Nuclear and Space Radiation Effects on Materials - Space Vehicle Design Criteria
Effects of nuclear and space radiation on mechanical, thermal, and optical properties of spacecraft structural materials
Source record↗
SEARCH · Engineering Papers
Results for “Materials Design”
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.
Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials
Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.
36 MATERIALS SCIENCE↗
A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery
Abstract Material properties share an intrinsic relationship with their structural attributes, making inverse design approaches crucial for discovering new materials with desired functionalities. Reinforcement Learning (RL) approaches are emerging as powerful inverse design tools, often functioning in discrete action spaces. This constrains their application in materials design problems, which involve continuous search spaces. Here, we introduce an RL-based framework CASTING (Continuous Action Space Tree Search for inverse design), that employs a decision tree-based Monte Carlo Tree Search (MCTS) algorithm with continuous space adaptation through modified policies and sampling. Using representative examples like Silver (Ag) for metals, Carbon (C) for covalent systems, and multicomponent systems such as graphane, boron nitride, and complex correlated oxides, we showcase its accuracy, convergence speed, and scalability in materials discovery and design. Furthermore, with the inverse design of super-hard Carbon phases, we demonstrate CASTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.
36 MATERIALS SCIENCE↗
Thermoelectric Performance Enhancement by Surrounding Crystalline Semiconductors with Metallic Nanoparticles
Direct conversion of thermal energy to electricity by thermoelectric (TE) devices may play a key role in future energy production and utilization. However, relatively poor performance of current TE materials has slowed development of new energy conversion applications. Recent reports have shown that the dimensionless Figure of Merit, ZT, for TE devices can be increased beyond the state-of-the-art level by nanoscale structuring of materials to reduce their thermal conductivity. New morphologically designed TE materials have been fabricated at the NASA Langley Research Center, and their characterization is underway. These newly designed materials are based on semiconductor crystal grains whose surfaces are surrounded by metallic nanoparticles. The nanoscale particles are used to tailor the thermal and electrical conduction properties for TE applications by altering the phonon and electron transport pathways. A sample of bismuth telluride decorated with metallic nanoparticles showed less thermal conductivity and twice the electrical conductivity at room temperature as compared to pure Bi2Te3. Apparently, electrons cross easily between semiconductor crystal grains via the intervening metallic nanoparticle bridges, but phonons are scattered at the interfacing gaps. Hence, if the interfacing gap is larger than the mean free path of the phonon, thermal energy transmission from one grain to others is reduced. Here we describe the design and analysis of these new materials that offer substantial improvements in thermoelectric performance.
Kim, Hyun-Jung↗
Techno-economics of hydrocarbon fuel production and recyclables recovery from landfill-destined municipal solid waste: AI-enhanced materials recovery facility design
Sustainable aviation fuels (SAF) production from cellulosic paper fractions of municipal solid waste (MSW) destined for landfills has strong potential to advance environmental, social, and economic sustainability across the aviation and waste sectors. This study proposes an artificial intelligence-enabled material recovery facility (AI-MRF) design to efficiently characterize, separate, process, and convert recovered paper waste from MSW into intermediate chemicals and SAF. The AI-MRF, designed to process 233,091 metric tons of MSW annually, integrates smart manufacturing technologies including AI, visual and hyperspectral imaging, multi-sensor data, and traditional sorting systems. Well-characterized and sorted cellulosic paper waste was utilized for chemical and fuel production scenarios, while clean plastics, metals, and glass were considered for recycling. Conversion of paper waste into intermediate sugars achieved a net present value (NPV) of up to $\$67$ million. For sugar-to-SAF production scenarios, the minimum fuel selling price (MFSP) was calculated at $\$6.11$ per gasoline gallon equivalent (GGE) when excluding recyclable revenue, and $\$4.03$ per GGE when halving recyclable revenue. The MFSP was further reduced to $\$1.96$ per GGE when accounting for SAF sales and recyclables. Nationally, this approach could yield about 2 billion GGE of hydrocarbon fuel annually from available MSW in the United States.
