An Open‐Source Multifunctional Testing Platform for Optical Phase Change Materials
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Cosmin-Constantin Popescu↗
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Results for “Platform materials”
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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Metamaterials as a Platform for the Development of Novel Materials for Energy Applications
To explore the fundamental properties of metamaterials (MMs) / metasurfaces and their potential for control of energy at the sub‐wavelength scale in support of the mission of the Department of Energy and the office of Basic Energy Sciences. Electromagnetic metamaterials provide a platform for the discovery and design of new materials with novel structures, functions, and properties. The PI proposes to advance the knowledge base of these materials through fundamental investigations of the experimental and theoretical properties of metamaterials for the discovery, prediction and design of new materials with novel structures, functions, and properties. The proposed research activities emphasize a complete basic research program including the conceptual / computational design, fabrication / synthesis of the materials, and the characterization and analysis of their electromagnetic properties. The proposed project explores the fundamental properties of metamaterials / metasurfaces and their potential for energy applications. There are three main topics which will be investigated: 1) Dispersion engineering with metamaterials and metasurfaces, 2) Epsilon near zero metamaterial absorbers and emitters, and 3) All dielectric metamaterials. The program implements a complete basic research program consisting of theory / design, modeling, characterization, and analysis, in order to fully characterize metamaterials and metasurfaces, while at the same time minimizing iterations necessary to achieve the proposal goals.
36 MATERIALS SCIENCE↗
Mixed Enthalpy–Entropy Descriptor for the Rational Design of Synthesizable High-Entropy Materials Over Vast Chemical Spaces
The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional material design and discovery. However, the identification of stable and synthesizable HEMs and robust design rules remains a daunting challenge. Here, we propose a mixed enthalpy–entropy descriptor (MEED) that enables highly efficient, robust, high-throughput prediction of synthesizable HEMs across vast chemical spaces from first-principles. The MEED is based on two parameters: the relative formation enthalpy with respect to the most stable competing compound and the spread of the point-defect formation energy spectrum. The former measures the relative synthesizability of an HEM to its most stable competing phase, going beyond the conventional thermodynamic understanding. Further, the latter gauges the relative entropy forming ability of an HEM, entailing no sampling over numerous alloy configurations. By applying the MEED to two structurally distinct representative material systems (i.e., 3D rocksalt carbides and 2D layered sulfides), we not only successfully identify all experimentally reported HEMs within these systems but also reveal a cutoff criterion for assessing their relative synthesizability within each system. By the MEED, tens of new high-entropy carbides and 2D high-entropy sulfides are also predicted, which have the potential for a wide variety of applications such as coating in aerospace devices, energy conversion and storage, and flexible electronics.
36 MATERIALS SCIENCE↗
Development of the Intelligent, Preventive Infrared (IR) Inspection System Housed in Hybrid Robotic Platforms
Robots and robotic systems that are designed for inspection, environmental study, and health and safety aid are becoming an increasing necessity. However, there is a number of challenges that accompany robots that are designed for these specific applications. These challenges include: navigating compact, enclosed spaces, travelling over multiple terrains and large obstacles, using the proper sensing and detection methods to assess an environment, and the use of lightweight and durable materials. The robotic platforms currently in development look at all of these challenges and attempt to overcome them. These designs specific use of hybrid robotic platforms, or platform that utilizes soft and rigid materials, allows for a more flexible platform and makes environments more navigable. To further improve the navigation of the platforms and environmental assessment, a novel infrared detection system is housed in the platforms to create a robot that can be used for the applications listed above and more. Objectives: Further develop two types of robotic platforms that utilize additive manufacturing, soft materials, and rigid materials. Continue the development of an intelligent and inhibitory infrared detection system based on an artificial intelligence (AI) algorithm. Continued study and fabrication of active soft materials designed for both sensing and actuation in hybrid robotic systems. Improve additive manufacturing fabrication to design rigid and semi-rigid components for hybrid robotic platforms. Transformable Wheel Robotic Platform: The chassis, wheels, tires and inspection system housing use different additive manufacturing techniques for fabrication. Continued work with additive manufacturing has lead to studies in metal-based printing and modular design and manufacturing. The new platform design with integrated electrical component printed. This will allow integration of the sensor housing