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At least 1,117 records · Page 62

Harnessing biological applications of quantum materials: opportunities and precautions

Since the discovery of graphene, research on two-dimensional (2D) quantum materials has generated a plethora of novel materials with the potential to significantly change our lives. Owing to their unique quantum, electronic, and excitonic properties, biosensing and bio-imaging are two specific areas where these quantum materials have started to make a large impact. This article provides a holistic overview into the properties, synthesis methods, biological applications, and toxicology studies of commonly studied quantum materials. Recent research into the biological applications of graphene and transition metal dichalcogenides is highlighted and their unique electronic properties are explored. Though tremendous research is generated in discovering new 2D materials, toxicology studies in the area are lacking. Historically, toxicology studies have lagged significantly behind new material discovery often with dire consequences. The product development cycle of polymeric materials is a testament to the negative consequences of having a reactionary approach to toxicology. With 2D materials set to become a widespread part of everyday life in the near future, we comment on the need for a proactive approach to examining and understanding their toxicology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials and Processes for New Propulsion Systems with Reduced Environmental Impact

Aeronautics research at NASA Glenn Research Center includes development, characterization and modeling of high temperature, lightweight materials and fabrication processes for aircraft propulsion systems with increased efficiency and reduced emissions, fuel burn and noise. Current propulsion materials research includes Ceramic Matrix Composites and Environmental Barrier Coatings, Polymer Matrix Composites and Additive Manufacturing processes. This presentation will summarize recent progress and plans in these areas. Ceramic Matrix Composites for Turbine Components: As part of NASA's Aeronautics research, Glenn Research Center has developed Ceramic Matrix Composites for 2700 degrees Fahrenheit turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of advanced fiber and matrix constituents that enabled this advancement will be reviewed, and characterization of the resulting improvements in mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Progress and plans for collaborative research with industry and other government agencies will be reviewed. Polymer Matrix Composites for Powertrain and Impact Protection: A lightweight, hybrid polymer matrix composite/steel gear concept for rotorcraft power transmission applications was evaluated at realistic speed, torque, and power conditions. Dynamic testing was performed at 5000 horsepower and 5400 revolutions per minute with no performance degradation. Test results demonstrated the potential of hybrid composite / metal gears to reduce gear weight by approximately 15 percent, enabling the implementation of multi-speed drive systems, which would otherwise have a weight penalty, for increased speed and efficiency. Results of post-test inspection and endurance tests will be presented. Separately, ballistic impact tests demonstrated improved damage tolerance in polymer matrix composites by incorporating lightweight, thermoplastic veil materials between selected composite plies during the composite fabrication process. Results of impact tests and post-test inspection will be presented. Additive Manufacturing for Electric Propulsion: Additive Manufacturing processes offer the potential to fabricate new, high power density electric motor designs with complex geometries, multi-material components and optimally designed components that would not be feasible with traditional manufacturing processes. High performance stator components using advanced 3-phase conductive coils were fabricated using direct printing with optimized silver pastes. Additional additive manufacturing methods are being used to fabricate rotors and motor housing components. Systems studies show that the higher performance and lower weight motors offer improved energy efficiency and reduced emissions. Improvements to motor performance resulting from optimized materials and component designs will be presented.

Additive Manufacturing↗

Adhesive evaluation of LARC-TPI and a water-soluble version of LARC-TPI

The results of a study to evaluate two Langley Research Center thermoplastic polimide (TPI) materials, identified as TPI/MTC for the material from Mitsui Toatsu Chemicals Inc. and TPI/H2O for the material from United Technologies Research Center, as high temperature thermoplastic adhesives and primers for bonding titanium (6AL-4V) adherends are discussed. A limited characterization of the materials was performed using a Diffuse Reflectance-Fourier Transform Infrared Spectroscopy (DR-FTIR) technique. Thermomechanical Analysis (TMA) and torsional braid techniques were used to determine glass transition temperature. The adhesive's strength, as determined by simple lap shear tests, as used to evaluate the effects of long term thermal exposure (up to 1000 hrs) at 204 deg C and a 72-hour water-boil.

Progar, D. J.↗

Adhesive evaluation of LARC-TPI and a water-soluble version of LARC-TPI

The results of a study to evaluate two Langley Research Center thermoplastic polimide (TPI) materials, identified as TPI/MTC for the material from Mitsui Toatsu Chemicals Inc. and TPI/H2O for the material from United Technologies Research Center, as high temperature thermoplastic adhesives and primers for bonding titanium (6AL-4V) adherends are discussed. A limited characterization of the materials was performed using a Diffuse Reflectance-Fourier Transform Infrared Spectroscopy (DR-FTIR) technique. Thermomechanical Analysis (TMA) and torsional braid techniques were used to determine glass transition temperature. The adhesive's strength, as determined by simple lap shear tests, was used to evaluate the effects of long term thermal exposure (up to 1000 hrs) at 204 deg C and a 72-hour water-boil.

