4 ] 4– units and transition metal cations, in which 3-center–2-electron σ bonding in Ge 2 Zn or Ge 2 Cd triangles plays a vital role in the stabilization of the whole structure. The cluster structures have an open framework with a large central cavity of diameter 4.6 Å for Zn and 5.0 Å for Cd, respectively. Time-dependent HRESI-MS spectra show that the larger clusters grow from smaller components with a single [Ge 4 ] 4– and ZnMes 2 units. Calculations performed at the DFT level indicate a very large HOMO–LUMO energy gap in [M 6 Ge 16 ] 4– (2.22 eV), suggesting high kinetic stability that may offer opportunities in materials science. These observations offer a new strategy for the assembly of heterometallic clusters with high symmetry.

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

σ‐Aromaticity‐Induced Stabilization of Heterometallic Supertetrahedral Clusters [Zn 6 Ge 16 ] 4− and [Cd 6 Ge 16 ] 4−

Abstract In this work, the largest heterometallic supertetrahedral clusters, [Zn 6 Ge 16 ] 4− and [Cd 6 Ge 16 ] 4− , were directly self‐assembled through highly‐charged [Ge 4 ] 4− units and transition metal cations, in which 3‐center–2‐electron σ bonding in Ge 2 Zn or Ge 2 Cd triangles plays a vital role in the stabilization of the whole structure. The cluster structures have an open framework with a large central cavity of diameter 4.6 Å for Zn and 5.0 Å for Cd, respectively. Time‐dependent HRESI‐MS spectra show that the larger clusters grow from smaller components with a single [Ge 4 ] 4− and ZnMes 2 units. Calculations performed at the DFT level indicate a very large HOMO–LUMO energy gap in [M 6 Ge 16 ] 4− (2.22 eV), suggesting high kinetic stability that may offer opportunities in materials science. These observations offer a new strategy for the assembly of heterometallic clusters with high symmetry.

Xu, Hong‐Lei↗
DOE OSTI2020

Surfactant-Induced Interfacial Aggregation of Porphyrins for Structuring Color-Tunable Liquids

Locking nonequilibrium shapes of liquids into targeted architectures by interfacial jamming of nanoparticles is an emerging area in material science. 5,10,15,20-tetrakis(4-sulfonatophenyl) porphyrin (H 6 TPPS) shows three different aggregation states that present an absorption imaging platform to monitor the assembly and jamming of supramolecular polymer surfactants (SPSs) at the liquid/liquid interface. The interfacial interconversion of H 6 TPPS, specifically H 4 TPPS 2- dissolved in water, from J- to an H-aggregation was induced by strong electrostatic interactions with amine-terminated polystyrene dissolved in toluene at the water/toluene interface. We find that this resulted in color-tunable liquids due to interfacial jamming of the SPSs formed between H 4 TPPS 2- and amine-terminated polystyrene. However, the formed SPSs cannot lock in nonequilibrium shapes of liquids. In addition, a self-wrinkling behavior was observed when amphiphilic triblock copolymers of PS-block-poly(2-vinylpyridine)-block-poly(ethylene oxide) were used to interact with H 4 TPPS 2- . Subsequently, the SPSs formed can lock in nonequilibrium shapes of liquids.

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

Narrowing lab–to–market gaps: Device innovations in fuel generation, solar–cell, and photodetection

Academic translational research efforts to industry are often an underlying sought–after goal among various researchers. Through the interchanges of research endeavors between academia–industry, great innovations can/has been achieved that cater to the real–world application by bridging “industrially relevant” problem solving with pursuing fundamental studies. It is pertinent that most of the studies from university–level research works may not translate into demonstrable market products due to various reasons. Funding support, individual researcher goals, socioeconomic factors, and most importantly the technical know–how of generating revenue strategies for startups, are a few of the factors that have slowed the pace of collaborative efforts. However, we believe that the most crucial component is the identification of the critical parameters that solve long–standing problems that hinder the scale–up of the lab scale research into marketable products considering the techno–economic analysis. Here, to illustrate this, we take the three most relevant examples of devices for fuel generation, devices to utilize solar radiation, and devices for detection and other related applications. In this perspective, we provide an in–depth case study of each of these critical parameters to comment on the direction of research avenues that can serve as step–stones for the commercialization of university–level lab research studies.

42 ENGINEERING↗
DOE OSTI2024

Probing Noncovalent Interaction Strengths of Host-Guest Complexes Using Negative Ion Photoelectron Spectroscopy

Noncovalent interactions (NCIs) are crucial for the formation and stability of host-guest complexes, which have wide-ranging implications across various fields, including biology, chemistry, materials science, pharmaceuticals, and environmental science. However, since NCIs are relatively weak and sensitive to bulk perturbation, direct and accurate measurement of their absolute strength has always been a significant challenge. This concept article aims to demonstrate the gas-phase electrospray ionization (ESI)-negative ion photoelectron spectroscopy (NIPES) as a direct and precise technique to measure the absolute interaction strength, probe nature of NCIs, and reveal the electronic structural information for host-guest complexes. Here, our recent studies in investigating various host-guest complexes that involve various types of NCIs such as anion–π, (di)hydrogen bonding, charge-separated ionic interactions, are overviewed. Finally, a summary and outlook are provided for this field.

