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Results for “materials screening”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design of a robot-automated flat plate/reflection geometry x-ray diffraction setup for accelerated materials discovery and structural screening

Here, we report the design, construction, and automation of a flat plate sample loading, alignment, and data acquisition system for X-ray diffraction measurements in reflection geometry implemented at the Stanford Synchrotron Radiation Lightsource. The system is built onto a single platform, enabling facile transferability, and is compartmentalized into sample storage, sample transfer, and sample position/alignment segments. The core feature of this system is a six-axis robotic arm that offers a large range of highly reproducible and programable movements. The degrees of freedom of the robot arm enable adaptability in which movements can be modified to fit various beamline environments and sample configurations. Samples are housed on 3D printed sample mounts, which are arranged onto a 6 × 2 array of sample cassettes capable of holding 7 samples. Using sample mounts designed for solid oxide electrolysis button cells (SOECs), the maximum tray capacity is 84 samples, which can be aligned and run in ~ 24 hours with long exposure scans. The sample array is additionally capable of accommodating a range of sample sizes and geometries due to the rapid 3D printed fabrication. The components of the setup will be described in detail and performance will be demonstrated with a set of representative SOEC and XRD standard samples. Opportunities for future developments and integration with the automated setup are summarized.

08 HYDROGEN↗
DOE OSTI2021

Screening candidate supplementary cementitious materials under standard and accelerated curing through time-series surface resistivity measurements and change-point detection

Time-series surface resistivity (SR) measurements are evaluated as an indicator of pozzolanicity in concretes containing 13 materials of both known and unknown pozzolanicity, under standard and accelerated curing conditions, and the results were validated against portlandite consumption obtained through thermogravimetric analysis. Change-point detection (CPD) analysis is applied to the data to provide a rigorous indicator of hydration age of the onset and rate of the pozzolanic reaction, if occurring. The SR measurements were able to capture the onset of the pozzolanic reactions in concretes curing at elevated temperature regimes, which allows determination of pozzolanicity weeks earlier than at standard curing temperatures. Using CPD along with slope analysis allows a comprehensive analysis of a material's reactivity and determination of pozzolanicity in as quickly as two days. Time-series SR measurements at elevated curing conditions, along with limits on material composition, are recommended for determination of pozzolanic reactivity in novel or variable materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning in materials science: From explainable predictions to autonomous design

The advent of big data and algorithmic developments in the field of machine learning (and artificial intelligence, in general) have greatly impacted the entire spectrum of physical sciences, including materials science. Materials data, measured or computed, combined with various techniques of machine learning have been employed to address a myriad of challenging problems, such as, development of efficient and predictive surrogate models for a range of materials properties, screening and down-selection of novel candidate materials for targeted applications, new methodologies to improve and further expedite molecular and atomistic simulations, with likely many more important developments to come in the foreseeable future. While the applications thus far have provided a glimpse of the true potential data-enabled routes have to offer, it has also become clear that further progress in this direction hinges on our ability to understand, explain and rationalize findings of a machine learning model in light of the domain-knowledge. This focused review provides an overview of the main areas where machine learning has been widely and successfully used in materials science. Subsequently, a brief discussion of several techniques that have been helpful in extracting physically-meaningful insights, causal relationships and design-centric knowledge from materials data is provided. Finally, we identify some of the imminent opportunities and challenges that materials community faces in this exciting and rapidly growing field.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Screening of Lost Circulation Materials for Geothermal Applications: Experimental Study at High Temperature

