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Results for “Reusability”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Neural network representation of electronic structure from ab initio molecular dynamics

Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. Here we introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When it is applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born–Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving the way to previously inaccessible or challenging avenues in materials modeling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

GBOpt: Grain boundary structure optimization using Monte Carlo and evolutionary algorithms

Polycrystalline materials are made of many small crystals separated by grain boundaries (GBs), whose atomic structure strongly influences material properties. Because the structure of a GB determines its properties, the optimal structure must be known in order to determine those impacts. There are many ways of placing atoms in the GB region, but the optimal structure is defined as the one that gives the lowest value of a target property (typically energy). GB structure optimization has been successfully demonstrated using stochastic and evolutionary methods, but no reusable, community-maintained open-source workflow has been developed. GBOpt (Grain Boundary Optimization) is an open-source Python package that creates that workflow, where we have presently implemented two approaches: Markov Chain Monte Carlo, and genetic algorithm based on elite selection. We demonstrate this capability by successfully reproducing the known optimal structures of a specific GB in two materials, and point interested readers to the GitHub repository for additional examples, including optimization for different properties. Both of the implemented approaches recovered the known structures, with the genetic algorithm approach finding the optimal structure faster on average.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning

Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Role of Ammonium Hydroxide on Glucose Oxidase Immobilized in Metal–Azolate Framework-7 Enzyme Activity

Enzymes are nature’s catalysts, but their instability outside native environments limits practical applications. Metal–organic frameworks (MOFs) offer a promising platform for enzyme immobilization, enhancing stability, and reusability through their tunable porosity and crystallinity. While ZIF-based MOFs have been extensively studied, metal azolate framework-7 (MAF-7) remains largely unexplored for biomimetic mineralization. Its hydrophilic character makes it a promising alternative for enzyme encapsulation; however, the role of essential basic modulators such as ammonium hydroxide (NH 4 OH) on enzyme structure and function has not been investigated. Here, in this study, we examine the NH 4 OH mediated synthesis of glucose oxidase within MAF-7 using powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), cryogenic transmission electron microscopy (cryo-TEM), and enzyme assays. Our results show that NH 4 OH modulates crystal morphology, enzyme activity, and nucleation behavior, with higher concentrations leading to partial enzyme denaturation and reduced catalytic performance. By integrating time-resolved cryo-TEM with activity assays, we uncover how modulator concentration impacts early stage crystallization and enzyme folding, a mechanistic insight not previously demonstrated in MOF systems. These findings highlight modulator chemistry as a critical, underexplored variable in MOF synthesis, advancing rational design strategies for enzyme@MOFs (E@MOF) beyond ZIFs and toward more tunable, biocompatible frameworks like MAF-7.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Community Data Mining Approach for Surface Complexation Database Development

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. Here the framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Moisture-driven CO 2 direct air capture and delivery for cultivating cyanobacteria

This study demonstrates a low-energy system that passively captures CO₂ from ambient air using reusable solid sorbents and delivers it directly into alkaline cultivation media to support the growth of cyanobacteria, from laboratory flasks to outdoor raceway ponds. While long-term operation revealed challenges including biofouling and sorbent degradation, the results suggest that with improved sorbent durability, this approach could provide a scalable source of atmospheric carbon for producing sustainable fuels, proteins, natural colorants, and other bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2021

High-Performance Catalytic Four-Channel Hollow Fibers with Highly Dispersed Nickel Nanoparticles Prepared by Atomic Layer Deposition for Dry Reforming of Methane

In this study, highly dispersed nickel (Ni) nanoparticles (NPs) with an average particle size of 4.3 nm were uniformly deposited on the outer surface, the inner channel surface, and inside the pores of 20-cm long 4-channel α-Al 2 O 3 hollow fibers (HFs) by atomic layer deposition (ALD) for dry reforming of methane (DRM). Cerium oxide (CeO 2 ) was added to promote the catalytic performance of Ni/Al 2 O 3 -HF catalysts. Rationally designed filling methods, by tuning the reactor size and inert fillings, can reduce the catalyst bed voidage in a fixed bed reactor for better reactant gas distribution, effectively utilize the Ni reactive sites, and achieve excellent catalytic performance. It was found that the CeO 2 -promoted Ni/Al 2 O 3 -HF catalyst was highly active and highly stable without deactivation during an overall 400-hr DRM test at 850 ºC. CeO 2 with reversible valence states could participate in surface reactions; especially, the formation of CeAlO 3 provided sufficient surface Ce 3+ for CO 2 activation and enhanced the stability and reusability of the HF catalysts.

