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At least 271 records · Page 15

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DOE OSTI2019

Data-driven high-fidelity 2D microstructure reconstruction via non-local patch-based image inpainting

Microstructure reconstruction problems are usually limited to the representation with finitely many number of phases, e.g. binary and ternary. However, images of microstructure obtained through experimental, for example, using microscope, are often represented as a RGB or grayscale image. Because the phase-based representation is discrete, more rigid, and provides less flexibility in modeling the microstructure, as compared to RGB or grayscale image, there is a loss of information in the conversion. In this paper, a microstructure reconstruction method, which produces images at the fidelity of experimental microscopy, i.e. RGB or grayscale image, is proposed without introducing any physics-based microstructure descriptor. Furthermore, the image texture is preserved and the microstructure image is represented with continuous variables (as in RGB or grayscale images), instead of binary or categorical variables, which results in a high-fidelity image of microstructure reconstruction. The advantage of the proposed method is its quality of reconstruction, which can be applied to any other binary or multiphase 2D microstructure. The proposed method can be thought of as a subsampling approach to expand the microstructure dataset, while preserving its image texture. Moreover, the size of the reconstructed image is more flexible, compared to other machine learning microstructure reconstruction method, where the size must be fixed beforehand. In addition, the proposed method is capable of joining the microstructure images taken at different locations to reconstruct a larger microstructure image. A significant advantage of the proposed method is to remedy the data scarcity problem in materials science, where experimental data is scare and hard to obtain. The proposed method can also be applied to generate statistically equivalent microstructures, which has a strong implication in microstructure-related uncertainty quantification applications. The proposed microstructure reconstruction method is demonstrated with the UltraHigh Carbon Steel micrograph DataBase (UHCSDB).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Generative large language models for predictive maintenance planning

Maintenance planning and the generation of necessary components for tasks can prove time-consuming and complex. Automating the creation of recurring or similar tasks by leveraging previous planning packages and data, while uncovering insights to automate planning package generation, presents an opportunity to conserve valuable time and resources. This work aims to harness the textual and probabilistic capabilities of large language models (LLMs) to automate the generation of planning packages. Utilizing diverse data sources ranging from raw data to handwritten text, both singular and collaborative LLMs are trained and tested. Results demonstrate their capability to generate essential planning package components, effectively replicating the statistical patterns in the data. This demonstrates the use of these tools inside a digital asset for automated planning. This work outlines a methodology for constructing datasets, a training suite, and evaluation methods for LLM-based textual and conversational planning tools utilized in an asset digital twin. Results indicate that the fine-tuned models generate estimated planning information within the statistical ranges observed in real maintenance data. The models achieve high accuracy (>90%) in document question-answering and instruction generation tasks. Furthermore, the conversational retrieval-augmented generation (RAG) assistant system achieves 100% document retrieval accuracy, while conversational information capture exceeds 98% across the majority of work-package assistant modules.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

A reformation in energy is underway to replace fossil fuels with renewable sources, driven by the development of new, robust, and multi-functional materials. High-entropy materials (HEMs) have emerged as promising candidates for various green energy applications, having unusual chemistries that give rise to remarkable functionalities. This review examines recent innovations in HEMs, focusing on hydrogen generation/storage, fuel cells, batteries, semiconductors/electronics, and catalysis—where HEMs have demonstrated the ability to outperform state-of-the-art materials. We present new master plots that illustrate the superior performance of HEMs compared to conventional systems for hydrogen generation/storage and heat-to-electricity conversion. We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. The review also presents current challenges and proposes future directions for the field. We emphasize the need for continued integration of modeling, data, and experiments to investigate and leverage the underlying mechanisms of the HEMs that are powering progress in sustainable energy.

batteries↗

DOE OSTI2023

Lignin with controlled structural properties by N-heterocycle-based deep eutectic solvent extraction

