Engineering topics

Martin, Joshua

Publications and source records attributed to Martin, Joshua.

11 records

DOE OSTI2025

Scattering neutrinos, spin models, and permutations

We consider a class of Heisenberg all-to-all coupled spin models inspired by neutrino interactions in a supernova with N degrees of freedom. These models are characterized by a coupling matrix that is relatively simple in the sense that there are only a few, relative to N , nontrivial eigenvalues, in distinction to the classic Heisenberg spin-glass models, leading to distinct behavior in both the high-temperature and low-temperature regimes. When the momenta of the neutrinos are uniform and random in directions, we can calculate the large- N partition function for the quantum Heisenberg model. In particular, the high-temperature partition function predicts a non-Gaussian density of states, providing interesting counterexamples showing the limits of general theorems on the density of states for quantum spin models. We can repeat the same argument for classical Heisenberg models, also known as rotor models, and we find the high-temperature expansion is completely controlled by the eigenvalues of the coupling matrix, and again predicts non-Gaussian behavior for the density of states as long as the number of eigenvalues does not scale linearly with N . Indeed, we derive the amusing fact that these partition functions are essentially the generating function for counting permutations in the high-temperature regime. Finally, for the case relevant to neutrinos in a supernova, we identify the low-temperature phase as a unique state with the direction of the momenta of the neutrino dictating its coherent state in flavor-space, a state we dub the “flavor-momentum-locked” state. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Hydrogen Production, Grid Integration, and Scaling for the Future

The project will explore near and long-term visions towards the commercialization of grid integrated electrolysis systems to inform deployment across the planning, procurement, and operation stages of hydrogen production on the grid. It will leverage NREL's state-of-the-art 1.25 MW polymer electrolyte membrane (PEM) electrolyzer system to characterize system performance in relevant scenarios, also creating a digital twin for emulation in the Advanced Research on Integrated Energy Systems (ARIES) virtual environment and performing hardware-in-the-loop (HIL) testing of pilot scale, decentralized, and centralized hydrogen systems.

electrolysis systems↗

DOE OSTI2024

Megawatt-Scale Low Temperature Electrolyzer Research Capability

The development and installation of a flexible low-temperature electrolyzer research capability at the multi-MW scale with integrated renewables will help lower the cost barrier to entry for electrolyzer manufactures needing at scale system and stack evaluation and enable more electrolyzer manufactures to accelerate to commercialization with building block scale demonstration and validation. This NREL capability represents a DOE HFTO investment to support the $1B DOE Clean Hydrogen Electrolysis Program working to achieve the Hydrogen Shot goal of $1 for 1 kg hydrogen in 1 decade, lower greenhouse gas emissions and criteria pollutants, build clean energy infrastructure, and provide pathways to private sector uptake.

electrical grid↗

DOE OSTI2024

ARIES / Flatirons Facility - Hydrogen System Capability Buildout

Under the "Advanced Research on Integrated Energy Systems" (ARIES) initiative, hydrogen system capabilities including a MW-scale electrolyzer, storage system, and MW-scale fuel cell generator will be designed and commissioned at NREL's Flatirons Campus. This hydrogen infrastructure will support H2@Scale goals by enabling integrated systems R&D to study the science of scaling for hydrogen energy systems.The system is designed with flexibility to provide a testbed to demonstrate systems integration, grid services, energy storage, direct renewable hydrogen production, and innovative end use applications (e.g. HD transportation, natural gas blending, etc.).

electrical grid↗

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 OSTI2024

A Simple Model of the Energy Threshold for Snowball Chambers

Cloud and bubble chambers have historically been used for particle detection, capitalizing on supersaturation and superheating, respectively. Here, we present new results from a prototype snowball chamber, in which an incoming particle triggers the crystallization of a purified, supercooled liquid. We demonstrate, for the first time, simulation agreement with our first results from 5 years ago: the higher temperature of the freezing of water and significantly shorter time spent supercooled compared to the control in the presence of a Cf-252 fission neutron source. This is accomplished by combining Geant4 modeling of neutron interactions with the Seitz nucleation model used in superheated bubble chambers, including those seeking dark matter. We explore the possible implications of using this new technology for GeV-scale WIMP searches, especially in terms of spin-dependent proton coupling, and report the first supercooling of WbLS (water-based liquid scintillator).