Abstract This study presents a laboratory experimental research to determine the characteristics of lost circulation materials (LCMs) capable of addressing thermal degradation, providing bridging and sealing in geothermal conditions. Eleven different materials were tested: Walnut Fine, Walnut Medium, Sawdust, Altavert, Graphite Blend, Bentonite Chips, Micronized Cellulose (MICRO-C), Magma Fiber Fine, diatomaceous earth/amorphous silica powder (DEASP), Cotton Seed Hulls, and a Calcium Carbonate Blend. The filtration and sealing pressure of the LCMs were measured with HPHT equipment up to 149 °C (300 °F). Besides, the particle size distribution (PSD) of fine granular materials was measured. The results show that the performance of some LCM materials commonly used in geothermal operations is affected by high temperature. Characteristics such as shape and size made some materials more prone to thermal degradation. Also, it was found that the PSD of LCMs is a key factor in the effectiveness of bridging and sealing fractures. The results suggest that granular materials with a wide particle size distribution PSD are suitable for geothermal applications.

Energy & Fuels↗
NASA NTRS1986

Screening and tests of materials for space applications

The outgassing properties of materials and other considerations on materials acceptance for space applications are discussed. The uses of the outgassing data for the evaluation of important performance characteristics of a space system are indicated. The deficiencies and advantages of the ASTM-E595-77 test method and materials acceptance criteria are discussed. Also discussed are the advantages for the selection of the materials and the uses of the data provided by the long-term measurements of the outgassing rates and surface re-emission of materials. The paper concludes that the results of the ASTM method with additional derived data on the material properties can be used for the initial evaluation of a space system's characteristics. Materials data on outgassing and re-emission rates at various temperatures obtained from the more expensive, long-term QCM and TGA measurements should be obtained when a detailed analysis of a system is suggested based on the various considerations discussed in the paper.

Scialdone, J. J.↗
NASA NTRS1990

New screening methodology to select low outgassing materials for cold, spaceborne optical instruments

Standardized techniques for outgassing tests are developed and set forth for use in the screening of materials for aerospace instruments with cooled sensors, optics, and/or detectors. Materials for optical instruments are discussed in terms of molecular outgassing, and material-outgassing test results are presented which relate to several test conditions. The existing outgassing standard is found to be inadequate, and revised outgassing standards related to four application levels are given. The test protocols are designed for the development of materials for optical instruments that operate in environments with temperatures below 20 C. Consideration is also given to potential molecular contamination in the space environment and to outgas screening of instruments with a variety of sensor/optics/detector temperatures. The standards are designed for use with existing outgassing-test data as well as contamination analyses relating to the instrument being tested.

O'Donnell, T.↗
NASA NTRS1990

Materials selection for long life in low earth orbit - A critical evaluation of atomic oxygen testing with thermal atom systems

The use of thermal atom test methods as a materials selection and screening technique for low-earth orbit (LEO) spacecraft is critically evaluated. The chemistry and physics of thermal atom environments are compared with the LEO environment. The relative reactivities of a number of materials determined in thermal atom environments are compared with those observed in LEO and in high-quality LEO simulations. Reaction efficiencies (cu cm/atom) measured in a new type of thermal atom apparatus are one-thousandth to one ten-thousandth those observed in LEO, and many materials showing nearly identical reactivities in LEO show relative reactivities differing by as much as a factor of eight in thermal atom systems. A simple phenomenological kinetic model for the reaction of oxygen atoms with organic materials can be used to explain the differences in reactivity in different environments. Certain speciic thermal atom test environments can be used as reliable materials screening tools.

Koontz, S. L.↗
NASA NTRS1974

Study of the effects of fuel vortex film cooling on high temperature coating durability

A report on the effects of fuel vortex film cooling on high temperature coating durability is presented. The program evaluated candidate high temperature oxidation resistant reaction control system engine thrust chamber material. As a result of the evaluation, the current and future programs may be optimized from the materials standpoint. Engine firing data for the evaluation of one material system is generated. The subjects considered are: (1) screening of materials, (2) thrust chamber fabrication, (3) engine testing, and (4) analysis of the data.