The complex and heterogeneous nature of the lignin macromolecule has presented a lasting barrier to its utilization. To achieve high lignin yield, the technical lignin extraction process usually severely modifies and condenses the native structure of lignin, which is a critical drawback for its utilization in conversion processes. In addition, there is no method capable of separating lignin from plant biomass with controlled structural properties. Here, we developed an N-heterocycle-based deep eutectic solvent formed between lactic acid and pyrazole (La–Py DES) with a binary hydrogen bonding functionality resulting in a high affinity toward lignin. In this study, up to 93.7% of lignin was extracted from wheat straw biomass at varying conditions from 90 °C to 145 °C. Through careful selection of treatment conditions as well as lactic acid to pyrazole ratios, lignin with controlled levels of ether linkage content, hydroxyl group content, and average molecular weight can be generated. Under mild extraction conditions (90 °C to 120 °C), light-colored native-like lignin can be produced with up to 80% yield, whereas ether linkage–free lignin with low polydispersity can be obtained at 145 °C. Overall, this study offers a new strategy for native lignin extraction and generating lignin with controlled structural properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Data for "Integrated Green Biorefinery for the Production of Anthocyanins, Fermentable Sugars, and High Pure Lignin from Miscanthus × giganteus "

Miscanthus x giganteus (Mxg) is a promising perennial crop for producing natural colorants, renewable fuels, and bioproducts. However, natural recalcitrance and high pretreatment cost are major barriers to their complete conversion. In this study, a green processing method has been investigated for efficient recovery of natural pigments (anthocyanins), fermentable sugars, and pure lignin from Mxg genotypes using choline chloride-based natural deep eutectic solvents (NADES) systems. Interestingly, choline chloride: lactic acid (ChCl: LA) NADES-processed biomass resulted in 67.8 ± 2.1 μg g−1 of anthocyanins from dry biomass. A maximum of 87.4%–94.1% glucose yield was achieved after enzymatic saccharification. The effective extraction of lignin with high purity with higher β-aryl ether (βO4) bonds from advanced crops is crucial for lignin valorization. Notably, highly pure lignin (≈93.4% ± 1.4%) is achieved after low-temperature NADES pretreatment while retaining lignin’s native structure. 31P nuclear magnetic resonance demonstrated that total phenolics for ChCl: LA-lignin resulted in 1.20 mmol g−1 hydroxyls. The relative monolignol composition of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) is 19.0, 65.7, and 14.3%, respectively, as evidenced by heteronuclear single quantum coherence analysis. This study provides a novel approach for obtaining high-purity lignin for catalytic depolymerization for oligomers and bifunctional monoaromatics production and leverages current cellulosic biorefinery technologies.

biomass analytics↗

DOE OSTI2025

Gas Hydrate Film Growth in Microfluidic Channels for Carbon Dioxide Capture and Sequestration Applications

Gas or clathrate hydrates are a solid, crystalline compound composed of water and guest molecules that typically form at high pressure and low temperature conditions. Carbon dioxide (CO2) hydrates may be involved in several carbon dioxide capture and sequestration (CCS) applications, including CO2 pipeline transportation and CO2 offshore sequestration. Within these applications, the formation mechanism and kinetics must be well understood to manage the CCS processes, either by preventing or promoting hydrate formation. In this work, a high-pressure glass microfluidic reactor is used in tandem with visual microscopy and in-situ Raman spectroscopy to study both the morphological and kinetic behavior of gas hydrate crystals. Subcooling, pressure, and CO2 flow rate are investigated for their impact on the thickening behavior of pure CO2 hydrates, with flow rate being the only parameter to have a significant effect. Visual and Raman spectroscopy evidence show that both a dense hydrate layer and a porous hydrate layer form, and the latter may provide a path for mass transfer to continue hydrate crystallization. A first principles mass transfer model is developed to describe CO2 hydrate crystal thickening at the interface between gas and water. The impacts of gas impurities and channel wettability are also studied. This method is further applied to investigate the conversion of methane hydrate to CO2 hydrate for combined energy recovery and methane hydrate formation. The authors acknowledge the US Department of Energy Basic Energy Science award # DE-SC0022162.

Wadsworth, Lindsey [Colorado School of Mines, Gold↗

DOE OSTI2018

Functional interlayers of fullerene derivatives and applications in organic solar cells

The invention provides novel materials, methods and designs to enable improved power conversion efficiencies of organic photovoltaics (OPVs). In particular, the invention provides novel materials and interlayers for polymer-based solar cells. Novel functional fullerene-based interlayers are disclosed that enable high efficiency devices in conjunction with numerous active layer and electrode materials.

