Understanding Ion Mobility in P2VP/NMP + I – Polymer Electrolytes: A Combined Simulation and Experimental Study
Not provided.
catalysis (heterogeneous)↗
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Results for “novel 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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Using scalable computer vision to automate high-throughput semiconductor characterization
Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.
Science & Technology - Other Topics↗
Efficient metal ion sieving in rectifying subnanochannels enabled by metal–organic frameworks
Not provided.
catalysis (heterogeneous)↗
Artificial intelligence for advanced functional materials: exploring current and future directions
This perspective addresses the topic of harnessing the tools of artificial intelligence (AI) for boosting innovation in functional materials design and engineering as well as discovering new materials for targeted applications in energy storage, biomedicine, composites, nanoelectronics or quantum technologies. It gives a current view of experts in the field, insisting on challenges and opportunities provided by the development of large materials databases, novel schemes for implementing AI into materials production and characterization as well as progress in the quest of simulating physical and chemical properties of realistic atomic models reaching the trillion atoms scale and with near ab initio accuracy.
36 MATERIALS SCIENCE↗
Water Treatment: Are Membranes the Panacea?
Alongside the rising global water demand, continued stress on current water supplies has sparked interest in using nontraditional source waters for energy, agriculture, industry, and domestic needs. Membrane technologies have emerged as one of the most promising approaches to achieve water security, but implementation of membrane processes for increasingly complex waters remains a challenge. The technical feasibility of membrane processes replacing conventional treatment of alternative water supplies (e.g., wastewater, seawater, and produced water) is considered in the context of typical and emerging water quality goals. This review considers the effectiveness of current technologies (both conventional and membrane based), as well as the potential for recent advancements in membrane research to achieve these water quality goals. We envision the future of water treatment to integrate advanced membranes (e.g., mixed-matrix membranes, block copolymers) into smart treatment trains that achieve several goals, including fit-for-purpose water generation, resource recovery, and energy conservation.
catalysis (heterogeneous)↗
Water Structure and Properties at Hydrophilic and Hydrophobic Surfaces
The properties of water on both molecular and macroscopic surfaces critically influence a wide range of physical behaviors, with applications spanning from membrane science to catalysis to protein engineering. Yet, our current understanding of water interfacing molecular and material surfaces is incomplete, in part because measurement of water structure and molecular-scale properties challenges even the most advanced experimental characterization techniques and computational approaches. This review highlights progress in the ongoing development of tools working to answer fundamental questions on the principles that govern the interactions between water and surfaces. One outstanding and critical question is what universal molecular signatures capture the hydrophobicity of different surfaces in an operationally meaningful way, since traditional macroscopic hydrophobicity measures like contact angles fail to capture even basic properties of molecular or extended surfaces with any heterogeneity at the nanometer length scale. Resolving this grand challenge will require close interactions between state-of-the-art experiments, simulations, and theory, spanning research groups and using agreed-upon model systems, to synthesize an integrated knowledge of solvation water structure, dynamics, and thermodynamics.
catalysis (heterogeneous)↗
A Regulatory Approach to Accelerated Deployment for New Material or Applications in Advanced Reactors
New advanced reactor developers may embark on deploying materials in novel and unique environments where a material’s long-term performance may be in question or unknown. In many cases, sufficient test data may not exist for the material in the desired application, or that no prescript or applicable regulatory testing requirements are available to demonstrate the safety of the application explicitly. This study endeavors to develop the framework for a regulatory and technical approach for safe and predictable accelerated materials use in advanced reactors guided by 10 CFR Part 50.43(e)(1), Advanced Reactor Design Criteria contained in Regulatory Guide 1.232, and Reliability Integrity Management Program (RIM) principles.
99 GENERAL AND MISCELLANEOUS↗
A cryogenically cooled 200 kV DC photoemission electron gun for ultralow emittance photocathodes
Novel photocathode materials like ordered surfaces of single crystal metals, epitaxially grown high quantum efficiency thin films, and topologically non-trivial materials with dirac cones show great promise for generating brighter electron beams for various accelerator and ultrafast electron scattering applications. Despite several materials being identified as brighter photocathodes, none of them have been tested in electron guns to extract electron beams due to technical and logistical challenges. In this paper, we present the design and commissioning of a cryocooled 200 kV DC electron gun that is capable of testing a wide variety of novel photocathode materials over a broad range of temperatures from 298 to 35 K for bright electron beam generation. This gun is designed to enable easy transfer of the photocathode to various standard ultra-high-vacuum surface diagnostics and preparation techniques, allowing a full characterization of the dependence of beam brightness on the photocathode material and surface properties. We demonstrate the development of such a high-voltage, high-gradient gun using materials and equipment that are easily available in any standard university lab, making the development of such 200 kV electron guns more accessible.