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Temperature Rise on Liner Surfaces of Fuel Cell Electric Vehicle Tanks during Fueling Process

Herein, the temperature of the inner tank walls, or plastic liners, of composite pressure tanks in fuel cell electric vehicles during fueling using three‐dimensional computational fluid dynamics (CFD) models is evaluated. The liner materials are limited to 85.0 °C to prevent thermal stress causing material failure that would result in a hydrogen leak. Therefore, the temperature of hydrogen gas must be limited to below 85.0 °C during the fueling process as dictated by the current fueling protocol. However, there are limited experimental or simulation data confirming that the temperature changes do not exceed the threshold. Herein, the liner temperatures with CFD tank models for two sizes of type IV tanks representative of the upper and lower system bounds that are close to the SAE J2601 fueling protocol (36.0 and 244.0 L) are evaluated. First, each model's reliability is validated with experimental data and then analyzed, and the data are used to evaluate the maximum hydrogen and liner temperatures under real‐world fueling conditions. The evaluation shows that the maximum liner surface temperature of each tank model is at least 7 °C lower than that of the hydrogen. Additionally, there is at least 12 °C difference found between the upper limit and actual liner temperatures.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

High-throughput printing of combinatorial materials from aerosols

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces 1 . Whereas traditional combinatorial deposition methods can generate material libraries 2,3 , these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases 4–6 . We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Synthesis, structure, electronic and thermal properties of sphalerite CuZn 2 InS 4

Quaternary chalcogenides continue to be of interest due to the variety of physical properties they possess, as well as their potential for different applications of interest. Investigations on materials with the sphalerite crystal structure have only recently begun. In this study we have synthesized sulfur-based sphalerite quaternary chalcogenides, including off-stoichiometric compositions, and investigated the temperature-dependent electronic, thermal and structural properties of these materials. Insulating to semiconducting transport is observed with stoichiometric variation, and analyses of heat capacity and thermal expansion revealed lattice anharmonicity that contributes to the low thermal conductivity these materials possess. Finally, we include similar analyses for CuZn 2 InSe 4 and compare these sphalerite quaternary chalcogenides to that of zinc blende binaries in order to fully understand the origin of the low thermal conductivity these quaternary chalcogenides possess.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Off-stoichiometric semiconductors Cu 1.33+x Zn 1.33-x In 1.33 Se 4 (x = 0, 0.1, 0.2 and 0.3): Synthesis, structure, and thermal and electrical properties

The synthesis, structure, and temperature dependent thermal and electrical properties of off-stoichiometric polycrystalline modified zinc blende quaternary chalcogenides Cu 1.33+x Zn 1.33-x In 1.33 Se 4 , where x = 0, 0.1, 0.2 and 0.3, are investigated. Temperature-dependent electrical properties reveal these compositions to be semiconductors with alteration of the carrier concentration and electrical transport via stoichiometric variation. The thermal conductivity is low for all specimens and intrinsic to these materials. First principles calculations are also reported in establishing a fundamental investigation that illustrates the large variation in stoichiometry that is possible in these materials. This stoichiometric variation results in the observed variation of the transport properties. Overall, the results presented reveal fundamental structure-property relationships in these quaternary chalcogenides, and provides a basis for further research into the viability for large stoichiometric variation in other materials that are of interest for technological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Thermal Properties of the Very Low Thermal Conductivity Ternary Chalcogenide Cu 4 Bi 4 M 9 (M = S, Se)

Temperature-dependent thermal properties of phase-pure polycrystalline ternary chalcogenides Cu 4 Bi 4 S 9 and Cu 4 Bi 4 Se 9 are reported. The structure and bonding in these materials result in very low thermal conductivity values (<0.8 W m -1 K -1 at room temperature) for both materials. The lattice contribution, Debye temperatures, and Sommerfeld coefficient are obtained from low-temperature heat capacity data that also indicate very small electronic contributions to the heat capacity for these materials. This study aids in the identification of new nontoxic, earth-abundant resistive ternary chalcogenide materials with low thermal conductivity for potential thermal barrier coating and rewriteable storage applications.

36 MATERIALS SCIENCE↗