onto the platform. Electrical components are being tested for battery life and performance. To improve this performance, such as integration of Lithium Polymer (LiPo) batteries. Snake Robotic Platform: The main focus of the development has centered around liquid-based soft actuators. That act on the principles of electrostatic and hydraulic actuation. A liquid dielectric sits between two compliant electrodes, contained by a flexible polymer shell. The electrodes and film gradually collapse toward each other from one corner of the electrode to the other. When the electrodes and film close together, a majority of the fluid is pushed into the area not covered by an electrode. A thin layer of the liquid dielectric remains between the electrode. The actuators will be stacked to cause large displacement, and move the linkages. The chassis of this platform uses purely additively manufactured linkages. Intelligent, Preventive IR Inspection System: Development of the AI for the system has lead to using a Scikit-Learn which assists in creating predictive models based on Regression, clustering, classification etc. To improve the infrared thermometry for low emissivity sources, work on the fabrication of a tandem photoconductive infrared thermometer was a main focus. Distance-Voltage-Temperature response data has been collected in the range of 7 cm - 100 cm and 200-400 deg. C. Modifications were made to the existing test bench to have a better control over the data. Automated data collection was realized using a Python code and an Arduino controlled stepper motor to increase the sample rate. A protective enclosure has been built around the setup to minimize the effect of the environment on the measurements. To better predict temperature, different AI models are being optimized. The regression model, LARS showed a high accuracy but had convergence issues and only works for the current test set-up. Results: The Transformable Wheel Robot has developed into a more flexible and modular platform. With the improvements to the current work, effort on the tire or soft gripper design been a large focus. The soft grippers will be interchange able to allow for increased performance in identified terrain types. The development of the liquid-based actuators allows the snake robotic platform to achieve the goals of being flexible and able to navigate confined spaces. However, there is room for improvement. Optimization work is currently being done in COMSOL Multiphysics. With the current IR system set-up the LARS model perfectly predicts the data; however, considering the mobility aspect of the project other models will allow for an optimized system. Testing of other model types is currently being done.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Science Driven Discovery of Nanoparticle Photocatalysts
Photocatalytic water splitting using suspensions of nanoparticle photocatalysts is a promising route to economically sustainable production of green hydrogen. The principal challenge is to develop photocatalysts with overall solar-to-hydrogen conversion efficiency that exceeds 10 percent. In this project we have developed a new platform for investigating candidate materials for photocatalytic water splitting. Our platform consists of patterned Au electrodes and a Ag/AgCl reference electrode on an insulating substrate onto which we disperse nanoparticle photocatalysts. We then cover the substrate with a thin layer of ionogel containing a protic ionic liquid that dissolves water from the ambient. Using this platform we have demonstrated photoelectrochemical activity mapping for single and small clusters of BiVO 4 nanoparticle photocatalysts and correlated these results to their Raman and photoluminescence spectra. The preliminary results suggest a strong correlation for low efficiency nanoparticles, followed by saturation for those with higher activities, indicating that interface reaction or electrolyte transport become the limiting factor. We anticipate that further application of this platform to investigation of candidate photocatalyst materials will provide useful insights into the mechanisms that limit their performance.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Oxide-nitride heteroepitaxy for low-loss dielectrics in superconducting quantum circuits
Superconducting qubits show great promise for the realization of fault-tolerant quantum computing, but lossy, amorphous dielectrics limit current technology. Identifying highly crystalline and stoichiometric dielectrics with intrinsically low microwave loss is therefore a central materials challenge, yet experimentally validated platforms remain scarce. In this work, we integrate a crystalline dielectric into a heteroepitaxial TiN/$γ$-Al$_2$O$_3$/TiN trilayer grown via pulsed laser deposition. Correlative high-resolution imaging, diffraction, and spectroscopy measurements confirm the single-crystal quality and chemical integrity of all layers, with minimal defects and limited anion interdiffusion across the oxide-nitride interfaces. Using microwave lumped-element resonators with parallel-plate capacitors, we report the first direct measurement of the dielectric loss of epitaxial $γ$-Al$_2$O$_3$, for which we find a low intrinsic two-level system loss, $δ_{\text{TLS}}^0 = (2.8 \pm 0.1) \times 10^{-5}$. These results establish heteroepitaxial oxides on transition metal nitrides as an attractive materials platform for superconducting quantum circuits, particularly for integration into compact device architectures such as merged-element transmons and microwave kinetic inductance detectors.
