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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Topological control of liquid-metal-dealloyed structures

Abstract The past few years have witnessed the rapid development of liquid metal dealloying to fabricate nano-/meso-scale porous and composite structures with ultra-high interfacial area for diverse materials applications. However, this method currently has two important limitations. First, it produces bicontinuous structures with high-genus topologies for a limited range of alloy compositions. Second, structures have a large ligament size due to substantial coarsening during dealloying at high temperature. Here we demonstrate computationally and experimentally that those limitations can be overcome by adding to the metallic melt an element that promotes high-genus topologies by limiting the leakage of the immiscible element during dealloying. We further interpret this finding by showing that bulk diffusive transport of the immiscible element in the liquid melt strongly influences the evolution of the solid fraction and topology of the structure during dealloying. The results shed light on fundamental differences in liquid metal and electrochemical dealloying and establish a new approach to produce liquid-metal-dealloyed structures with desired size and topologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enabling ambient stability and quantum integration of organometallic magnonic ferrimagnets via atomic layer encapsulation

Magnons, the quanta of spin waves in magnetic materials, are promising for hybrid quantum systems by bridging electromagnetic and spin degrees of freedom. The organometallic ferrimagnet vanadium tetracyanoethylene (V[TCNE] x , x ≈ 2) is especially well-suited for quantum magnonics due to its low Gilbert damping and substrate versatility. However, its rapid chemical degradation in ambient conditions hinders practical applications. Incumbent encapsulation methods provide some protection, but are bulky, obscure intrinsic properties of V[TCNE] x , introduce thermal stress at cryogenic temperatures, and complicate microwave device integration. Here, we demonstrate that ultrathin alumina films deposited via low-temperature atomic layer deposition effectively protect V[TCNE] x by preserving its magnetic and magnonic properties following ambient exposure. The sub-100 nm transparent films also enable advanced spectroscopy, magnetometry, and cavity magnonic measurements that reveal the intrinsic properties of V[TCNE] x . This encapsulation strategy advances molecule-based quantum information science by providing a robust route toward scalable, monolithic integration in hybrid quantum technologies.

magnetic materials↗
DOE OSTI2023

Grain boundary effects in high-temperature liquid-metal dealloying: a multi-phase field study

Abstract A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying, specifically considering the role of grain boundaries. A semi-implicit time-stepping algorithm using spectral methods is implemented, which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness. Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface, which locally accelerates diffusion-coupled growth of a liquid channel into the precursor. This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations. The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species, below the parting limit . The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Colloidal quantum wells for optoelectronic devices

Colloidal quantum wells, also called nanoplatelets, are nanoscopic materials displaying quantum confinement in two dimensions. Unlike colloidal quantum dots, colloidal quantum well ensembles have no inhomogeneous broadening due to an atomically-precise definition of the short axis, a fact which results in much narrower ensemble absorption and emission. Thus, colloidal quantum wells can translate many advantages of colloidal nanocrsytals or other solution-processable materials, such as scalable synthesis and substrate-agnostic deposition (particularly compared to epitaxial quantum wells), without sacrificing material uniformity. Furthermore, due to very narrow photoluminescnece peaks, these materials have found a home in applications involving light emission, such as downconversion enhancement films, light-emitting diodes, and lasers, in which they represent some of the best performers among solution-cast materials. As argued in this review, the full spectrum of epitaxial quantum well devices offers a roadmap to other potential applications, such as detection, electronics, electro-optics, non-linear optics, or intersubband devices, in which only nascent efforts have been made.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-pressure high-temperature synthesis and thermal equation of state of high-entropy transition metal boride

High-entropy transition metal boride (Hf 0.2 Ti 0.2 Zr 0.2 Ta 0.2 Mo 0.2 )B 2 sample was synthesized under high-pressure and high-temperature starting from ball-milled oxide precursors (HfO 2 , TiO 2 , ZrO 2 , Ta 2 O 5 , MoO 3 ) mixed with graphite and boron-carbide. Experiments were conducted in a large-volume Paris Edinburgh press combined with an in-situ Energy Dispersive X-ray Diffraction. The hexagonal AlB 2 phase with an ambient pressure volume V 0 = 27.93 ± 0.03 Å 3 was synthesized at a pressure of 0.9 GPa and temperatures above 1373K. High-pressure high-temperature studies on the synthesized high-entropy transition metal boride sample were performed to 7.6 GPa and 1873 K. The thermal equation of state fitted to the experimental data resulted in an ambient pressure bulk-modulus K 0 = 344 ± 39 GPa, dK/dT = –0.108 ± 0.027 GPa/K, and a temperature dependent volumetric thermal expansion coefficient α = α 0 + α 1 T + α 2 T –2 . The thermal stability combined with a high bulk-modulus establishes this high-entropy transition metal boride as an ultrahard high-temperature ceramic material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Materials representation and transfer learning for multi-property prediction