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

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Chemist: A Domain-Specific Language by Chemists for Chemists

Managing the complexity of quantum chemistry (QC) software is key to ensuring it remains accessible, maintainable, and reusable. Noticeably missing from the QC ecosystem are modules targeting bottleneck routines. Here we argue that this is likely due to the difficulty in defining interfaces for such modules. To that end, we introduce the open-source, publicly available Chemist library https://github.com/NWChemEx/Chemist. Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks. The usefulness of Chemist is demonstrated by discussing the interface of NWChemEx’s Fock build module and by showcasing a proof-of-concept self-consistent field algorithm containing uncertainty propagation.

Algorithms↗
DOE OSTI2024

Using Active Learning to Rapidly Develop Machine Learned Diffusion Coefficients of CO 2 Conversion Reagents in Metal–Organic Frameworks

Here, we used a combined molecular dynamics/active learning (AL) approach to create machine learning models that can predict the diffusion coefficient of epichlorohydrin and chloropropene carbonate, the reactant and product of a common CO 2 cycloaddition reaction, in metal–organic frameworks (MOFs). Nanoporous MOFs are effective catalysts for the cycloaddition of CO 2 to epoxides. The diffusion rates within nanoporous catalysts can control the rate of reaction as the reactants and products must diffuse to the active sites within the MOF and then out of the nanoporous material for reusability. However, the diffusion process is routinely ignored when searching for new materials in catalytic applications. Here we verified improvement during the AL process by consistently tracking metrics on the same groups of MOFs to ensure consistency. Metal identity was found to have little impact on diffusion rates, while structural features like pore limiting diameter act as a threshold where a minimum value is needed for high diffusion rates. We identified the MOFs with the highest epichlorohydrin and chloropropene carbonate diffusion coefficients which can be used for further studies of reaction energetics.

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

Open-Source and FAIR Research Software for Proteomics

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Mesoporous Crystalline Niobium Oxide with a High Surface Area: A Solid Acid Catalyst for Alkyne Hydration

A mesoporous crystalline niobium oxide with tunable pore sizes was synthesized via the sol–gel-based inverse micelle method. The material shows a surface area of 127 m 2 /g, which is the highest surface area reported so far for crystalline niobium oxide synthesized by soft template methods. The material also has a monomodal pore size distribution with an average pore diameter of 5.6 nm. A comprehensive characterization of niobium oxide was performed using powder X-ray diffraction, Brunauer–Emmett–Teller, thermogravimetric analysis, scanning electron microscopy, transmission electron microscopy, UV–vis, and X-ray photoelectron spectroscopy. The material acts as an environmentally friendly, solid acid catalyst toward hydration of alkynes under with excellent catalytic activity (99% conversion, 99% selectivity, and 4.39 h –1 TOF). Brønsted acid sites present in the catalyst were found to be responsible for the high catalytic activity. Lastly, the catalyst was reusable up to five cycles without a significant loss of the activity.

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

Polymer Layer-Accelerated CO 2 Absorption in Aqueous Amino Acid Solutions

Direct air capture (DAC) of CO 2 via solvent-based absorption is considered a promising negative-emission technology. However, the low concentration of CO 2 in the air and slow transport into the solvent make DAC notoriously challenging to implement without costly investments. In this study, we explore the fundamental role that the bulk and surface properties of CO 2 -permeable polymer membranes play in enhancing the efficiency of the solution sorption process in passive DAC of CO 2 . This work leverages various spectroscopic and computational studies to demonstrate that a hybrid system, comprising a reusable CO 2 -permeable polymer layer placed atop an aqueous amino acid (AA) solution, can outperform a pure aqueous AA system by 2-fold. Here we show how the enhanced solubility of CO 2 in the polymer layer can improve the transport of CO 2 into the aqueous phase, while the chemistry of the polymer can control the interfacial barrier for CO 2 permeation and the interfacial concentration of reactive AAs. The derived knowledge of the material properties achieved here can aid in the design of DAC systems with improved performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

