Identification of volatile contaminants of space cabin materials Final report, Jan. 1967 - Feb. 1968
Screening tests on candidate construction materials for spacecraft cabins to determine gas-off and oxidation products
Hodgson, F. N.↗
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
SynthEsizing Novel H2 Sensors for Operational Resilience in Pipeline Infrastructure (SENSOR)
A flexible and extensible computational framework acts as a black-box materials discovery engine, capable of screening, predicting, and designing advanced materials with minimal manual intervention was developed. While developed for hydrogen sensing, the approach can be readily adapted to other materials challenges, offering a powerful tool for data-driven materials innovation.
08 HYDROGEN↗
Techniques used for limiting degradation products of polymeric materials for use in the space environment
Techniques are discussed for limiting or controlling the degradation products (outgassing) of polymeric materials in the space environment. One technique, now ASTM E-595-77, is used to screen out those materials which lose greater than 1% Total Mass Loss when in vacuum for 24 hours at 125 C and which have more than 0.10% Collected Volatile Condensable Materials condensing on a collector surface at 25 C. Examples of silicone materials which are high and low in outgassing are given. The numerous mechanical motions in spacecraft experiments require liquid lubricants which also might degrade in space. Labyrinth seals and barrier films are utilized to limit the degradation of or from these lubricants. A recoverable in-flight experiment has been proposed for making definitive measurements of how effective these techniques are in limiting the amounts and escape paths of outgassed molecules.
Vest, C. E.↗
DMA Modulus as a Screening Parameter for Compatibility of Polymeric Containment Materials with Various Solutions for use in Space Shuttle Microgravity Protein Crystal Growth (PCG) Experiments
Protein crystals are grown in microgravity experiments inside the Space Shuttle during orbit. Such crystals are basically grown in a five-component system containing a salt, buffer, polymer, organic and water. During these experiments, a number of different polymeric containment materials must be compatible with up to hundreds of different PCG solutions in various concentrations for durations up to 180 days. When such compatibility experiments are performed at NASA/MSFC (Marshall Space Flight Center) simultaneously on containment material samples immersed in various solutions in vials, the samples are rather small out of necessity. DMA4 modulus was often used as the primary screening parameter for such small samples as a pass/fail criterion for incompatibility issues. In particular, the TA Instruments DMA 2980 film tension clamp was used to test rubber O-rings as small in I.D. as 0.091 in. by cutting through the cross-section at one place, then clamping the stretched linear cord stock at each end. The film tension clamp was also used to successfully test short length samples of medical/surgical grade tubing with an O.D. of 0.125 in.
Wingard, Charles Doug↗
Scintillators
As concerns about the illicit movement of radioactive materials across international borders increase, so too has the need for increased protection of those borders both foreign and domestic. The challenge is not only to detect hidden radioactive materials, but also to distinguish them from legitimate radionuclides such as radio-pharmaceuticals that are often transported across borders and shipped throughout a country. With more than 600 U.S. border sites to protect, screening imported radioactive material requires a careful balance of high throughput and high search efficiency. However, these requirements are difficult to meet as rapid screening operations leave less time for radiation detectors to efficiently evaluate materials. In support of border security, Sandia developed organic glass scintillators.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Relative toxicity of pyrolysis products of some materials used in home furnishings
Seventy samples of cushioning and upholstery materials used in home furnishings were evaluated for relative toxicity by means of the USF/NASA toxicity screening test. The materials were variably toxic under pyrolysis conditions, and this test appeared suitable for discriminating among them on the bases of time to incapacitation and time to death. The addition of fire retardants to these materials to comply with flammability regulations either had no significant effect on toxicity, or resulted in a reduction in relative toxicity. The modification of materials to comply with California upholstered furniture flammability regulations appears to have resulted in desirable limitations on toxicity. Fifty percent of the 70 materials tested caused incapacitation earlier than did the materials in compliance, and 30 percent caused death earlier.