14 SOLAR ENERGY↗

DOE OSTI2018

Chimeric enzymes for conversion of lignin-derived chemicals

Disclosed herein are enzymes useful for the dealkylation of aromatic substrates, including the conversion of guaiacol or guaethol to catechol. Methods of converting aromatic substrates found in lignin-based feedstocks such as pyrolysis oil into products such as catechol are also disclosed. Also presented herein are methods for rapidly evolving and optimizing genetic regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Conversion of ethanol to C5+ ketones in single catalyst bed

Methods, systems and catalysts for converting an alcohol containing feedstock to an upgraded material in a single catalyst bed wherein a feedstock is fed to a catalyst under preselected conditions to obtain an intermediate; and condensing the intermediate through an aldol condensation reaction to yield a product containing an upgraded material. In one instance the feedstock includes ethanol, the catalyst is a mixed metal oxide catalyst and the upgraded material is typically a C5+ ketone(s) or alcohol(s), such as 2-pentanone, 2-heptanone, 4-heptanone and 2-nonanone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Electrochemical catalyst for conversion of nitrogen gas to ammonia

The invention provides a method of converting nitrogen into ammonia. The method comprises contacting an electrocatalyst with an aqueous solution of dissolved nitrogen gas. The electrocatalyst comprises carbon nanospikes doped with nitrogen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Hexagonal Distributed Embedded Energy Converter (HexDEEC)

Hexagonal Distributed Embedded Energy Converters are relatively small, centimeter scale, energy transducers that leverage variable capacitance to generate electricity when their hyperelastic structure is dynamically deformed. A multitude of HexDEECs can be woven to form construction materials that can be used to build complete energy conversion structures, such as ocean wave energy converters.

BFSF↗

DOE OSTI2023

Continuous multimodal technologies in industrial microbiology: potential for achieving high process performance and agility

The field of industrial microbiology has great potential to tackle the most pressing challenges facing society, but today, this entails much more than classical fermentation technology followed by product upgrading. Methods are needed to confer unit-operation-level functionality and whole-system-level robustness, as well as flexibility. As examples of this concept, we focus here on methodologies often deployed at industrial scale as discrete processes—such as biological, chemical, and electrochemical unit operations—that are also capable of substantial complementarity when combined sequentially and operated continuously. A key and relatively new type of conversion step is made possible by catalyst immobilization methods at both the enzymatic and cellular level. Cases drawn from electro-fermentation for acetoin production and syngas-mediated microbial electrosynthesis of ethanol exemplify the synergy of combined operational approaches. Because modular processes can be treated as a series of reactor elements, considerable flexibility is possible. As discussed, however, not all processes are amenable to this intensification.

09 BIOMASS FUELS↗

DOE OSTI2018

Preface

This special issue of Catalysis Today results from the Symposium in Catalysts and Catalytic Technologies for Conversion of Biomass and its Derivatives during the 252nd American Chemical Society National Meeting & Exposition held in Philadelphia, Pennsylvania on August 22 – 24, 2016. The topics of the three-day symposium covered (1) experimental and theory/computational methods for characterization and reactivity studies of biomass catalytic conversion; (2) novel catalytic materials for biomass processing: heterogeneous, homogeneous and biological catalysts; (3) catalytic technologies for biomass pretreatment and upgrading; and, (4) catalytic conversion of lignocellulose, starch, sugars and lipids to fuels and chemicals. The symposium consisted of 49 accepted presentations, with three keynote talks specifically on hydrogenation/hydrogenolysis of furans, thermochemical conversion of biomass and valorization of lignocellulosics to fuels, materials and chemicals.

Olarte, Mariefel V.↗

DOE OSTI2024

Cascade photocatalysis device

Described herein are devices and methods utilizing cascade photocatalysis to drive multiple chemical reactions via a series of photoelectrochemical catalysts driven by the conversion of light into current by one or more photovoltaic devices. The described devices and methods are tunable and may be used in conjunction with different reactants and products, including the conversion of carbon dioxide into valuable hydrocarbon products.

