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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Machine Learning for Computational Heterogeneous Catalysis

Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the development of scientific data repositories, as well as data mining and machine learning tools to investigate the vast materials space. The goal of using these tools is to establish a deeper understanding of the relations between materials properties and activity, selectivity and stability – the important figures of merit in catalysis. Based on these insights, catalyst design principles can be established, which hopefully lead us to discover highly efficient catalysts to solve pressing issues for a sustainable future and the synthesis of highly functional materials, chemicals and pharmaceuticals. The inherent complexity of catalytic reactions quests for machine learning methods to efficiently navigate through the high‐dimensional hyper‐surfaces in structure optimization problems to determine relevant chemical structures and transition states. In this review, we show how cutting edge data infrastructures and machine learning methods are being used to address problems in computational heterogeneous catalysis.

Schlexer Lamoureux, Philomena↗
DOE OSTI2018

Infrared Microscopy as a Probe of Composition within a Model Biofuel Cell Electrode Prepared from Trametes versicolor Laccase

Abstract Infrared microscopy was applied in the study of laccase biofuel cell electrodes that demonstrated high current and power densities traceable to the use of a low equivalent weight (EW), short side chain (Aquivion) ionomer in the catalyst layer. The electrodes were prepared from a biocatalyst ink composed of orientation‐directing anthracene‐modified multi‐walled carbon nanotubes (An‐MWCNTs) in a dispersion of ionomer exchanged by hydrophobic cations. The ink was applied to an electronically conductive carbon felt support that was hot‐pressed to a Nafion‐NRE 212 (51 μm thickness) membrane, forming the framework for an air‐breathing biofuel cell cathode. Infrared microscopy sampling was performed with the use of a micro‐attenuated total reflection probe that enabled spectra to be recorded from ∼32 μm diameter circular spatial regions on the materials investigated. Sensitivity to deformation of the soft polymer membrane‐based materials was assessed through trial experiments on pure membrane samples before approaching the compositionally more complex biofuel cell electrodes. In studies of laccase cathodes, infrared spectral features of enzyme, buffer anions and surrounding An‐MWCNTs were identified. Heterogeneity in the spatial distribution of components and unexpected bands traceable to insoluble copper salts were detected. The results suggest directions for improving electrode activity and bring to light needs for advancing quantitative interpretations.

Liang, Ying↗
DOE OSTI2024

In‐Situ Product Removal for the Enzymatic Depolymerization of Poly(ethylene terephthalate) via a Membrane Reactor

Poly(ethylene terephthalate) (PET) is a common single-use plastic and a major contributor to plastic waste. PET upcycling through enzymatic depolymerization has drawn significant interests, but lack of robust enzymes in acidic environments remains a challenge. This study investigates in-situ product removal (ISPR) of protons and monomers from enzymatic PET depolymerization via a membrane reactor, focusing on the ICCG variant of leaf branch compost cutinase. More than two-fold improvements in overall PET depolymerization and terephthalic acid yields were achieved employing ISPR for an initial PET loading of 10 mgPET ml buffer −1 . The benefit of ISPR was reduced for a lower initial loading of 1 mgPET ml buffer −1 due to decreased need for pH stabilization of the enzyme-containing solutions. A back-of-envelop analysis suggests that at a modest dilution ratio, ISPR could help achieve savings on caustic base solutions used for pH control in a bioreactor. Our study provides valuable insights for future ISPR developments for enzymatic PET depolymerization, addressing the pressing need for more sustainable solutions towards plastic recycling and environmental conservation.

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

Rapid eco‐phenotypic feedback and the temperature response of biomass dynamics

Biomass dynamics capture information on population dynamics and ecosystem-level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time-series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment-dependent eco-phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Reduction of Pertechnetate by Chemical and Photochemical Approaches and Incorporation of Tc(IV) into Titanium Dioxide