Progar, D. J.↗

New directions in lubrication, materials, wear, and surface interactions - Tribology in the 80's

New directions in tribology are described. A range of topics is addressed, extending from fundamental research on tribological materials of all kinds and their surface effects, to final technological applications in mechanical components such as bearings, gears, and seals. The general topics addressed include: importance and definition of materials in tribology; future directions of research in adhesion and friction, wear and wear-resistant materials, and liquid lubricants and additives; status and new directions in elastohydrodynamic lubrication and solid lubricants; and tribological materials for mechanical components of the future.

Loomis, W. R.↗

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Lastly, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

36 MATERIALS SCIENCE↗

FAIRLinked: Data FAIRification Tools for Materials Data Science

FAIRLinked is a software package created to support the FAIRification of materials science data, ensuring proper alignment with FAIR principles: Findable, Accessible, Interoperable, and Reusable. It is built to be compatible with MDS-Onto, an ontology designed to capture the semantics of various types of materials data, enabling integration and sharing across different research workflows. The package is subdivided into three subpackages: InterfaceMDS, RDFTableConversion, and QBWorkflow. The first subpackage, InterfaceMDS allows users to search for terms using either string search or various filters, explore different domains and subdomains, and add terms to MDS-Onto. RDFTableConversion is used for serialization and deserialization of data from CSV into JSONLDs and vice versa in a way that captures the semantics of the data using MDS-Onto. Lastly, QBWorkflow is a serialization and deserialization workflow that incorporates RDF Data Cube vocabulary, useful for working with multidimensional datasets. By offering these packages, FAIRLinked lowers the barrier of creating FAIR, machine-actionable data for researchers in the materials science community.

FAIR↗

Deep Learning the Electromagnetic Properties of Metamaterials—A Comprehensive Review

Deep neural networks (DNNs) are empirically derived systems that have transformed traditional research methods, and are driving scientific discovery. Here, artificial electromagnetic materials (AEMs)—including electromagnetic metamaterials, photonic crystals, and plasmonics—are research fields where DNN results valorize the data driven approach; especially in cases where conventional methods have failed. In view of the great potential of deep learning for the future of artificial electromagnetic materials research, the status of the field with a focus on recent advances, key limitations, and future directions is reviewed. Strategies, guidance, evaluation, and limits of using deep networks for both forward and inverse AEM problems are presented.

14 SOLAR ENERGY↗

Polymer Aerogels for Lunar Applications and Beyond

As the Space Community endeavors to reach new heights of exploration, materials for extreme environment are on the forefront of research. One such material would include polymer aerogels; lightweight solids with nano-scale pore size, high internal surface area, low thermal conductivity, and extremely high porosities. Due to these interesting properties, aerogels are ideal as thermal insulators but are by no means limited to this application. The high porosity and surface area also make aerogels an ideal host system for particle incorporation for applications such as catalyst supports, sensor platforms, and vibro-acoustic mitigating materials. Polymer aerogels also have the potential to combat issues found in extraterrestrial environments such as dust and radiation mitigation. Herein, current research will be discussed as it pertains to Space exploration.

Stephanie Vivod↗

Large space structures - Structural concepts and materials

Large space structures will be a key element of future space activities. They will include spacecraft such as the planned Space Station and large antenna/reflector structures for communications and observations. These large structures will exceed 100 m in length or 30 m in diameter. This paper provides an overview of research in the space construction of large structures including erectable and deployable concepts. Also, an approach to automated, on-orbit construction is presented. Materials research for space applications focuses on high stiffness, low expansion composite materials that provide adequate durability in the space environment. The status of these materials research activities is discussed.

Blankenship, Charles P.↗

A framework for materials informatics education through workshops

The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curricula, regular hands-on workshops present the most effective medium to initiate researchers to informatics and have them start applying the best AI/ML tools to their own research. With the help of the Materials Research Society (MRS), members of the MRS AI Staging Committee, and a dedicated team of instructors, we successfully conducted workshops covering the essential concepts of AI/ML as applied to materials data, at both the Spring and Fall Meetings in 2022, with plans to make this a regular feature in future meetings. Here, in this article, we discuss the importance of materials informatics education via the lens of these workshops, including details such as learning and implementing specific algorithms, the crucial nuts and bolts of ML, and using competitions to increase interest and participation.

