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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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This is the final presentation we provided to our program director, Hal Finkel. He was quite impressed with our progress and results. This is considered as the final report of the project.
Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.
Abstract Ultra‐wide bandgap (UWBG) materials are poised to play an important role in the future of power electronics. Devices made from UWBG materials are expected to operate at higher voltages, frequencies, and temperatures than current silicon and silicon‐carbide‐based devices and can even lead to significant miniaturization of such devices. In the UWBG field, aluminum nitride and boron nitride have attracted great interest; however, the B x Al 1− x N alloys are much less studied. In this work, using first‐principles simulations combining density‐functional theory and the cluster expansion method, the crystal structure of B x Al 1− x N alloys is predicted. Seventeen ground state structures of B x Al 1− x N with formation energies between 0.11 and 0.25 eV atom ‐1 are found. All of these structures are found to be dynamically stable. The B x Al 1− x N structures are found to have predominantly a tetrahedral bonding environment; however, some structures exhibit sp 2 bonds similar to hexagonal BN. This work expands knowledge of the structures, energies, and bonding in B x Al 1− x N which aids their synthesis, the innovation of lateral or vertical devices, and discovery of compatible dielectric and Ohmic contact materials.
Abstract Perovskite solar cells (PSCs) are promising for high‐efficiency tandem applications, but their long‐term stability, particularly due to ion migration, remains a challenge. Despite progress in stabilizing PSCs, they still fall short compared to mature technologies like silicon. This study explores how different piperazinium salt treatments using iodide, chloride, tosylate, and bistriflimide anions affect the energetics, carrier dynamics, and stability of 1.68 eV bandgap PSCs. Chloride‐based treatments achieved the highest power conversion efficiency (21.5%) and open‐circuit voltage (1.28 V), correlating with stronger band bending and n‐type character at the surface. At the same time, they showed reduced long‐term stability due to increased ionic losses. Tosylate‐treated devices offered the best balance, retaining 96.4% efficiency after 1000 h (ISOS‐LC‐1I). These findings suggest that targeted surface treatments can enhance both efficiency and stability in PSCs.
Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.
Academic translational research efforts to industry are often an underlying sought–after goal among various researchers. Through the interchanges of research endeavors between academia–industry, great innovations can/has been achieved that cater to the real–world application by bridging “industrially relevant” problem solving with pursuing fundamental studies. It is pertinent that most of the studies from university–level research works may not translate into demonstrable market products due to various reasons. Funding support, individual researcher goals, socioeconomic factors, and most importantly the technical know–how of generating revenue strategies for startups, are a few of the factors that have slowed the pace of collaborative efforts. However, we believe that the most crucial component is the identification of the critical parameters that solve long–standing problems that hinder the scale–up of the lab scale research into marketable products considering the techno–economic analysis. Here, to illustrate this, we take the three most relevant examples of devices for fuel generation, devices to utilize solar radiation, and devices for detection and other related applications. In this perspective, we provide an in–depth case study of each of these critical parameters to comment on the direction of research avenues that can serve as step–stones for the commercialization of university–level lab research studies.
Brain-inspired computing, reconfigurable optical metamaterials, photonic tensor cores, and many other advanced applications require next-generation phase-change materials (PCMs) with better energy efficiency and a wider thermal and spectral range for reliable operations. Germanium ditelluride (GeTe 2 ), with higher thermal stability and a larger bandgap compared to current benchmark PCMs, appears promising for THz metasurfaces and the controlled crystallization of atomically thin 2D materials. Using high-energy X-Ray diffraction supported by first-principles simulation, the atomic structure in semiconducting pulsed laser deposition films and metallic high-temperature liquids is investigated. The results suggest that the structural and chemical metastability of GeTe 2 , leading to disproportionation into GeTe and Te, is related to high internal pressure during a semiconductor–metal transition, presumably occurring in the supercooled melt. Similar phenomena are expected for canonical GeS 2 and GeSe 2 under high temperatures and pressures.
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Variable stoichiometry and silicate polymorphism in calcium-silicate-hydrates (C-S-H) has impeded the revelation of point defects distribution in the silicate tetrahedral network of C-S-H, which resembles tobermorite crystal structure with some bridging tetrahedra (BT) and paired tetrahedra (PT) vacancies in dreierketten chains. Here we use a computational approach to characterize silicate polymorphism by introducing the vacancy ratio of BT to PT (α) and establishing a three-term empirical mean chain length (MCL) formula for different calcium-to‑silicon ratios (Ca/Si) ranging from 1.2 to 2.3. The formula identifies BT and PT controls at low and high α respectively and allows an inverse mapping of polymorphic range based on NMR experiments. The proposed computational framework quantitatively describes silicate polymorphs and links NMR-measured MCL to C-S-H atomistic configurations at the molecular level.
Increased use of gas diffusion electrodes for CO 2 electroreduction widens the experimental phase space that was previously inaccessible using foil electrodes, raising fundamental questions over the impacts of key variables that translate between liquid- and vapor-fed CO 2 electrolysis systems. This work focuses on studying the interplay of current-potential profiles and electrochemically active surface area (ECSA) by implementing a Cu nanoflower catalyst morphology. The results show decreased overpotentials as much as 460 and 174 mV for foil and gas diffusion electrodes, respectively, while maintaining or improving multi-carbon product current density. Furthermore, these overpotential shifts and product activities normalized by ECSA lead to current-potential relationships akin to those of the Tafel description, which are found through a continuum model to be useful for describing the roughness dependence for both liquid- and vapor-fed systems. This analysis establishes a holistic approach for establishing catalyst design criteria to improve materials development for CO 2 .
Recent advances in the technology readiness level (TRL) of low-temperature electrochemical CO 2 reduction (eCO2R) have demonstrated that the technology has potential for industrial deployment. However, industrial deployment of eCO2R still requires advances to reach cost parity with existing thermal catalytic pathways. Technoeconomic analysis of eCO2R suggests that research and development will require a decrease in both capital expenditures and operational expenditures to be cost competitive. Here, to decrease the capital expenditures of the system will require increasing the durability to >3 years, while decreasing the operational expenditures will require an increase in energy efficiency due to the cost of electricity being the driving operational cost of a unit.