Garcia-Wetten, David A. [Northwestern U.]↗
Emerging Two-Dimensional Organic Semiconductor-Incorporated Perovskites–A Fascinating Family of Hybrid Electronic Materials
Halide perovskites have attracted a great amount of attention owing to their unique materials chemistry, excellent electronic properties, and low-cost manufacturing. Two-dimensional (2D) halide perovskites, originating from three-dimensional (3D) perovskite structures, are structurally more diverse and therefore create functional possibilities beyond 3D perovskites. The much less restrictive size constraints on the organic component of these hybrid materials particularly provide an exciting platform for designing unprecedented materials and functionalities at the molecular level. In this Perspective, we discuss the concept and recent development of a sub-class of 2D perovskites, namely, organic semiconductor-incorporated perovskites (OSiPs). OSiPs combine the electronic functionality of organic semiconductors with the soft and dynamic halide perovskite lattice, offering opportunities for tailoring the energy landscape, lattice and carrier dynamics, and electron/ion transport properties for various fundamental studies, as well as device applications. Specifically, we summarize recent advances in the design, synthesis, and structural analysis of OSiPs with various organic conjugated moieties as well as the application of OSiPs in photovoltaics, light-emitting devices, and transistors. As a result, challenges and further opportunities for OSiPs in molecular design, integration of novel functionality, film quality, and stability issues are addressed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Applications of Autonomous Data Collection and Active Learning
Advances in sensors and robotics have dramatically improved the diversity of experimental approaches available to the materials community. Autonomous data collection platforms, either custom-made or commercially available, provide researchers with novel tools with which to probe materials behavior and perform advanced materials characterization. The application of novel control algorithms and active learning approaches can create much more robust experimental data, or can be used to improve the performance of existing characterization tools. Five papers within this special topic focus on experimental and computational methodologies for use in automatic data collection routines for materials characterization. From novel platforms for materials discovery to new statistical frameworks for assessing the autonomous experimentation process, these five papers highlight the diverse range of applications of automation for advancing materials science.
36 MATERIALS SCIENCE↗
FY 2025 Multidimensional Data Correlation Platform: Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing
The Advanced Materials and Manufacturing Technologies (AMMT) program continues to advance a data-driven approach to demonstrate the utility of additive manufacturing for fabricating components for nuclear applications. A key scientific goal is to leverage data to better understand manufacturing outcomes and thereby improve the performance, reliability, and lifespan of nuclear components. Ultimately, this effort supports the development of standards for certification and qualification of additively manufactured components, enabling broader industry adoption. In support of this objective, the AMMT program is building and deploying a data management platform to record, index, analyze, and make available the manufacturing data generated across the AMMT program. In FY 2023, the team conceptualized the architecture of the platform and, in FY 2024, deployed the first functional version at the Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF). In FY 2025, the platform was officially opened to all AMMT members. To enable this expansion, core modifications and enhancements were developed, including improvements to the user interface and workflows for data entry and retrieval. Most notably, robust security and access control mechanisms were implemented to protect data and manage information sharing. This effort featured a logging system, protected views, and controlled access mechanisms. This report documents these enhancements and the transition of the platform into program-wide use.
36 MATERIALS SCIENCE↗
System and technoeconomic analysis of solar thermochemical hydrogen production
Hydrogen is a promising energy carrier that can be obtained from various feedstocks using renewable energy sources. Direct solar thermochemical hydrogen (STCH) production by water splitting can utilize the full spectrum of solar radiation and has the potential to achieve high solar energy conversion efficiencies. Currently STCH research areas focus on material discovery. This paper evaluates the performance of various STCH materials in the context of a system platform to assess techno-economic benefits and gaps in the path to STCH scale-up. Additionally, to analyze the hydrogen production cost, a concentrating solar thermal (CST) system is introduced as a platform for integrating STCH materials and accommodating generalized thermochemical processes. The thermochemical process is based on a two-step STCH cycle using metal oxide that consists of a high temperature step for metal oxide reduction, followed by an oxidation step for water splitting at a lower temperature. A preferred configuration is to have the high temperature step occurring in a directly irradiated solar receiver reactor. To this end, we conceptualized a receiver design and associated solar field layout and investigated STCH operational boundaries, component costs and sensitivity parameters on the $2/kgH 2 goal of hydrogen production. The study explored system-related variables and factors associated with scaling up. The CST platform allows more comprehensive studies that encompass aspects of STCH materials and systems such as cost, hydrogen productivity and replacement frequency, alongside other system components like heliostat field, tower, and potential receiver costs.
08 HYDROGEN↗
Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models
Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.
