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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

New coal char-based bricks: Effects of curing temperature, humidity, pressing pressure, and addition of superplasticizer on the physical, mechanical, and thermal properties

Coal char, as a sustainable and eco-friendly material, holds significant potential for use in new construction materials, specifically, coal char-based bricks. This study employed the pre-pressing method to create char bricks containing high char content of 70%. The impact of various curing temperatures (20, 40, 60 °C), humidity levels (15% and 90%), and pressing pressures (3.5, 7, and 10 MPa) on the density, X-ray diffraction, compressive strength, and thermal conductivity of char-based samples were examined. The addition of superplasticizer and the performance of char bricks were assessed by comparing them to traditional clay bricks and corresponding standards. The study discovers that the temperature of 40 °C enhances the early 7-day strength of char brick samples, while the highest 28-day strength is observed in char bricks at a temperature of 20 °C and humidity of 90%. Compared to conventional clay bricks (with density of 1.9 g/cm3, thermal conductivity of 0.39-0.63 W/mK, compressive strength of 10-20 MPa), the proposed char bricks exhibit lower density (~0.8 g/cm 3 ), lower thermal conductivity (0.26-0.35 W/mK), and good performance in compressive strength (up to 15 MPa). Lastly, coal char-based bricks with high char content demonstrate significant advantages over traditional clay bricks, making them a sustainable and environmentally friendly building material option.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recent advances in nano-scale spatial resolution x-ray microscopy instrumentation at NSLS-II

X-ray microscopy is an invaluable and powerful characterization tool applied in many scientific fields, such as materials science, biology, environmental science, and energy research. In recent years it has been driven by rapid developments of novel technologies and systems resulting in imaging experiments elucidating structural inhomogeneities and chemical reactions at the nanometer scale. To obtain high spatial resolution comprehensive chemical and structural information, an X-ray microscope must be equipped with adequate capabilities and allow for simultaneous acquisition of multiple datasets. In recent years, a number of X-ray microscopes have been designed, constructed, and commissioned at NSLS-II. Here we provide an overview of the microscopy instrumentation development program at NSLS-II and specifically focus on the multilayer Laue lens-based hard X-ray nanoprobe optimized for ~10 nm spatial resolution imaging, its current status, and future upgrades along with recently constructed Kirkpatrick-Baez based scanning microscope designed for ~100 nm spatial resolution experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hematite Crystallization from a Two-Line Ferrihydrite Suspension

Rational design and synthesis of materials, determination of environmental conditions at the time of mineral formation, and definition of mechanisms in biomineralizing systems all require an understanding of the effect of multiple factors on modulating crystallization pathways. In this study, we investigate the influence of temperature, oxalate additive, aging time, and addition of seed crystals on hematite (α-Fe 2 O 3 , Hm) crystallization from a two-line ferrihydrite (Fe 2 O 3 ·xH 2 O, Fh) suspension. We also investigate the effect of temperature on the aging of spindle-shaped Hm mesocrystals, which we synthesize through the addition of sodium oxalate. The results show that Hm mesocrystals form in a temperature window of 45 °C-130 °C. Temperatures ≥ 140 °C favor formation of rhombohedral Hm, suggesting classical monomer-by-monomer growth dominates, whereas crystallization by particle attachment (CPA) is dominant between 45 and 90 °C, while the two processes compete in the intermediate temperature range. Aging of mesocrystals in the original solution at 90 °C or 180 °C leads to a slow morphological evolution towards rhombohedral crystals due to Ostwald ripening. Then, by utilizing rhombohedral Hm and rod-shaped goethite as substrates on which to assemble the mesocrystals, we demonstrate formation of complex heterogeneous structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CO2 Sorption in Aminopolymer-Based Direct Air Capture Composites Through Fluorescent Detection

Aminopolymer-mesoporous oxide composites are becoming widely recognized for their ability to adsorb CO2 directly from the air. However, a better fundamental understanding of the nature of these materials under different environmental operating conditions will be necessary before they become ubiquitous in industrial direct air capture (DAC) systems. For example, gas diffusion in general is coupled with polymer segmental mobility in these composites; diffusion is therefore affected by interactions of the polymer with the pore wall of the mesoporous oxide, by the relative humidity of the air, and by electrostatic crosslinks that develop as a function of CO2 sorption. Disentangling these and additional complicated effects in order to better optimize operating conditions is a major challenge for the field. Here, we present a method for quantifying the adsorption of CO2 and moisture in a polyethylenimine (PEI) - Al2O3 composite using infrared sensing while we simultaneously monitor polymer mobility with a fluorescent probe molecule doped into the composite. Both the fluorescence intensity and shape of the emission spectra are strongly dependent on the mobility of the supporting medium. We monitor the polymer mobility and CO2 adsorption kinetics across a series of different relative humidities (RH) with this technique, and we observed that the relative difference between polymer mobility and sorption kinetics from one RH to the next are quite dramatic. We interpret these results and discuss how they can be used to inform the design of more efficient DAC systems for real-world operating conditions.