Hilado, C. J.↗
Altering Linear Scaling Relationships on Metal Catalysts via Ligand–Adsorbate Hydrogen Bonding
Linear scaling relationships for adsorption energies of related molecules provide a simple tool for the prediction of catalytic properties and also reveal inherent constraints in heterogeneous catalyst design. In an effort to predict materials that preferentially stabilize intermediates capable of forming hydrogen bonds (H-bonds) and thus reduce these constraints, scaling relations for thiolate-coated fcc (111) surfaces were developed. Here, we demonstrate how ligand–adsorbate H-bonds lead to the stabilization of certain adsorbates and how this affects the linear scaling of adsorption energies for similarly bound intermediates. For H-bonds that occur remote from the surface, ligand–adsorbate H-bond strength is independent of metal composition and instead depends only on the acidities of the H-bond-forming functional groups. As the distance of H-bond-accepting groups from the surface decreases and interactions with the metal strengthen, the effect of surface composition on H-bond strength increases while additional factors, such as conformational changes and steric hinderance, can offset the stabilizing effect of the ligands. In this work, these competing factors may influence both the slope and y-intercept of adsorption strength scaling. These findings aid the rational design of enhanced catalytic materials by enabling the screening of ligand- or spectator-modified materials that do not conform to the linear scaling relations of bare metal surfaces.
36 MATERIALS SCIENCE↗
Perspective on Solar Energy Materials, Design and Discovery, Defects, Disorder, and Interfaces
The energy transition still faces a daunting math. Currently, more than three quarters of final energy consumption occurs in form of fuels vs less than one quarter in electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, meeting the terawatt challenge requires enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies, for example via solar thermochemical routes. In this presentation, we will review successes and challenges in photovoltaic materials from silicon to CdTe to halide perovskites and potential emerging materials, with a particular perspective on the role of first principles calculations and predictions. Materials design and discovery is evolving to incorporate defects, disorder, and interfaces. These phenomena play also an important role in the thermochemical generation of hydrogen, allowing to utilize synergies between renewable electricity and fuels in computational research. At the same time, machine learning approaches are increasingly geared toward properties of non-ideal materials, for example defect formation, allowing the screening for more complex material behavior as needed for the respective applications.
fuels↗
Excitonic effects in absorption spectra of carbon dioxide reduction photocatalysts
Abstract The formation and disassociation of excitons play a crucial role in any photovoltaic or photocatalytic application. However, excitonic effects are seldom considered in materials discovery studies due to the monumental computational cost associated with the examination of these properties. Here, we study the excitonic properties of nearly 50 photocatalysts using state-of-the-art Bethe–Salpeter formalism. These ~50 materials were recently recognized as promising photocatalysts for CO 2 reduction through a data-driven screening of 68,860 materials. Here, we propose three screening criteria based on the optical properties of these materials, taking excitonic effects into account, to further down select six materials. Furthermore, we study the correlation between the exciton binding energies obtained from the Bethe–Salpeter formalism and those obtained from the computationally much less-expensive Wannier–Mott model for these chemically diverse ~50 materials. This work presents a paradigm towards the inclusion of excitonic effects in future materials discovery for solar-energy harvesting applications.
36 MATERIALS SCIENCE↗
Evaluation of nonmetallic thermal protection materials for the manned space shuttle. Volume 1, task 1: Assessment of technical risks associated with utilization of nonmetallic thermal protection system
Technical problems of design and flight qualification of the proposed classes of surface insulation materials and leading edge materials were reviewed. A screening test plan, a preliminary design data test plan and a design data test plan were outlined. This program defined the apparent critical differences between the surface insulators and the leading edge materials, structuring specialized screening test plans for each of these two classes of materials. Unique testing techniques were shown to be important in evaluating the structural interaction aspects of the surface insulators and a separate task was defined to validate the test plan. In addition, a compilation was made of available information on proposed material (including metallic TPS), previous shuttle programs, pertinent test procedures, and other national programs of merit. This material was collected and summarized in an informally structured workbook.
Wilkinson, W. H.↗
Computational Materials Research
High temperature thermoplastic polyimide polymers are incorporated in engineering structures in the form of matrix materials in advanced fiber composites and adhesives in bonded joints. Developing analytical tools to predict long term performance and screen for final materials selection for polymers is the impetus for intensive studies at NASA and major industry based airframe developers. These fiber-reinforced polymeric composites (FRPCs) combine high strength with lightweight. In addition, they offer corrosion and fatigue resistance, a reduction in parts count, and new possibilities for control through aeroelastic tailoring and "smart" structures containing fully-integrated sensors and actuators. However, large-scale acceptance and use of polymer composites has historically been extremely slow. Reasons for this include a lack of familiarity of designers with the materials; the need for new tooling and new inspection and repair infrastructures; and high raw materials and fabrication costs.