36 MATERIALS SCIENCE↗
Cation-disordered rocksalt-type high-entropy cathodes for Li-ion batteries
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99 GENERAL AND MISCELLANEOUS↗
FY 2024 Multidimensional Data Correlation Platform: Unified Software Architecture For Advanced Materials And Manufacturing Technologies Data Management And Processing
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36 MATERIALS SCIENCE↗
Lower Cost Renewable Nanoparticle Platform to Increases Production of Cathode Material (CRADA Final Report)
Employees of Sylvatex synthesized candidate cathode materials for lithium-ion batteries in PI’s labs and at the Molecular Foundry using sustainable methods. They then benchmarked the synthesized materials against available commercial cathode materials in lithium half-cells (coin cell configurations) to compare performance and ensure that their materials met or exceeded metrics of the commercial materials.
36 MATERIALS SCIENCE↗
COMPACT - Designing and fabricating a multi-modal characterization platform for a broad range of materials
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Mishra, Swapna Sindhu [Sandia National Laboratorie↗
Magnetic Properties Tuning via Broad Range Site Deficiency in Square Net Material UCu x Bi 2
HfCuSi 2 -type pnictogen compounds have recently been shown to be a versatile platform for designing materials with topologically nontrivial band structures. However, these phases require strict control over the electron count to tune the Fermi level, which can only be achieved in compositions with A 2+ M 2+ Pn 2 and A 3+ M + Pn 2 (A = lanthanides, M = transition metals, Pn = pnictogens P–Bi) charge distribution. While such lanthanide compounds have been thoroughly studied as candidate magnetic topological materials, their heavy element analogs with uranium and bismuth remain largely underexplored. In this report, we present the synthesis of UCu x Bi 2 single crystals and study their magnetic properties. Detailed structural analysis revealed that flux-grown crystals always form as a site-deficient UCu x Bi 2 composition, where x varies between 0.20 and 0.64. Magnetic property measurements revealed a dependence of the magnetic coupling on the Cu site deficiency, linearly changing the Néel temperature from 51 K for UCu 0.60 Bi 2 to 118 K for UCu 0.30 Bi 2 . Moreover, higher Cu concentration promotes a metamagnetic transition in highly magnetically anisotropic UCu 0.60 Bi 2 single crystals. We show that DFT calculations can successfully model site deficiency in the UCu x Sb 2 and UCu x Bi 2 systems. This work paves the way toward using the site deficiency to tune the Fermi level in more ubiquitous A 3+ M 2+ x Pn 2 phases, which previously have not been considered topological candidate materials due to unfavorable electron count.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mo Atom Rearrangement Drives Layer-Dependent Reactivity in Two-Dimensional MoS 2
Two-dimensional (2D) materials offer a valuable platform for manipulating and studying chemical reactions at the atomic level, owing to the ease of controlling their microscopic structure at the nanometer scale. While extensive research has been conducted on the structure-dependent chemical activity of 2D materials, the influence of structural transformation during the reaction has remained largely unexplored. In this work, we report the layer-dependent chemical reactivity of MoS 2 during a nitridation atomic substitution reaction and attribute it to the rearrangement of Mo atoms. Our results show that the chemical reactivity of MoS 2 decreases as the number of layers is reduced in the few-layer regime. In particular, monolayer MoS 2 exhibits significantly lower reactivity compared with its few-layer and multilayer counterparts. Atomic-resolution transmission electron microscopy (TEM) reveals that MoN nanonetworks form as reaction products from monolayer and bilayer MoS 2 , with the continuity of the MoN crystals increasing with layer number, consistent with the local conductivity mapping data. The layer-dependent reactivity is attributed to the relative stability of the hypothetically formed MoN phase, which retains the number of Mo atomic layers present in the precursor. Specifically, the low chemical reactivity of monolayer MoS 2 is attributed to the high energy cost associated with Mo atom diffusion and migration necessary to form multilayer Mo lattices in the thermodynamically stable MoN phase. In conclusion, this study underscores the critical role of lattice rearrangement in governing chemical reactivity and highlights the potential of 2D materials as versatile platforms for advancing the understanding of materials chemistry at the atomic scale.
Chemical reactivity↗
Nanorod Material Developed for Use as an Optical Sensor Platform
Optical sensors are becoming increasingly important in the development of new nonintrusive or embedded sensors. The use of light and material optical properties helps us measure unknown parameters such as temperature, pressure, flow, or chemical species. The focus of this work is to develop new nanostructure platforms upon which optical sensors can be constructed. These nanorods are synthesized oxides that form a base structure to which luminescent sensing dyes or dopants can be attached or embedded. The nanorod structure allows for a much greater open area than closed or polymer-based sensors do, enabling a much faster contact of the measured species with the luminescent sensor and, thus, a potentially faster measurement.
Bencic, Timothy J.↗