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

Chemical Recycling Processes of Waste Polyethylene Terephthalate Using Solid Catalysts

Polyethylene terephthalate (PET) is a non-degradable single-use plastic and a major component of plastic waste in landfills. Chemical recycling is one of the most widely adopted methods to transform post-consumer PET into PET's building block chemicals. Non-catalytic depolymerization of PET is very slow and requires high temperatures and/or pressures. Recent advancements in the field of material science and catalysis have delivered several innovative strategies to promote PET depolymerization under mild reaction conditions. Particularly, heterogeneous catalysts assisted depolymerization of post-consumer PET to monomers and other value-added chemicals is the most industrially compatible method. Here, this review includes current progresses on the heterogeneously catalyzed chemical recycling of PET. It describes four key pathways for PET depolymerization including, glycolysis, pyrolysis, alcoholysis, and reductive depolymerization. The catalyst function, active sites and structure-activity correlations are briefly outlined in each section. An outlook for future development is also presented.

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

A comparison of Gaussian processes and neural networks for computer model emulation and calibration

The Department of Energy relies on complex physics simulations for prediction in domains like cosmology, nuclear theory, and materials science. These simulations are often extremely computationally intensive, with some requiring days or weeks for a single simulation. In order to assure their accuracy, these models are calibrated against observational data in order to estimate inputs and systematic biases. Because of their great computational complexity, this process typically requires the construction of an emulator, a fast approximation to the simulation. In this paper, two emulator approaches are compared: Gaussian process regression and neural networks. Their emulation accuracy and calibration performance on three real problems of Department of Energy interest is considered. On these problems, the Gaussian process emulator tends to be more accurate with narrower, but still well-calibrated uncertainty estimates. The neural network emulator is accurate, but tends to have large uncertainty on its predictions. Finally, as a result, calibration with the Gaussian process emulator produces more constrained posteriors that still perform well in prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An Anthradithiophene Donor Polymer for Organic Solar Cells with a Good Balance between Efficiency and Synthetic Accessibility

Over the past few years, the organic photovoltaics technology (OPV) has reached remarkable power conversion efficiencies (PCEs), mostly thanks to the advent of nonfullerene acceptors as well as to a high level of materials engineering. Yet, the complex materials syntheses behind these results ultimately limit technological readiness. The quest for scalable organic compounds offering high PCE and reasonably low synthetic complexity is a must to close the gap between laboratory R&D and commercial products. The synthesis and full characterization of a new conjugated polymer called PATTD is reported herein, based on a novel anthradithiophene as an electron–rich building block coupled with a commercially available dithienylbenzodithiophenedione as an electron–withdrawing comonomer. Its photovoltaic properties are studied in blends with IT–4F and IDIC as acceptors. PATTD:IT–4F–based photovoltaic devices exhibit a PCE approaching 10% and over 2300 h shelf–life stability. Finally, the PATTD scalability factor (SF), together with the PATTD–based photovoltaic performances, lead to a PCE/SF value equal to 0.297, placing such devices into the innermost circle of OPV materials, achieving one of the best compromises between efficiency and synthetic complexity and at the same time offering promising industrial perspectives.

14 SOLAR ENERGY↗
DOE OSTI2021

Algorithm advances and applications of time‐dependent first‐principles simulations for ultrafast dynamics

Abstract Far from equilibrium phenomenon is a central theme of contemporary material research. Such phenomenon can exhibit itself in atomic structure and dynamics, but very often it also happens as non‐equilibrium phenomenon in the electronic structure. In ab initio material simulation, density functional theory (DFT) has played an essential role in studying electronic ground state problems. For excited states, besides many‐body perturbation theory, another powerful tool is the time dependent DFT (TDDFT) method. In particular, the real‐time TDDFT (rt‐TDDFT) method can be used to simulate many non‐equilibrium phenomena directly. Here we introduce our works on some algorithm advances based on our recently rt‐TDDFT method. This method uses the plane‐wave basis set, and significantly accelerates its efficiency by increasing the time step from 0.1–1 as in traditional methods to 0.2–0.5 fs. The noncollinear magnetic moments and spin–orbit coupling have also been included in our rt‐TDDFT method. Furthermore, a Boltzmann‐TDDFT algorithm has been developed to solve the hot carrier overheating problem in Ehrenfest dynamics, and a natural orbital branching algorithm has been developed to overcome the mean‐field approximation in Ehrenfest dynamics nuclear trajectory, thus allows stochastic multiple paths in chemical reactions. Utilizing these methods, we have studied the photoinduced ultrafast demagnetization, ultrafast phase transition, energy transfer between plasmon and hot carriers, as well as the high‐energy ion implantation and low‐energy atomic diffusion in semiconductors. We believe the tools as the ones introduced here can enable us to study a wide range of phenomena which are of great interest in modern day material research. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Density Functional Theory