3D-Bioprinted Marine Bacteria for the Degradation of Polyhydroxybutyrate Bioplastics

The severe, long-lasting harm caused by plastic pollution to marine ecosystems and coastal economies has led to the development of biodegradable plastics; however, their limited decomposition in marine environments remains a challenge. Here, technologies are presented for creating 3D-bioprinted living materials as a proof of concept for bioplastic degradation, with specific use in marine environments. The approach developed here integrates the halotolerant bioplastic-degrading bacterium Bacillus sp. NRRL B- 14911 into alginate-based bio-ink to print an engineered living material (ELM) termed a “bio-sticker.” Quantification of bacteria viability reveals that bioprinted marine bacteria survive within biostickers for more than 3 weeks. The rate at which the biostickers degrade the bioplastic polyhydroxybutyrate (PHB) can be tuned by altering biosticker biomass concentration, bioplastic concentration, or incubation temperature. Biostickers that are transferred to a different PHB sample still retain high biodegradation activity, demonstrating their reusability. Strain sweep oscillatory tests demonstrate that the biostickers display predominantly viscoelastic behavior. Monotonic tensile tests indicate that the elastic modulus and the adhesion of the biostickers are not negatively impacted by bacteria growth or incubation temperature. This work paves the way for the development of ELMs to facilitate the inclusion of bioplastics within the blue economy, promoting the emergence of more sustainable and ecofriendly materials.

3D bioprinting↗
DOE OSTI2021

Exploring the Structure and Performance of Cd–Chalcogenide Photocatalysts in Selective Trifluoromethylation

The field of heterogeneous photoredox catalysis has grown substantially and impacted organic synthesis because of the affordability and reusability of catalysts. This study reports radical trifluoromethylation with Cd–chalcogenide semiconductors. Cd semiconductors, particularly CdSe, are readily available, commercial, visible-light-responsive, heterogeneous photocatalysts. The potential of readily available Cd semiconductors, particularly CdSe, is confirmed by their increased photocatalytic activity toward trifluoromethylation with various substrates, such as (hetero)arenes and vinylic amides/acids, via addition, cyclization, and decarboxylation under visible light. Additionally, the economic significance of this strategy is also highlighted through the scalable synthesis of biologically active molecules followed by catalyst reuse. Moreover, these catalysts are relatively inexpensive compared with transition metal-based homogeneous photocatalysts, presently used in organic synthesis.

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

Pick-and-Place Transfer of Arbitrary-Metal Electrodes for van der Waals Device Fabrication

Van der Waals electrode integration is a promising strategy to create nearly perfect interfaces between metals and 2D materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique. Here, we demonstrate the pick-and-place transfer of prefabricated electrodes from reusable polished hydrogenated diamond substrates without the use of any sacrificial layers due to the inherent low-energy and dangling-bond-free nature of the hydrogenated diamond surface. The technique enables transfer of arbitrary-metal electrodes and an electrode array, as demonstrated by successful transfer of eight different elemental metals with work functions ranging from 4.22 to 5.65 eV. We also demonstrate the electrode array transfer for large-scale device fabrication. The mechanical transfer of metal electrodes from diamond to van der Waals materials creates atomically smooth interfaces with no interstitial impurities or disorder, as observed with cross-section high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. As a demonstration of its device application, we use the diamond transfer technique to create metal contacts to monolayer transition metal dichalcogenide semiconductors with high-work-function Pd, low-work-function Ti, and semimetal Bi to create n- and p-type field-effect transistors with low Schottky barrier heights. We also extend this technology to air-sensitive materials (trilayer 1T’ WTe 2 ) and other applications such as ambipolar transistors, Schottky diodes, and optoelectronics. This highly reliable and reproducible technology paves the way for new device architectures and high-performance devices.

2D materials↗
DOE OSTI2026

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