carbon capture↗
DOE OSTI2026

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Temperature Corrosion of Chromia-Forming Ni-Based Alloys in CO 2 Containing Impurities

Future technologies require structural materials resistant to environmental degradation in high-temperature CO 2 -rich environments. In this work, we exposed several commercially available Ni-based alloys (230, 263, 282, 617, 625, and 740H) to atmospheric pressure gases intended to simulate the compositions expected in future direct-fired supercritical CO 2 power cycles. The alloys were exposed to 95% CO 2 + 4% H 2 O + 1% O 2 and the same gas containing 0.1% SO 2 at temperatures of 600, 650, 700, 750, and 800 °C for 2500 h. With minor exceptions, chromia scales formed on all alloys at all temperatures in the SO 2 -free gas, yielding parabolic growth rates that followed an Arrhenius temperature dependence. Behavior in the SO 2 -containing gas was more complex. Generally, the alloys performed well at temperatures of 650, 750, and 800 °C. While some alloys further performed relatively well across the whole temperature range, several of the alloys experienced chromia failure resulting in non-protective duplex oxide scales and high oxidation rates, at temperatures of 600 and 700 °C. Deviation from protective behavior was associated with internal sulfide formation and, additionally for the case of 600 °C, external sulfate formation. Extensive carburization accompanied growth of the non-protective duplex oxide scales, which made it more difficult for the alloy to recover after initiation of the sulfur-induced accelerated corrosion process. The thermodynamic and kinetic factors influencing the accelerated corrosion in the presence of sulfur are discussed. The results suggest that caution is required when assessing compatibility of Ni-based alloys for CO 2 -based systems when sulfur-based impurities are expected.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A General Route to Flame Aerosol Synthesis and In Situ Functionalization of Mesoporous Silica

Abstract Mesoporous silica is a versatile material for energy, environmental, and medical applications. Here, for the first time, we report a flame aerosol synthesis method for a class of mesoporous silica with hollow structure and specific surface area exceeding 1000 m 2 g −1 . We show its superior performance in water purification, as a drug carrier, and in thermal insulation. Moreover, we propose a general route to produce mesoporous nanoshell‐supported nanocatalysts by in situ decoration with active nanoclusters, including noble metal (Pt/SiO 2 ), transition metal (Ni/SiO 2 ), metal oxide (CrO 3 /SiO 2 ), and alumina support (Co/Al 2 O 3 ). As a prototypical application, we perform dry reforming of methane using Ni/SiO 2 , achieving constant 97 % CH 4 and CO 2 conversions for more than 200 hours, dramatically outperforming an MCM‐41 supported Ni catalyst. This work provides a scalable strategy to produce mesoporous nanoshells and proposes an in situ functionalization mechanism to design and produce flexible catalysts for many reactions.

Liu, Shuo↗
DOE OSTI2022

A General Route to Flame Aerosol Synthesis and In Situ Functionalization of Mesoporous Silica

Mesoporous silica is a versatile material for energy, environmental, and medical applications. In this work, for the first time, we report a flame aerosol synthesis method for a class of mesoporous silica with hollow structure and specific surface area exceeding 1000 m 2 /g -1 . We show its superior performance in water purification, drug carrier, and thermal insulation. Moreover, we propose a general route to produce mesoporous nanoshell supported nanocatalysts by in situ decorating active nanoclusters, including noble metal (Pt/SiO 2 ), transition metal (Ni/SiO 2 ), metal oxide (CrO 3 /SiO 2 ), and alumina support (Co/Al 2 O 3 ). As a prototypical application, we perform dry reforming of methane using Ni/SiO 2 , achieving constant 97% CH 4 and CO 2 conversions for more than 200 hours, dramatically outperforming MCM-41 supported Ni catalyst. This work provides a scalable strategy to produce mesoporous nanoshells and proposes an in situ functionalization mechanism to flexible catalysts design for many reactions.

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

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multi-species electrolyte migration kinetics with directed flow

Here, this paper investigates an electrochemical process designed to control mixing kinetics in liquid electrolytes. The process utilizes an electrochemical cell with anode and cathode chambers connected by a channel without a membrane. This configuration depletes multiple electroactive species in the cathode chamber while selectively replenishing them in the anode chamber. A key application is the removal of impurity species from the cathode chamber electrolyte and the selective replenishment of primary electroactive species in the anode chamber. Aqueous cell experiments were conducted to validate the theoretical model, and simulations were performed for molten salt electrolytes. This approach minimizes waste by reducing the need for additional electrolyte supplies and extends the utilization of anion species, contributing to environmentally sustainable electrochemical materials processing.