Instruments & Instrumentation↗
Deep learning of experimental electrochemistry for battery cathodes across diverse compositions
Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. Here, we present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.
25 ENERGY STORAGE↗
A Novel Surface Restoration Method for Hydropower Steel Components: Plasma Gouging and Inconel Cold Spray Coating for Material Repair
A novel surface restoration approach combining plasma gouging with subsequent cold spray deposition is demonstrated in this study. Plasma gouging effectively removes the damaged steel surface, leaving grooves and forming a plasma gouging affected zone up to ~300?µm thick. Within this zone, a hardened martensitic layer with a peak hardness of ~370?HV—almost twice that of the base substrate (~200?HV)—is produced. Following plasma gouging, cold spray deposition is applied to rebuild the surface. Experimental results reveal that cold spray coatings deposited at low energy suffer from delamination, whereas high energy cold spray deposits yield a well-bonded coating. Microstructural analysis further shows that the martensitic layer formed by plasma gouging undergoes dynamic recrystallization during cold spray, reducing the hardness to 317?HV. These findings demonstrate the feasibility of this hybrid method for effective surface restoration of damaged steel components.
Wang, Tianhao↗
Bench Scale Testing of Next Generation Hollow Fiber Membrane Modules
This project seeks to develop a next generation membrane material (PI-2) for application in Air Liquide’s (AL) hybrid process. Combining the cold membrane operation with an integrated CO 2 Compression and Purification Unit (CPU) significantly reduces the overall cost of CO 2 capture. The proposed work will accelerate the membrane bundle fabrication, scale-up and performance validation of this new material. The proposed novel membrane development, combined with the results of the previous Cold Membrane Project, will provide the best opportunity for AL to meet the long term development targets of the DOE with respect to timing, cost, and performance for CO 2 capture. Our previous field test program (DE-FE0013163) showed promising results for the hybrid process utilizing the existing commercial AL membrane bundles (PI-1 material). The project work has also shown the potential for significant improvements through initial laboratory tests with the novel material (PI-2). The initial PI-2 results show a step-change in membrane permeance. This will enable further reduction in the cost of CO 2 capture by reducing the number of membrane modules and associated equipment in the system. In order to capture this value, however, the new material needs to be validated by field testing of large bundles, representative of commercial production. Lastly, a comprehensive evaluation of novel hybrid processes and costs needs to be completed to ensure optimal use of this improved material performance. The current project seeks to develop this next generation membrane to TRL 5 (approximately 600 - 1,000 Nm3/h flue gas, 350 - 600 scfm, 0.2 - 0.3 MWe equivalent). Air Liquide manufacturing methodology will be applied to fabricate prototype (4”) membrane modules from PI-2 material. Once the manufacturing methods prove reliable with the new material, and performance is demonstrated in line with expectation, 6” commercial scale bundles will be fabricated. Recognizing that a low cost membrane solution by itself may not meet DOE’s LCOE target for CO 2 capture, we will also perform simulation studies of novel hybrid processes in combination with the next generation membrane technology. This approach has the best potential for exceeding the DOE targets. The best evaluation of the new commercial units will be performance testing under real flue gas at the NCCC. Finally, a rigorous TEA, which incorporates the novel process studies and field performance, will be completed.
36 MATERIALS SCIENCE↗
A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding
Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction
Engineering↗
Fused filament fabrication of novel phase-change material functional composites
Additively manufactured polymer heat exchangers are of recent interest in the thermal sciences due to their lightweight and intricate heat-transfer-enhancing geometrical features. The goal of the present research is to directly encapsulate phase-change material (PCM) into polymer filament for the purpose of 3D printing polymer heat exchangers capable of latent heat thermal energy storage and management. PCMs have the ability to absorb large amounts of latent heat while undergoing a solid-to-liquid phase change at a nearly constant temperature. Encapsulation or containment of PCMs is necessary to prevent leaking since the material continuously cycles between a liquid and a solid state. An organic-based PCM and high-density polyethylene (HDPE) were combined and extruded into a functional composite filament. For the first time, with the aid of a heated enclosure and HDPE build plates, it was demonstrated that these functional composite materials can be printed using fused filament fabrication (FFF). Printing HDPE is known to be difficult; however, based on what was observed in the current study, the PCM and HDPE composite was easier to print than pure HDPE. Thermal properties, such as latent heat of fusion, phase-change temperature, and thermal conductivity, of the composite filament and 3D printed samples were investigated and compared with compression-molded bulk material. Finally, the microstructures of the composite filament and 3D printed samples were visualized, and the basic structures of the HDPE and PCM within both the filament and 3D printed parts were clearly delineated.