36 MATERIALS SCIENCE↗

Hybrid Metal Halides: Advancing Optoelectronic Materials (Final Technical Report)

Hybrid metal halides, particularly main group halide perovskites, are a unique class of materials that offer exceptional optoelectronic properties along with a remarkable materials design space. Initial research on this class of materials was driven by the ability of the prototype hybrid 3D perovskite-structured compound methylammonium lead iodide to function as the active layer in thin film solar cells. It is now known that this class of materials comprise a large family with tunable band gaps, relatively high charge carrier mobilities in both single crystal and polycrystalline forms, and relatively low concentrations of (deleterious) electrically active states within the band gap. Beyond applications in solar cells, the potential of these materials has been extended to emitters in light emitting diodes, and active components of radiation detectors. Complementing new functionality, the design space for hybrid metal halides continues to increase with discovery of new structural motifs. In this project, the combination of organic and inorganic functionalities has been employed to open pathways to the design and synthesis new, functional hybrid metal halides. Beyond the simple perovskites, Ruddlesden-Popper and Dion-Jacobsen compounds, and other variants, such as the newly advanced “hollow” perovskites have been studied. The materials have provided routes to understanding the unique electronic properties of hybrid metal halides because of their natural quantum well structures as well as other means of controlling band gaps and band dispersions. Understanding these materials, including the design rules for their formation, their structures and compositions in bulk and in thin films form, and the role of local (non-crystallographic) structure has an important aspect of this endeavor. The goal of advancing new materials and new fundamental understanding within this deceptively simple, yet fascinating class of compounds, so richly endowed with interesting and useful functionality, has been fulfilled.

36 MATERIALS SCIENCE↗

CFD validation experiments for internal flows

Computational Fluid Dynamics (CFD) validation experiments at NASA Lewis Research Center are described. The material presented summarizes the research in three areas: Inlets, Ducts and Nozzles; Turbomachinery; and Chemically Reacting Flows. The specific validation activities are concerned with shock-boundary layer interactions, vortex generator effects, large low speed centrifugal compressor measurements, transonic fan shock structure, rotor/stator kinetic energy distributions, stator wake shedding characteristics, boundary layer transition, multiphase flow and reacting shear layers. These experiments are intended to provide CFD validation data for the internal flow fields within aerospace propulsion system components.

Povinelli, Louis A.↗

An overview of the measurements of thermophysical properties and some results on molten superalloys and semiconductors

This presentation consists of two parts: comments on the results of measurements on thermophysical properties based on the paper, 'Things Mother Never Taught Me (About Thermophysical Properties of Solids)' and results of thermophysical property measurements on selected solid and molten semiconductors and a proprietary superalloy. The first part may be considered as a tutorial for those involved in using or procuring thermophysical property data. The second part is presented as illustrations of what has been accomplished on molten materials at the Thermophysical Properties Research Laboratory (TPRL). The materials include Ge, PbTe, PbSnTe, HgCdTe and a superalloy.

Taylor, R. E.↗

Design and Control of a Proof-of-Concept Active Jet Engine Intake Using Shape Memory Alloy Actuators

The design and control of a novel proof-of-concept active jet engine intake using Nickel-Titanium (Ni-Ti or Nitinol) shape memory alloy (SMA) wire actuators is used to demonstrate the potential of an adaptive intake to improve the fuel efficiency of a jet engine. The Nitinol SMA material is selected for this research due to the material's ability to generate large strains of up to 5 percent for repeated operations, a high power-to-weight ratio, electrical resistive actuation, and easy fabrication into a variety of shapes. The proof-of-concept engine intake employs an overlapping leaf design arranged in a concentric configuration. Each leaf is mounted on a supporting bar that rotates upon actuation by SMA wires electrical resistive heating. Feedback control is enabled through the use of a laser range sensor to detect the movement of a leaf and determine the radius of the intake area. Due to the hysteresis behavior inherent in SMAs, a nonlinear robust controller is used to direct the SMA wire actuation. The controller design utilizes the sliding-mode approach to compensate for the nonlinearities associated with the SMA actuator. Feedback control experiments conducted on a fabricated proof-of-concept model have demonstrated the capability to precisely control the intake area and achieve up to a 25 percent reduction in intake area. The experiments demonstrate the feasibility of engine intake area control using the proposed design.

Song, Gangbing↗

CMC Research at NASA Glenn in 2015: Recent Progress and Plans

An overview of recent research in Ceramic Matrix Composite materials at NASA Glenn Research Center. For presentation at the July 16, 2015 GRC Dialogue Day with Ohio Academia, as part of the establishment of the Ohio Federal Research Network.

Ceramics and Composites↗

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