The adoption of machine learning in materials science has rapidly transformed materials property prediction. Hurdles limiting full capitalization of recent advancements in machine learning include the limited development of methods to learn the underlying interactions of multiple elements as well as the relationships among multiple properties to facilitate property prediction in new composition spaces. To address these issues, we introduce the Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP) framework that seamlessly integrates: (i) prediction using only a material's composition, (ii) learning and exploitation of correlations among target properties in multi-target regression, and (iii) leveraging training data from tangential domains via generative transfer learning. The model is demonstrated for prediction of spectral optical absorption of complex metal oxides spanning 69 three-cation metal oxide composition spaces. H-CLMP accurately predicts non-linear composition-property relationships in composition spaces for which no training data are available, which broadens the purview of machine learning to the discovery of materials with exceptional properties. This achievement results from the principled integration of latent embedding learning, property correlation learning, generative transfer learning, and attention models. The best performance is obtained using H-CLMP with transfer learning [H-CLMP(T)] wherein a generative adversarial network is trained on computational density of states data and deployed in the target domain to augment prediction of optical absorption from composition. H-CLMP(T) aggregates multiple knowledge sources with a framework that is well suited for multi-target regression across the physical sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Metal–ceramic composite structures for fabrication of high power density plasmonic devices

The recent decade brought many advances to plasmonics, but high power density plasmonic antennas designed to behave as heaters or operate in high temperature environments are still facing material stability challenges preventing their ultimate use. Gold has been the optimal choice among plasmonic materials but experiences morphology changes at temperature that result in device efficiency reduction and failure. Bulk titanium nitride has been explored as a solution but has deal-breaking tradeoffs in device quality factor. In this paper, we explore via proof-of-concept the use of a metal–ceramic composite structure to determine whether a bulk Au nanorod can provide strong plasmonic resonances while coated with an ultrathin conformal layer of titanium nitride or silica to provide morphological stability and sufficient plasmonic activity without excessive resonance quality degradation. We show SEM-level morphological stability for temperatures up to 500 °C with coatings below 4 nm. Computer modeling suggests the ultrathin titanium nitride has detrimental effects on the strong plasmonic resonances of a Au nanorod. Here, we then looked into other possible coatings for solutions to stabilize high power density plasmonic antennas including plasmonic oxides, metal adhesion layers, and silica, the latter appearing to be the best option while lowering the overall peak electric field intensity, the silica increases the electric field intensity at its boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Low temperature tetragonal polymorph of CaZrF 6

A new tetragonal polymorph of CaZrF 6 can be prepared by high energy ball milling of a CaF 2 /ZrF 4 mixture, followed by heat treatment at 325 °C. This polymorph is thermodynamically stable with respect to the well-known cubic form at low temperatures. However, it readily transforms to the cubic form on heating above ~400 °C. The tetragonal (β) CaZrF 6 is not isostructural with any previously known alkaline earth AZrF 6 phase. Unlike the cubic form, which shows strong negative thermal expansion over a wide temperature range, the tetragonal form displays positive thermal expansion in all directions (100–400 K: α l ~ +17 × 10 –6 K –1 and +13 × 10 –6 K –1 along the a- and c-axes, respectively).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additive manufacturing of high explosives with inert dilution for wave shaping and detonation velocity grading