Technetium-99 is a prevalent fission product from nuclear waste. The long half-life (211,000 yr) and environmental mobility of pertechnetate (TcO 4 - ) render Tc particularly challenging to isolate and stabilize. Here, in this study, we present two approaches for development of potential wasteforms using titanium dioxide, TiO 2 . Approach 1 is a low temperature chemical synthesis of TiO 2 doped with Tc(IV) from TcO 4 - intended to mimic the Tc waste stream from the UREX family of separations and removes 98.5 % of the Tc, mainly present as edge-shared Tc(IV) pairs. Approach 2 utilizes TiO 2 to photocatalytically reduce TcO 4 - to Tc(IV) stabilized on the surface of or within the TiO 2 lattice. The %Tc removed from solution and adsorbed to TiO 2 is pH dependent, with the maximum Tc(IV) adsorbed at pH 3–4 as either TcO 2 or edge-sharing Tc(IV) octahedra. The Tc(IV)-TiO 2 composites materials formed by both approaches are suitable for consolidation into a dense wasteform by Hot Isostatic Pressing (HIPing).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

Abstract The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub‐daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state‐of‐the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model‐data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge‐guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision‐relevant predictions of riverine water quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Hydroxide-ion transport and stability of diblock copolymers with a polydiallyldimethyl ammonium hydroxide block

Base-stable amphiphilic diblock copolymers with a polydiallyl dimethyl ammonium hydroxide block were synthesized and characterized to quantify hydroxide-ion transport in the hydrated state; polystyrene was the hydrophobic block. The challenge of synthesizing a copolymer comprising blocks with very different solubility behaviors was addressed by a combination of reversible addition fragmentation chain transfer polymerization and ion metathesis. Both monomers used in the polymerization are commercially available on industrial scales. Hydroxide-ion conductivities of 0.8 mS/cm were achieved in hot-pressed membranes immersed in water at room temperature despite relatively low water uptake (4.2 water molecules per hydroxide ion). Finally, the stability of the polydimethyl ammonium hydroxide chains was investigated in 2 M NaOD at 60 °C.1H NMR spectroscopy studies showed no detectable degradation after 2000 hours.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hypersonic Jets of Detonation Products in the Hydrodynamic Collapse of Macroscopic Voids

Localizing the energetic output from detonation waves has been a long-standing challenge in applied detonation physics. Here, energy localization is achieved via machined millimeter scale voids in pressed samples of PBX 9501, an HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane)-based plastic bonded explosive. A main mechanism of energy localization in these systems, the formation of hydrodynamic jets of dense product gases, is characterized experimentally using a semicylindrical geometry in witness plate impact experiments and streak imaging of the jet propagating into the air. The distance at which the jet is optimally developed is identified and the supersonic flow structure in the vicinity of this feature is explored using hydrocode simulations. This analysis found that most of the kinetic energy of the hydrodynamic jet arises from pressure gradients induced by geometrically mediated squeeze flow lateral to the direction of detonation propagation. This work presents a new development in the control of energetic output from detonation waves and applications to detonation wave shaping are discussed.

42 ENGINEERING↗
DOE OSTI2017

Statistics of Density, Temperature and Air Gaps on the TATB Cylinder Test

In this paper, duplicate cylinder tests (CYLEX) have been run on PBX 9502 and LX-17. The 95 % error in the absolute value of the derived detonation energy density is about ±1 % whereas the 95 % error of the difference error is ±0.5 % or better. The analytic model has been upgraded with a better strain description. The effect of the air gap between a pressed solid explosive and the inner copper wall has been measured and modeled. An off-center effect has also been seen. Density effects on the energy density from 1.82 to 1.92 g cm -3 are described for LX-17. Data has also been taken at -55, 75 and 125 °C. Finally, the last temperature gives a large enough difference to show that the mechanism appears to be only density change.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Nonlinear Resonant Ultrasound Spectroscopy for Predicting Sensitivity to Initiation in Granular High Explosives

Abstract Nonlinear Resonant Ultrasound Spectroscopy (NRUS) is a technique that can measure bulk nonlinear coefficients of the nonlinear elastic modulus for a material. NRUS has been used to identify damage in a variety of granular materials including rocks and concrete. Some energetic materials, such as Pentaerythritol Tetranitrate (PETN), are commonly fielded as pressed granular compacts. It is well known that the sensitivity to initiation of these materials is heavily dependent on their microstructure, and that microstructure changes naturally (becomes damaged) over time. In this study, we examine the use of NRUS to identify changes in microstructure between pristine and thermally aged PETN pellets. In particular, we examine the relationship between the bulk hysteretic nonlinearity, α , of the pellets and time spent at temperature, powder specific surface area (SSA), and sensitivity to initiation. We find that, in general, α does not increase uniformly for all pellets within a single thermal aging condition. However, when the pellets are test fired to determine sensitivity to initiation, there is a strong correlation between α and firing voltage threshold. NRUS‐measured α has the added benefit that the measurements can be made in situ and on benchtop scales.