Electrochemical Process↗
DOE OSTI2025

Scanning Electrochemical Microscopy: An Evolving Toolbox for Revealing the Chemistry within Electrochemical Processes

The parallel development of ultramicroelectrodes (UMEs) and groundbreaking scanning probe microscopy techniques in the late 1980s led to the development of the scanning electrochemical microscope. Scanning electrochemical microscopy (SECM) was born from the idea of using a tiny electrode to measure the local electrochemical behavior at operating electrodes. From its foundations, the technique displayed an inherent versatility in measuring sample properties beyond topography. It allowed experimenters to measure and map chemical reactions occurring at diverse interfaces, from inspecting the reversibility of redox mediators at metal electrodes, to detecting the hallmarks of cellular respiration on living plant leaves. Related but distinct electrochemical scanning probe techniques, such as electrochemical atomic force microscopy (EC-AFM), scanning ion conductance microscopy (SICM), and scanning electrochemical cell microscopy (SECCM) have developed in parallel. These techniques have demonstrated exquisite spatial resolution down to the nanoscale regime. However, it is the proposition of this review that SECM remains unmatched at revealing the chemical aspects of electrochemistry. Furthermore, it is our intention to review and demonstrate that the versatile architecture of SECM continues to evolve and address fundamental and emerging challenges in the fields of energy storage and conversion, chemical biology, materials science, and environmental chemistry, among others.

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

Unraveling pH-Dependent Changes in Adsorption Structure of Uranyl on Alumina (012)

Mitigating uranium transport in groundwater is imperative for ensuring access to clean water across the globe. Here, in situ resonant anomalous X-ray reflectivity is used to investigate the adsorption of uranyl on alumina (012) in acidic aqueous solutions, representing typical U VI concentrations of contaminated water near mining sites. The analyses reveal that U VI adsorbs at two distinct heights of 2.4-3.2 and 5-5.3 angstrom from the surface terminal oxygens. The former is interpreted as the mixture of inner-sphere and outer-sphere complexes that adsorb closest to the surface. The latter is interpreted as an outer-sphere complex that shares one equatorial H 2 O with the terminal surface oxygen. With increasing pH, we observe an increasing prevalence of these outer-sphere complexes, indicating the enhanced role of the hydrogen bond that stabilizes adsorbed uranyl species. Finally, the presented work provides a molecular-scale understanding of sorption of uranyl on Al-based-oxide surfaces that has implications for environmental chemistry and materials science.

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

Composition and Configuration Dependence of Glass-Transition Temperature in Binary Copolymers and Blends of Polyhydroxyalkanoate Biopolymers

Polyhydroxyalkanoates (PHAs), a promising class of biomaterials, have gained considerable attention to replace petroleum-based plastics owing to their excellent biocompatibility and biodegradability. Homopolymers of PHA suffer from poor tunability in thermal and mechanical properties. Going from homopolymers to copolymers, the design space can be substantially enhanced by combining two or more monomers in different compositions (i.e., relative ratios of the different monomers) and configurations (i.e., relative positions of the different monomers in the polymer backbone) leading to a substantially large chemical space where application-specific optimization for the targeted functionality can be performed. However, this composition and configuration dependence of properties in the vast PHA copolymer chemical space remains largely unexplored. In this contribution, further building on our past work with PHA homopolymers, we systematically explore these chemical trends for glass-transition temperature (Tg) in PHA copolymers and blends. Overall, our molecular dynamics simulations, utilizing a previously validated force field for PHAs, suggest that these trends are largely governed not only by the homopolymer Tg values but also configuration-dependent interchain interactions in the copolymer system. In particular, our results indicate that the configuration-dependent variation in the target property at a fixed composition can be significant in the presence of hydrogen-bond-forming monomers. These qualitative observations are further rationalized by quantitatively analyzing various closely related atomic level descriptors of copolymers and blends such as monomer mobility, number of hydrogen bonds, and pair correlation functions. The findings presented in this work help to develop a deeper atomistic-level understanding of thermomechanical behavior of PHA-based copolymers and can potentially guide the rational design of biopolymers as environmental-friendly functional materials.