09 BIOMASS FUELS↗
Classification and designation systems for materials: A report on the present situation, an inventory of the systems in use, and comments on the future possibilities
The different systems that are in use for the major classes of engineering materials are summarized. The work was carried out within the scope of the Versailles project on advanced materials and standards (VAMAS). An inventory of national and international standards that give specifications for the materials and international standards are included. Comments on the increasing knowledge of, and the increasing demand for, data concerning the materials performance are included. Recommendations for future activities in the standardization of classification and designation systems are given.
Reynard, Keith W.↗
Characterizing and Capturing Essential Properties of Materials for the Design of One of NASA's Large Observatories, the James Webb Space Telescope
A viewgraph presentation on the properties of materials used for the development of the James Webb Space Telescope is shown. The topics include: 1) James Webb Space Telescope (JWST) Overview; 2) Integrated Science Instrument Module (ISIM) Materials Development; and 3) Capturing Essential Data.
Polis, Daniel↗
Size effect in composite materials and structures: Basic concepts and design considerations
Composite materials display strength characteristics that are similar to those of brittle ceramics, whose strengths are known to decrease with increasing volume for a uniform state of stress (size effect) and also are dependent on stress distribution. These similarities raise the question of whether there is also a size effect in composite materials and structures. There is significant, but inconclusive experimental evidence for the existence of a size effect in composites. Macroscopic and micromechanical statistical models have been developed which predict a size effect and are in general agreement with experimental data. The existence of a significant size effect in composites would be of great importance. For example, it would mean that use of standard test coupons to establish design allowables for large structures could be very nonconservative. Further, it would be necessary to analyze the strength of large composite structures using statistical methods, as is done for ceramics.
Zweben, Carl↗
Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys
We report Bayesian Optimization (BO) has emerged as a powerful framework to efficiently explore and exploit materials design spaces. To date, most BO approaches to materials design have focused on the materials discovery problem as if it were a single expensive-to-query ‘black box’ in which the target is to optimize a single objective (i.e., material property or performance metric). Also, such approaches tend to be constraint agnostic. Here, we present a novel multi-information BO framework capable of actively learning materials design as a multiple objectives and constraints problem. We demonstrate this framework by optimally exploring a Refractory Multi-Principal-Element Alloy (MPEA) space, here specifically, the system Mo-Nb-Ti-V-W. The MPEAs are explored to optimize two density-functional theory (DFT) derived ductility indicators (Pugh’s Ratio and Cauchy pressure) while learning design constraints relevant to the manufacturing of high-temperature gas-turbine components. Alloys in the BO Pareto-front are analyzed using DFT to gain an insight into fundamental atomic and electronic underpinning for their superior performance, as evaluated within this framework.
36 MATERIALS SCIENCE↗
Absolute band-edge energies are over-emphasized in the design of photoelectrochemical materials
The absolute band-edge potentials of semiconductors, i.e., the conduction-band minimum, valence-band maximum, and their relative positions to solution redox potentials, are often invoked as design principles for photoelectrochemical (PEC) devices, especially for particulate photocatalysts. Here we show that reliance on these criteria is not necessary and limits the exploration of materials that will advance the fields of photoelectrochemistry, photochemistry, and photocatalysis. We discuss how i) band-edge energies are not singular parameters and instead shift with pH, electrolyte type, and surface chemistry; ii) the free energy of electrons and holes in comparison to that of solution redox couples dictates overall reaction spontaneity and thus reactivity; and iii) favorable charge-transfer kinetics can occur even when the relevant electrolyte redox potential(s) appear ‘outside’ the bandgap, enabled by the inversion or accumulation of electronic charge at the semiconductor surface. As a result, this discussion informs design principles for photocatalyst systems engineering for both one-electron redox reactions as well as for more complex multi-electron transfer reactions (e.g, H 2 evolution, H 2 O oxidation, CO 2 reduction).