Source record↗
DOE OSTI2026

Generative Models for Crystalline Materials

Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and accelerating materials discovery. Early ML approaches primarily focused on constructing and screening large material spaces to identify promising candidates for various applications. More recently, research efforts have increasingly shifted toward generating crystal structures using end-to-end generative models. This review analyzes the current state of generative modeling for crystal structure prediction and de novo generation. It examines crystal representations, outlines the generative models used to design crystal structures, and evaluates their respective strengths and limitations. Furthermore, the review highlights experimental considerations for evaluating generated structures and provides recommendations for suitable existing software tools. Emerging topics, such as modeling disorder and defects, integration in advanced characterization, incorporating synthetic feasibility constraints, and model explainability are explored. Ultimately, this work aims to inform both experimental scientists looking to adapt suitable ML models to their specific circumstances and ML specialists seeking to understand the unique challenges related to inverse materials design and discovery.

Metni, Houssam [Karlsruhe Inst. of Technology (KIT↗
DOE OSTI2022

Topological Superconductivity Based on Antisymmetric Spin–Orbit Coupling

Topological superconductivity (TSC) has drawn much attention for its fundamental interest and application in quantum computation. An outstanding challenge is the lack of intrinsic TSC materials with a p-wave pairing gap, which has led to the development of an effective p-wave theory of coupling s-wave gap with Rashba spin–orbit coupling (RSOC). However, the RSOC-strict mechanism and materials pose still both fundamental and practical limitations. Here, we generalize this theory to antisymmetric SOC (ASOC). Using k·p perturbation theory, we demonstrate that 2D crystals, with point groups of C 2 , C 4 , C 6 , C 2v , C 4v , C 6v , D 2 , D 4 , D 6 , S 4 , or D 2d , can all facilitate the desired ASOC. Remarkably, this enables us to discover 314 TSC candidates by screening 2D material databases, which are further confirmed by first-principles calculations of Majorana boundary modes and the topological invariant of the superconducting gap. As a result, our work fundamentally enriches TSC theory and greatly expands the classes of TSC materials for experimental exploration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

An integrated online radioassay data storage and analytics tool for nEXO

Large-scale low-background detectors are increasingly used in rare-event searches as experimental collaborations push for enhanced sensitivity. However, building such detectors, in practice, creates an abundance of radioassay data especially during the conceptual phase of an experiment when hundreds of materials are screened for radiopurity. A tool is needed to manage and make use of the radioassay screening data to quantitatively assess detector design options. We have developed a Materials Database Application for the nEXO experiment to serve this purpose. Furthermore, this paper describes this database application, explains how it functions, and discusses how it streamlines the design of the experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Opening band gaps of low-dimensional materials at the meta-GGA level of density functional approximations

The quasiparticle band structure can be properly described by Hedin's GW approximation (GW), at a high computational cost. For band gaps, semilocal density functionals up to the generalized gradient approximation (GGA) level cannot compete with the accuracy of hybrid-based approximations or GW. Meta-GGA density functionals with a strong dependence on the kinetic energy density ingredient can potentially give wider band gaps compared with GGAs. The recent TASK meta-GGA density functional from Aschebrock and Kümmel [ Phys. Rev. Research 1 , 033082 (2019) ], is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme and therefore harbors great opportunities for band gap prediction. Although this approximation was found to yield excellent band gaps of bulk solids, this accuracy cannot be straightforwardly transferred to low-dimensional materials. Additionally, the reduced screening of these materials results in larger band gaps compared with their bulk counterparts, as an additional barrier to overcome. In this paper we demonstrate how the alteration of this functional affects the band gaps of monolayers and nanoribbons and present accurate band gaps competing with the revised Heyd-Scuseria-Ernzerhof (HSE06) approximation. In order to achieve this goal, we have modified the TASK functional (a) by changing the tight upper bound for one- or two-electron systems ( h X 0 ) from 1.174 to 1.29 and (b) by changing the limit of the interpolation function f X ( α → ∞ ) of the TASK functional that interpolates the exchange enhancement factor F X ( s , α ) from α = 0 to 1. The resulting modified TASK (mTASK) was tested for various materials from three dimensions to two dimensions to one dimension (nanoribbons) and was compared with the results of the higher-level hybrid functional HSE06 or with the G 0 W 0 approximation within many-body perturbation theory. We find that mTASK systematically improves the band gaps and band structures of two-dimensional (2D) and 1D systems, without significantly affecting the accuracy of the original TASK for the bulk 3D materials, when compared with the Perdew-Burke-Ernzerhof (PBE) GGA and the strongly constrained and appropriately normed (SCAN) meta-GGA. We further demonstrate the applicability of mTASK by assessing the band structures of transition metal dichalcogenide nanoribbons with respect to various bending curvatures.