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

Coordinated Cation Transport in Ti 3 C 2 T x MXene Membranes

Membrane nanofiltration is an attractive strategy for the selective recovery of high-demand metals from wastewater and brine. Effective sieving of ions in aqueous environments will require precise control over membranes’ nanochannel size and chemistry. Ti 3 C 2 T x MXene is an environmentally stable 2D material that can be processed into laminar membranes containing nanoscale interlayer spaces. The MXene interlayer environment depends on the ion species and amount of water intercalated between MXene sheets, and it is the major factor governing permeation and selectivity through MXene membranes. Coordinated ion–ion and ion-interlayer dynamics in the presence of complex mixtures can impact ion permeability and selectivity. Herein, we observe strong competitive effects between different cations (Li + , Na + , and Ca 2+ ) in binary mixtures, resulting in reduced selectivity when compared with single-salt permeability ratios. X-ray diffraction, molecular dynamics, and density functional theory simulations support the conclusion that cations with stronger attraction to MXene flakes can preferentially occupy the MXene nanochannels and hinder other ions via charge or size exclusion. In conclusion, elucidation of ion transport behavior in MXene under complex conditions will allow for more rational design of efficient ion-sieving membranes.

2D Materials↗
DOE OSTI2021

Snapshots of Ce 70 Toroid Assembly from Solids and Solution

Crystallization at the solid–liquid interface is difficult to spectroscopically observe and therefore challenging to understand and ultimately control at the molecular level. The Ce70-torroid formulated [Ce IV 70 (OH) 36 (O) 64 (SO 4 ) 60 (H 2 O) 10 ] 4– , part of a larger emerging family of M IV 70 -materials (M = Zr, U, Ce), presents such an opportunity. We elucidated assembly mechanisms by the X-ray scattering (small-angle scattering and total scattering) of solutions and solids as well as crystallizing and identifying fragments of Ce 70 by single-crystal X-ray diffraction. Fragments show evidence for templated growth (Ce 5 , [Ce 5 (O) 3 (SO 4 ) 12 ] 10- ) and modular assembly from hexamer (Ce 6 ) building units (Ce 13 , [Ce 13 (OH) 6 (O) 12 (SO 4 ) 14 (H 2 O) 14 ] 6– and Ce 62 , [Ce 62 (OH) 30 (O) 58 (SO 4 ) 58 ] 14- ). Ce 62 , an almost complete ring, precipitates instantaneously in the presence of ammonium cations as two torqued arcs that interlock by hydrogen boding through NH 4 + , a structural motif not observed before in inorganic systems. The room temperature rapid assemblies of both Ce 70 and Ce 62 , respectively, by the addition of Li + and NH 4 + , along with ion-exchange and redox behavior, invite exploitation of this emerging material family in environmental and energy applications.

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

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Characterization of just one atom using synchrotron X-rays

Since the discovery of X-rays by Roentgen in 1895, its use has been ubiquitous, from medical and environmental applications to materials sciences. X-ray characterization requires a large number of atoms and reducing the material quantity is a long-standing goal. Here we show that X-rays can be used to characterize the elemental and chemical state of just one atom. Using a specialized tip as a detector, X-ray-excited currents generated from an iron and a terbium atom coordinated to organic ligands are detected. The fingerprints of a single atom, the L 2,3 and M 4,5 absorption edge signals for iron and terbium, respectively, are clearly observed in the X-ray absorption spectra. The chemical states of these atoms are characterized by means of near-edge X-ray absorption signals, in which X-ray-excited resonance tunnelling (X-ERT) is dominant for the iron atom. The X-ray signal can be sensed only when the tip is located directly above the atom in extreme proximity, which confirms atomically localized detection in the tunnelling regime. Finally, our work connects synchrotron X-rays with a quantum tunnelling process and opens future X-rays experiments for simultaneous characterizations of elemental and chemical properties of materials at the ultimate single-atom limit.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels

Abstract A majority of experimental disciplines face the challenge of exploring large and high-dimensional parameter spaces in search of new scientific discoveries. Materials science is no exception; the wide variety of synthesis, processing, and environmental conditions that influence material properties gives rise to particularly vast parameter spaces. Recent advances have led to an increase in the efficiency of materials discovery by increasingly automating the exploration processes. Methods for autonomous experimentation have become more sophisticated recently, allowing for multi-dimensional parameter spaces to be explored efficiently and with minimal human intervention, thereby liberating the scientists to focus on interpretations and big-picture decisions. Gaussian process regression (GPR) techniques have emerged as the method of choice for steering many classes of experiments. We have recently demonstrated the positive impact of GPR-driven decision-making algorithms on autonomously-steered experiments at a synchrotron beamline. However, due to the complexity of the experiments, GPR often cannot be used in its most basic form, but rather has to be tuned to account for the special requirements of the experiments. Two requirements seem to be of particular importance, namely inhomogeneous measurement noise (input-dependent or non-i.i.d.) and anisotropic kernel functions, which are the two concepts that we tackle in this paper. Our synthetic and experimental tests demonstrate the importance of both concepts for experiments in materials science and the benefits that result from including them in the autonomous decision-making process.

36 MATERIALS SCIENCE↗