36 MATERIALS SCIENCE↗
Machine learning in materials science: From explainable predictions to autonomous design
The advent of big data and algorithmic developments in the field of machine learning (and artificial intelligence, in general) have greatly impacted the entire spectrum of physical sciences, including materials science. Materials data, measured or computed, combined with various techniques of machine learning have been employed to address a myriad of challenging problems, such as, development of efficient and predictive surrogate models for a range of materials properties, screening and down-selection of novel candidate materials for targeted applications, new methodologies to improve and further expedite molecular and atomistic simulations, with likely many more important developments to come in the foreseeable future. While the applications thus far have provided a glimpse of the true potential data-enabled routes have to offer, it has also become clear that further progress in this direction hinges on our ability to understand, explain and rationalize findings of a machine learning model in light of the domain-knowledge. This focused review provides an overview of the main areas where machine learning has been widely and successfully used in materials science. Subsequently, a brief discussion of several techniques that have been helpful in extracting physically-meaningful insights, causal relationships and design-centric knowledge from materials data is provided. Finally, we identify some of the imminent opportunities and challenges that materials community faces in this exciting and rapidly growing field.
36 MATERIALS SCIENCE↗
Multi-messenger nanoprobes of hidden magnetism in a strained manganite
Not provided.
charge transport↗
Low-loss composite photonic platform based on 2D semiconductor monolayers
Not provided.
charge transport↗
Pulsed-laser epitaxy of metallic delafossite PdCrO 2 films
Alternate stacking of a highly conducting metallic layer with a magnetic triangular layer found in delafossite PdCrO 2 provides an excellent platform for discovering intriguing correlated quantum phenomena. Thin film growth of delafossites may enable not only the tuning of the basic physical properties beyond what bulk materials can exhibit, but also the development of novel hybrid materials by interfacing with dissimilar materials, yet this has proven to be extremely challenging. Here, we report the epitaxial growth of metallic delafossite PdCrO 2 films by pulsed laser epitaxy (PLE). The fundamental role of the PLE growth conditions, epitaxial strain, and chemical and structural characteristics of the substrate is investigated by growing under various growth conditions and on various types of substrates. While strain plays a large role in improving the crystallinity, the direct growth of epitaxial PdCrO 2 films without impurity phases was not successful. We attribute this difficulty to both the chemical and structural dissimilarities with the substrate and volatile nature of the PdO sublayer, which make nucleation of the right phase difficult. This difficulty was overcome by growing CuCrO 2 buffer layers before PdCrO 2 films were grown. Unlike PdCrO 2 , CuCrO 2 films were readily grown with a relatively wide growth window. Only a monolayer thick buffer layer was sufficient to grow the correct PdCrO 2 phase. This result indicates that the epitaxy of Pd-based delafossites is extremely sensitive to the chemistry and structure of the interface, necessitating near perfect substrate materials. The resulting films are commensurately strained and show an antiferromagnetic transition at 40 K that persists down to as thin as 3.6 nm in thickness. This work provides key insights into advancing the epitaxial growth of the broader class of metallic delafossites for both studying the basic physical properties and developing new spintronic and computing devices.
36 MATERIALS SCIENCE↗
Uncovering electron-phonon scattering and phonon dynamics in type-I Weyl semimetals
Studies of topological semimetals have revealed spectacular transport phenomena spanning extreme magnetoresistance effects and ultrahigh mobilities. As phonon dynamics and electron-phonon scattering play a critical role in the electrical and thermal transport, in this work we pursue a fundamental understanding of these effects in type-I Weyl semimetals NbAs and TaAs. In the temperature-dependent Raman spectra of NbAs we reveal a previously unreported Fano line shape, a signature stemming from the electron-phonon interaction. Additionally, the temperature dependence of the A 1 phonon linewidths in both NbAs and TaAs strongly deviate from the standard model of anharmonic decay. To capture the mechanisms responsible for the observed Fano asymmetry and the atypical phonon linewidth, we present first-principles calculations of the phonon self-energy correction due to the electron-phonon interaction. Through this study of the phonon dynamics and electron-phonon interaction in these Weyl semimetals, we consider specific microscopic pathways which could contribute to the nature of their macroscopic transport.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