The performance of a high explosive charge is highly influenced by the detonation velocity and any inherent internal structure. Additively manufactured (AM) high explosive charges allow for a precisely engineered internal structure and the selective placement of discrete or graded volumes of a tailored material, which are unachievable by conventional means. The dilution of a solid explosive by an inert additive for detonation velocity reduction is herein evaluated for a method of material extrusion called a direct-ink-write AM, where an 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane-based ultraviolet -curable energetic-binder paste explosive was diluted by the inert density mock 5-iodo-2′-deoxyuridine for use in the manufacture of multi-material explosive charges. The explosive ink was characterized for printing by rheological and particle size measurements, and the detonation velocities for 0–40 wt. % inert diluent were found to have a continuous linear reduction in detonation velocity down to 14.3% difference. A two-component 3D plane wave explosive lens with 8.038 km/s “fast” and 7.491 km/s “slow” diluted ink in an internal cone demonstrated a reduced time of breakout at the output face from 361 to 53 ns. A linearly graded “fast–slow–fast” cylinder was successfully printed and fired, showing engineered control along the length of the charge as the detonation velocity dropped from 7.851 to 6.700 km/s and then recovered to 7.241 km/s. The extreme control over the internal composition of a high explosive charge via a dual-material extruder/mixer challenges conventional manufacturing approaches and opens new avenues for engineered detonation wavefronts, high explosive charge performance, and new applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Benchmarking large language models for materials synthesis: The case of atomic layer deposition

In this work, we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and, in particular, in the field of atomic layer deposition, a thin film growth technique used in energy applications and microelectronics. Our benchmark comprises questions with a level of difficulty ranging from the graduate level to domain expert current with the state of the art in the field. Human experts reviewed the questions along the criteria of difficulty and specificity, and the model responses along four different criteria: overall quality, specificity, relevance, and accuracy. We ran this benchmark on an instance of OpenAI’s GPT-4o. The responses from the model received a composite quality score of 3.7 on a 1–5 scale, consistent with a passing grade. However, 36% of the questions received at least one below average score. An in-depth analysis of the responses identified at least five instances of suspected hallucination. Finally, we observed statistically significant correlations between the difficulty of the question and the quality of the response, the difficulty of the question and the relevance of the response, the specificity of the question, and the accuracy of the response as graded by the human experts. Furthermore, this emphasizes the need to evaluate LLMs across multiple criteria beyond difficulty or accuracy.

Artificial intelligence↗
DOE OSTI2020

Process scale-up and optimization of the metal-organic framework synthesis

Mosaic Materials is incubated under Cyclotron Road LBNL, focusing on design, synthesis, and characterization of metal-organic frameworks as highly selective and energy efficient adsorbents for carbon dioxide. The Chief Science Officer, Dr. Thomas McDonald, invented a new class of phase-change adsorbents for acid gas removal that the company is working to commercialize as its first product. ABPD worked with Mosaic team to scale up their synthesis process and evaluate the downstream processing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Study of Poly(ether ketone ketone) (PEKK): Outgassing Characteristics and Likely Residual Synthesis Impurities

In May-June, 2020, a study was conducted to characterize the outgassing properties of a series PEKK (Poly(ether ketone ketone)) samples using cryo-GC/MS headspace analysis. Three sets of samples were interrogated: sample group 1 consisted of 2 additively manufactured PEKK samples (PEKK "ole and "New") prepared by KCNSC from powder material from Solvay Specialty Polymers USA, LLC. Sample groups 2 and 3 consist of 5 PEKK powder types (used as feedstock for additive manufacturing processes) and 4 additively-manufactured PEKK material lots, respectively. Contrary to expectations, all samples of PEKK material were observed to outgas sulfur-containing compounds. Other analyses (EDS/EMA, GC-TOF/MS of PEKK sample extractions) confirmed the presence of sulfur in the PEKK bulk material. Specifically, Diphenyl sulfone (used as a reagent or high-temperature solvent in the synthesis of Polyaryletherketone or PAEK polymers) was observed in three of the powders and in both the PEKK "Old" and "New" samples, suggesting that the source of the sulfur can be traced to impurities in the material left over from the synthesis process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Liquid crystals of neat boron nitride nanotubes and their assembly into ordered macroscopic materials

Abstract Boron nitride nanotubes (BNNTs) have attracted attention for their predicted extraordinary properties; yet, challenges in synthesis and processing have stifled progress on macroscopic materials. Recent advances have led to the production of highly pure BNNTs. Here we report that neat BNNTs dissolve in chlorosulfonic acid (CSA) and form birefringent liquid crystal domains at concentrations above 170 ppmw. These tactoidal domains merge into millimeter-sized regions upon light sonication in capillaries. Cryogenic electron microscopy directly shows nematic alignment of BNNTs in solution. BNNT liquid crystals can be processed into aligned films and extruded into neat BNNT fibers. This study of nematic liquid crystals of BNNTs demonstrates their ability to form macroscopic materials to be used in high-performance applications.

36 MATERIALS SCIENCE↗