Veazie, David R.↗
Many-body physics and machine learning enabled discovery of promising solar materials
Starting from a diverse dataset of 350+ GW-BSE computed quasiparticle gaps and exciton binding energies, a machine learning model is trained and then used to screen through 7K+ materials to identify 396 with excellent solar applications.
Biswas, Tathagata [Department of Physics, Arizona ↗
Data mining and computational screening of Rashba-Dresselhaus splitting and optoelectronic properties in two-dimensional perovskite materials
Recent developments highlighting the promise of two-dimensional perovskites have vastly increased the compositional search space in the perovskite family. This presents a great opportunity for the realization of highly performant devices and practical challenges associated with the identification of candidate materials. High-fidelity computational screening offers great value in this regard. In this study, we carry out a multiscale computational workflow, generating a dataset of two-dimensional perovskites in the Dion-Jacobson and Ruddlesden-Popper phases. Our dataset comprises ten B-site cations, four halogens, and over 20 organic cations across over 2000 materials. We compute electronic properties, thermoelectric performance, and numerous geometric characteristics. Furthermore, we introduce a framework for the high-throughput computation of Rashba-Dresselhaus splitting. Finally, we use this dataset to train machine learning models for the accurate prediction of band gaps, candidate Rashba-Dresselhaus materials, and partial charges. The work presented herein can aid future investigations of two-dimensional perovskites with targeted applications in mind.
14 SOLAR ENERGY↗
Electron-phonon coupling strength from ab initio frozen-phonon approach
In this work, we propose a fast method for high-throughput screening of potential superconducting materials. The method is based on calculating metallic screening of zone-center phonon modes, which provides an accurate estimate for the electron-phonon coupling strength. This method is complementary to the recently proposed Rigid Muffin Tin (RMT) method, which amounts to integrating the electronphonon coupling over the entire Brillouin zone (as opposed to the zone center), but in a relatively inferior approximation. We illustrate the use of this method by applying it to MgB 2 , where the high-temperature superconductivity is known to be driven largely by the zone-center modes, and compare it to a sister compound AlB 2 . We further illustrate the usage of this descriptor by screening a large number of binary hydrides, for which accurate first-principle calculations of electron-phonon coupling have been recently published. Together with the RMT descriptor, this method opens a way to perform initial high-throughput screening in search of conventional superconductors via machine learning or data mining.
36 MATERIALS SCIENCE↗
Machine Learning Screening of Metal-Ion Battery Electrode Materials
Here, in this work we present deep neural network regression machine learning models (ML) for predicting the average voltage and the percentage change in volume of battery electrodes upon charging and discharging with metal ions. Our models exhibit good performance as measured by the average mean absolute error obtained from a 10-fold cross-validation as well as on independent test sets. We further assess the robustness our ML models by investigating their screening potential beyond the training database. We produce novel Na-ion electrodes by systematically replacing Li-ions in the original database by Na-ions, and then selecting a set of 22 electrodes that exhibit a good performance in energy density as well as small volume variations upon charging and discharging, as predicted by the machine learning model. The ML predictions for these new materials are then compared to quantum-mechanics based calculations. Our results reaffirm the significant role of machine learning techniques in the exploration of materials for battery applications.
,electrode volume change↗
Flash fire propensity of materials
Flash fire test results on 86 materials, evaluated using the USF flash fire screening test, are presented. The materials which appear least prone to flash fires are PVC, polyphenylene oxide and sulfide, and polyether and polyaryl sulfone; these did not produce flash fires under these particular test conditions. The principal value of these screening tests at the present time is in identifying materials which appear prone to flash fires, and in identifying which formulations of a generic material are more or less prone to flash fires.
Hilado, C. J.↗
High contrast cathode ray tube
A layer of material is described, which contains fine grains of phosphor material stimulated by electrons to produce visible radiation. The layer, which also contains fine grains of cobalt oxide, is deposited on the glass screen of a cathode ray tube to provide high contrast, by absorbing most of the visible radiation which is directed to the layer through the screen, while not materially affecting the visible light which the phosphor material produces in response to the electron stimulation.
Lisovicz, E. J.↗
Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals
Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