14 SOLAR ENERGY↗
Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials
Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Redox-Based Chemical Looping Large-Scale Air Separation Unit Designs Using Perovskite Material
Oxygen production by means of air separation through redox cycle reactions of Sr 1–x Ca x FeO 3-δ perovskite particles is examined numerically in the context of modular large-scale units. Fixed-bed, multicomponent reactor designs allowing for the recovery of the energy released by the exothermic oxidation (or adsorption) to enhance the endothermic reduction (or desorption) of the perovskite material are considered and compared against a baseline cylindrical packed bed. Numerically, the gas–solid reacting system is approximated as a single-phase reacting gas flow through a porous medium of constant porosity. The redox kinetics account for the oxygen nonstoichiometry of the perovskite, which exhibits a dependence on the temperature and the oxygen partial pressure, in order to describe some mechanisms of the oxygen vacancies. Results show that the spontaneous release of the oxygen from the lattice arrangements, through the thermal management of the heat of the oxidation reaction from the geometrical design of the reactors, can be enhanced up to 4% with respect to the baseline oxygen production of 0.201 g O 2 ·h –1 ·g perovskite –1 with the cylindrical packed bed, in the condition of operations in this work, at 500 °C. Sensitivity to the operation temperature showed that the oxygen production is greatly enhanced by approximately 30% with the increase of the temperature from 500 to 550 °C. We report this result is consistent with experimental observations of faster release of the oxygen from the lattice arrangements of this perovskite at 550 °C.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Handbook of the optical, thermal and mechanical properties of six polycrystalline dielectric materials
The design data for six polycrystalline dielectric materials are presented to describe the optical, thermal, and mechanical properties. The materials are aluminum oxide, calcium fluoride, magnesium fluoride, magnesium oxide, silicon dioxide, and titanium dioxide. The primary interest is in the polycrystalline state, although single crystal data are included when appropriate. The temperature range is room temperature to melting point. The wavelength range is from near ultraviolet to near infrared.
Dewitt, D. P.↗
Transformer design tradeoffs
Material was presented to assist transformer designers in the transition from long-used English units to the less familiar metric equivalents. A coordination between the area product numbers ap (product of window and core cross-section areas) and current density J was developed for a given regulation and temperature rise. Straight-line relationships for Ap and Volume, Ap and surface area At and, Ap and weight were developed. These relationships can now be used as new tools to simplify and standardize the process of transformer design. They also made it possible to design transformers of small bulk and volume or to optimize efficiency.
Mclyman, W. T.↗
Design of the materials experiment carrier for on-orbit servicing
This paper discussed the MEC system and its mission from the viewpoint of orbit servicing. Information is provided on MEC system requirements, design for on orbit servicing, on orbit servicing operations and rationale and servicing costs.
Waltz, D. M.↗
CubeSat Material Limits For Design for Demise
The CubeSat form factor of nano‐satellite (a satellite with a mass between one and ten kilograms) has grown in popularity due to their ease of construction and low development and launch costs. In particular, their use as student led payload design projects has increased due to the growing number of launch opportunities. CubeSats are often deployed as secondary or tertiary payloads on most US launch vehicles or they may be deployed from the ISS. The focus of this study will be on CubeSats launched from the ISS. From a space safety standpoint, the development and deployment processes for CubeSats differ significantly from that of most satellites. For large satellites, extensive design reviews and documentation are completed, including assessing requirements associated with reentry survivability. Typical CubeSat missions selected for ISS deployment have a less rigorous review process that may not evaluate aspects beyond overall design feasibility. CubeSat design teams often do not have the resources to ensure their design is compliant with reentry risk requirements. A study was conducted to examine methods to easily identify the maximum amount of a given material that can be used in the construction of a CubeSats without posing harm to persons on the ground. The results demonstrate that there is not a general equation or relationship that can be used for all materials; instead a limiting value must be defined for each unique material. In addition, the specific limits found for a number of generic materials that have been previously used as benchmarking materials for reentry survivability analysis tool comparison will be discussed.
Kelley, R. L.↗
Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model
Abstract The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.
36 MATERIALS SCIENCE↗