Schulze, Peter↗
DOE OSTI2019

Prediction of Probabilistic Detonation Threshold via Millimeter-Scale Microstructure-Explicit and Void-Explicit Simulations

We present an approach and relevant models for predicting the probabilistic shoc-to-detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure-explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro-1,3,5,7-tetranitro-1,2,3,5-tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical-thermal-chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank-ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run-distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Gas Transport in the Insensitive High Explosive PBX 9502

Small-scale laboratory experiments were performed to analyze gas transport mechanics in PBX 9502, an insensitive high explosive (IHE) composition. Two independent investigations are reported here. First, gas permeametry and dynamic pycnometry techniques were used to measure the molecular flow (Knudsen) coefficient and the internally interconnected void fraction of pristine and thermally damaged samples in two uniaxial pressing orientations. The permeability of PBX 9502 was found to be unmeasurably low (of the same order of magnitude as PTFE) with gas transport being diffusion-dominated. Secondly, a pressure vessel experiment was developed to measure quasi-static and dynamic gas generation as the explosive was heated to self-ignition (cookoff). The gas generation results and the permeability/diffusivity findings provide evidence that PBX 9502 remains impermeable until seconds prior to self-ignition. At ignition, internal void-pressure drives macro-scale cracking and the sample becomes uniformly incorporated in the following deconsolidating deflagration. These results are discussed within the context of previous observations of pressure-dependent cookoff behavior of PBX 9502 and provide a more complete description of thermal damage evolution in this explosive composition.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Coefficient of Thermal Expansion during Ratchet Growth of TATB Compactions

Triamino trinitrobenzene (TATB) is an insensitive high explosive, meaning that it is quite immune from accidental detonation and only performs in appropriately engineered configurations. While this is advantageous for applications, the TATB crystal is graphitic and possesses significant thermal and mechanical anisotropy. Compactions of TATB crystals, with or without binder, have been shown to have oriented TATB crystals that relate to the pressing geometry and process, and this TATB texture necessarily imparts microscale and macroscale anisotropy to the compaction. By a mechanism not fully understood, thermal cycling results in irreversible volume expansion (also called ratchet growth) of the compaction likely by creating stress points on the microscale. Changes in density caused by thermal cycling can certainly effect the explosive performance. Our past characterization of the ratchet growth phenomenon has focused on the magnitude of the irreversible strain as measured before and after a thermal cycle. Finally, in the work presented here, we analyze the evolving thermal expansion behavior during the ascending and descending temperature ramps, providing further insight into the material changes taking place during the ratchet growth phenomenon.

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

Effects of sub‐mm cylindrical voids on detonation performance in PBX 9501

Abstract Internal features of varying scale and geometry are always present in explosives systems. Below a critical length, dependent on the explosive, these features can operate as a driving force for energy concentration and reaction, known as hotspots. At larger length scales, internal features result in jetting and detonation wave shaping, allowing for bulk work to be done by the explosive as is seen in shape charges. To date, a large volume of work has been performed to simulate hotspot ignition and large‐scale wave shaping. However, little experimental data exists on the effects of features in intermediate length scales, 0.1 to 1 millimeter. It has been observed in many tests that these small‐scale features can influence the high explosive (HE) performance and in some cases cause substantial damage to adjacent systems. This work provides quantitative data on the effects of machined voids moderately above more typical hotspot lengths, 0.3–0.8 mm in diameter, in PBX 9501 pressed to 1.785 g cm −3 ±2.5 mg cm −3 . Streak imaging was used to visualize void collapse, jet velocity, re‐initiation time, and wave shape evolution. Delay in detonation front propagation time was found to be linearly dependent on the void diameter and jet velocity was found to be independent within the tested range and resolution. Cut‐back experiments were used to investigate wave shape distortion and evolution downstream of the void, showing consistent growth and decay shapes across all void sizes. Simulations using CTH, a hydrocode by Sandia National Laboratory, were used to investigate void collapse showing agreement with the trends of experimental results but yielded inaccurate wave shape development delay values. Both simulation and experimental results identified several re‐initiation mechanisms with jetting and subsequent double shocking of localized HE being the dominant mechanisms for the void sizes that were studied.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