Liu, Wen‐Hao↗
DOE OSTI2022

Chemical transformations and transport phenomena at interfaces

Abstract Interfaces, the boundary that separates two or more chemical compositions and/or phases of matter, alters basic chemical and physical properties including the thermodynamics of selectivity, transition states, and pathways of chemical reactions, nucleation events and phase growth, and kinetic barriers and mechanisms for mass transport and heat transport. While progress has been made in advancing more interface‐sensitive experimental approaches, their interpretation requires new theoretical methods and models that in turn can further elaborate on the microscopic physics that make interfacial chemistry so unique compared to the bulk phase. In this review, we describe some of the most recent theoretical efforts in modeling interfaces, and what has been learned about the transport and chemical transformations that occur at the air–liquid and solid–liquid interfaces. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Software > Quantum Chemistry Software > Simulation Methods

Hao, Hongxia↗
DOE OSTI2025

Advances and Challenges of SCAN and r 2 SCAN Density Functionals in Transition‐Metal Compounds

ABSTRACT Transition‐metal compounds (TMCs) with open‐shell d ‐electrons are characterized by a complex interplay of lattice, charge, orbital, and spin degrees of freedom, giving rise to various fascinating applications. Often exhibiting exotic properties, these compounds are commonly classified as correlated systems due to strong inter‐electronic interactions called Hubbard U . This inherent complexity presents significant challenges to Kohn‐Sham density functional theory (KS‐DFT), the most widely used electronic structure method in condensed matter physics and materials science. While KS‐DFT is, in principle, exact for the ground‐state total energy, its exchange‐correlation energy must be approximated in practice. The mean‐field nature of KS implementations, combined with the limitations of current exchange‐correlation density functional approximations, has led to the perception that DFT is inadequate for correlated systems, particularly TMCs. Consequently, a common workaround involves augmenting DFT with an on‐site Hubbard‐like U correction. In recent years, the strongly constrained and appropriately normed (SCAN) density functional, along with its refined variant r 2 SCAN, has achieved remarkable progress in accurately describing the structural, energetic, electronic, magnetic, and vibrational properties of TMCs, challenging the traditional perception of DFT's limitations. This review explores the design principles of SCAN and r 2 SCAN, highlights their key advancements in studying TMCs, explains the mechanisms driving these improvements, and addresses the remaining challenges in this evolving field.

Zhang, Yubo [Minjiang Collaborative Center for The↗
DOE OSTI2023

An asynchronous parallel high-throughput model calibration framework for crystal plasticity finite element constitutive models

Crystal plasticity finite element model (CPFEM) is a powerful numerical simulation in the integrated computational materials engineering toolboxes that relates microstructures to homogenized materials properties and establishes the structure–property linkages in computational materials science. However, to establish the predictive capability, one needs to calibrate the underlying constitutive model, verify the solution and validate the model prediction against experimental data. Bayesian optimization (BO) has stood out as a gradient-free efficient global optimization algorithm that is capable of calibrating constitutive models for CPFEM. Here in this paper, we apply a recently developed asynchronous parallel constrained BO algorithm to calibrate phenomenological constitutive models for stainless steel 304 L, Tantalum, and Cantor high-entropy alloy.

304L stainless steel↗
DOE OSTI2020

Effect of pH on the Activity of Ice-Binding Protein from Marinomonas primoryensis

The ability of an ice-binding protein (IBP) from Marinomonas primoryensis (MpIBP) to influence ice crystal growth and structure in nonphysiological pH environments was investigated in this work. The ability for MpIBP to retain ice interactivity under stressed environmental conditions was determined via (1) a modified splat assay to determine ice recrystallization inhibition (IRI) of polycrystalline ice and (2) nanoliter osmometry to evaluate the ability of MpIBP to dynamically shape the morphology of a single ice crystal. Circular dichroism (CD) was used to relate the IRI and DIS activity of MpIBP to secondary structure. The results illustrate that MpIBP secondary structure was stable between pH 6 and pH 10. It was found that MpIBP did not interact with ice at pH=4 or pH=13. At 6=pH=12 MpIBP exhibited a reduction in grain size of ice crystals as compared to control solutions and demonstrated dynamic ice shaping at 6=pH=10. The results substantiate that MpIBP retains some secondary structure and function in non-neutral pH environments; thereby, enabling its potential utility in nonphysiological materials science and engineering applications.

antifreeze proteins↗
DOE OSTI2025

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