Tamboli, Adele Clare↗

DOE OSTI2018

Understanding the Reactive Adsorption of H 2 S and CO 2 in Sodium-Exchanged Zeolites

Purifying sour natural gas streams containing hydrogen sulfide and carbon dioxide has been a long-standing environmental and economic challenge. In the presence of cation-exchanged zeolites, these two acid gases can react to form carbonyl sulfide and water (H 2 S+CO 2 H 2 O+COS), but this reaction is rarely accounted for. In this work, we carry out reactive first-principles Monte Carlo (RxFPMC) simulations for mixtures of H 2 S and CO 2 in all-silica and Na-exchanged forms of zeolite beta to understand the governing principles driving the enhanced conversion. The RxFPMC simulations show that the presence of Na + cations can change the equilibrium constant by several orders of magnitude compared to the gas phase or in all-silica beta. The shift in the reaction equilibrium is caused by very strong interactions of H 2 O with Na + that reduce the reaction enthalpy by about 20 kJmol -1 . The simulations also demonstrate that the siting of Al atoms in the framework plays an important role. Lastly, the RxFPMC method presented here is applicable to any chemical conversion in any confined environment, where strong interactions of guest molecules with the host framework and high activation energies limit the use of other computational approaches to study reaction equilibria.

03 NATURAL GAS↗

DOE OSTI2023

Modeling of Liquid Hydrogen Tank Cooled with Para-Orthohydrogen Conversion

With the accelerating development of liquid-hydrogen storage facilities, the problem of boil-off hydrogen losses becomes very important. A promising method to reduce these losses is to utilize the endothermic para-orthohydrogen conversion of vented hydrogen, which can effectively decrease heat loads on a hydrogen tank. To model such a process, a hybrid computational model has been developed, based on the application of computational fluid dynamics for an ullage space, where knowledge of thermal stratification is important, and reduced-order models for other system elements. The simulation results for a spheroidal tank in selected conditions indicated a 10–25% reduction of boil-off losses due to cooling produced by vented hydrogen undergoing para-ortho-conversion.

08 HYDROGEN↗

DOE OSTI2018

Ultrafast Spin-to-Charge Conversion at the Surface of Topological Insulator Thin Films

Strong spin–orbit coupling, resulting in the formation of spin–momentum–locked surface states, endows topological insulators with superior spin–to–charge conversion characteristics, though the dynamics that govern it have remained elusive. Here, an all–optical method is presented, which enables unprecedented tracking of the ultrafast dynamics of spin–to–charge conversion in a prototypical topological insulator Bi 2 Se 3 /ferromagnetic Co heterostructure, down to the sub–picosecond timescale. Compared to pure Bi 2 Se 3 or Co, a giant terahertz emission is observed in the heterostructure that originates from spin–to–charge conversion, in which the topological surface states play a crucial role. A 0.12 ps timescale is identified that sets a technological speed limit of spin–to–charge conversion processes in topological insulators. Additionally, it is shown that the spin–to–charge conversion efficiency is temperature independent in Bi 2 Se 3 as expected from the nature of the surface states, paving the way for designing next–generation high–speed optospintronic devices based on topological insulators at room temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Dynamic Load Inrush Current Mitigation in Islanded Microgrids Powered by Grid-Forming Inverters

Grid-forming inverters in a microgrid may trip due to high inrush current caused by a switched connection of an inductive load, e.g., a relatively large induction motor. The control scheme presented in this article includes virtual inertia control method superimposed on the cascaded controller. This article studies the impact of cascaded control scheme used for grid-forming inverter to mitigate the inrush current effects and enhance the inverter’s robustness for the safe connection of inductive and dynamic loads. Experimental tests are performed using the virtual inertia method for generating the reference angle for synchronous frame conversion. The experimental performance and sensitivity of the controller to different controller gain settings for a switched connection of an induction motor are discussed. The cascaded operation significantly mitigates the inrush currents while the inverters can perform a normal operation. The performance of the control method is tested in a laboratory-scale hardware setup of a 208V microgrid fed by 5kVA and 10kVA inverters, and the results are presented.

Gursoy, Mehmetcan↗