36 MATERIALS SCIENCE↗
NASA NTRS1978

ALC/50/ values for some polymeric materials

Apparent lethal concentrations for 50 per cent of the test animals within a 30-min exposure period (ALC/50/) were determined for seventeen samples of polymeric materials, using the screening test method. The materials evaluated included resin-glass composites, film composites, and miscellaneous resins. ALC(50) values, based on weight of original sample charged, ranged from 24 to 110 mg/l. Modified phenolic resins seemed to exhibit less toxicity than the baseline epoxy resins. Among the film composites evaluated, only flame modified polyvinyl fluoride appeared to exhibit less toxicity than the baseline polyvinyl fluoride film.

Hilado, C. J.↗
DOE OSTI2020

Gapped metals as thermoelectric materials revealed by high-throughput screening

The typical strategy to design high performance thermoelectric materials is to dope a semiconducting material until optimal properties are obtained. However, some known thermoelectric materials such as La 3 Te 4 , Mo 3 Sb 7 , Yb 14 MnSb 11 , and NbCoSb are actually gapped metals,i.e., their band structure displays a gap slightly above or below the band crossed by the Fermi level. This key feature makes these metals comparable to degenerate semiconductors and thus suitable for thermoelectric applications. In this work, we perform a computational high-throughput search for such gapped metals exhibiting attractive thermoelectric properties. Several thousands of metals are found to present this key feature, and about one thousand of them show decent thermoelectric properties as evaluated by a computed zT. We present the different chemistry of gapped metals we discovered such as clathrates, Chevrel phases, or transition metal dichalcogenides and discuss their previous studies as thermoelectric and their potential as new thermoelectric materials.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Screening of High Temperature Organic Materials for Future Stirling Convertors

Along with major advancement of Stirling-based convertors, high temperature organics are needed to develop future higher temperature convertors for much improved efficiencies as well as to improve the margin of reliability for the current SOA (State-of-the-Art) convertors. The higher temperature capabilities would improve robustness of the convertors and also allow them to be used in additional missions, particularly ones that require a Venus flyby for a gravity assist. Various organic materials have been employed as essential components in the convertor for their unique properties and functions such as bonding, potting, sealing, thread locking, insulation, and lubrication. The Stirling convertor radioisotope generators have been developed for potential future space applications including Lunar/Mars surface power or a variety of spacecraft and vehicles, especially with a long mission cycle, sometimes up to 17 years, such as deep space exploration. Thus, performance, durability, and reliability of the organics should be critically evaluated in terms of every possible material structure-process-service environment relations based on the potential mission specifications. The initial efforts in screening the high temperature candidates focused on the most susceptible organics, such as adhesive, potting compound, O-ring, shrink tubing, and thread locker materials in conjunction with commercially available materials. More systematic and practical test methodologies that were developed and optimized based on the extensive organic evaluations and validations performed for various Stirling convertor types were employed to determine thermal stability, outgassing, and material compatibility of the selected organic candidates against their functional requirements. Processing and fabrication conditions and procedures were also optimized. This report presents results of the three-step candidate evaluation processes, their application limitations, and the final selection recommendations.

Screening↗