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At least 307 records · Page 17

High-Temperature Gas Sensor Materials with Properties Predicted via First-Principles Calculations with Machine Learning Modeling and Experimental Corroboration

Understanding the temperature dependence of functional properties of sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we first assess the temperature dependence of band gap renormalization in sensing materials by employing Allen-Heine-Cardona (AHC) theory with density functional theory (DFT) simulations corroborated with experimental observation. As the AHC calculations are impractical for high-throughput screening of materials, we employ data-driven Gaussian process regression to predict the parameters employed in the O’Donnell empirical model from a set of physical features. To mitigate the reliability issues arising from the small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as to quantify the uncertainty associated with theoretical predictions. These models capture well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions and, therefore, the variation of bandgap as a function of temperature for other novel materials. The predicted candidates from machine learning models are further validated by experiments and DFT calculations.

bandgap renormalization↗

Harnessing Quantum Capacitance in 2D Material/Molecular Layer Junctions for Novel Electronic Device Functionality

Two-dimensional (2D) materials promise advances in electronic devices beyond Moore’s scaling law through extended functionality, such as non-monotonic dependence of device parameters on input parameters. However, the robustness and performance of effects like negative differential resistance (NDR) and anti-ambipolar behavior have been limited in scale and robustness by relying on atomic defects and complex heterojunctions. In this paper, we introduce a novel device concept that utilizes the quantum capacitance of junctions between 2D materials and molecular layers. We realized a variable capacitance 2D molecular junction (vc2Dmj) diode through the scalable integration of graphene and single layers of stearic acid. The vc2Dmj exhibits NDR with a substantial peak-to-valley ratio even at room temperature and an active negative resistance region. The origin of this unique behavior was identified through thermoelectric measurements and ab initio calculations to be a hybridization effect between graphene and the molecular layer. The enhancement of device parameters through morphology optimization highlights the potential of our approach toward new functionalities that advance the landscape of future electronics.

2D materials↗

Second-harmonic generation tensors from high-throughput density-functional perturbation theory

Optical materials play a key role in enabling modern optoelectronic technologies in a wide variety of domains such as the medical or the energy sector. Among them, nonlinear optical crystals are of primary importance to achieve a broader range of electromagnetic waves in the devices. However, numerous and contradicting requirements significantly limit the discovery of new potential candidates, which, in turn, hinders the technological development. In the present work, the static nonlinear susceptibility and dielectric tensor are computed via density-functional perturbation theory for a set of 579 inorganic semiconductors. The computational methodology is discussed and the provided database is described with respect to both its data distribution and its format. Several comparisons with both experimental and ab initio results from literature allow to confirm the reliability of our data. The aim of this work is to provide a relevant dataset to foster the identification of promising nonlinear optical crystals in order to motivate their subsequent experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Block copolymer self-assembly derived mesoporous magnetic materials with three-dimensionally (3D) co-continuous gyroid nanostructure

Magnetic nanomaterials are gaining interest for their many applications in technological areas from information science and computing to next-generation quantum energy materials. While magnetic materials have historically been nanostructured through techniques such as lithography and molecular beam epitaxy, there has recently been growing interest in using soft matter self-assembly. In this work, a triblock terpolymer, poly(isoprene-block-styrene-block-ethylene oxide) (ISO), is used as a structure directing agent for aluminosilicate sol nanoparticles and magnetic material precursors to generate organic–inorganic bulk hybrid films with co-continuous morphology. After thermal processing into mesoporous materials, results from a combination of small angle X-ray scattering (SAXS) and scanning electron microscopy (SEM) are consistent with the double gyroid morphology. Nitrogen sorption measurements reveal a type IV isotherm with H1 hysteresis, and yield a specific surface area of around 200 m 2 g −1 and an average pore size of 23 nm. The magnetization of the mesostructured material as a function of applied field shows magnetic hysteresis and coercivity at 300 K and 10 K. Comparison of magnetic measurements between the mesoporous gyroid and an unstructured bulk magnetic material, derived from the identical inorganic precursors, reveals the structured material exhibits a coercivity of 250 Oe, opposed to 148 Oe for the unstructured at 10 K, and presence of remnant magnetic moment not conventionally found in bulk hematite; both of these properties are attributed to the mesostructure. This scalable route to mesoporous magnetic materials with co-continuous morphologies from block copolymer self-assembly may provide a pathway to advanced magnetic nanomaterials with a range of potential applications.

Chemistry↗

Enhancing electrocatalytic performance of RuO 2 -based catalysts: mechanistic insights, strategic approaches, and recent advances

Abstract Electrochemical water splitting presents the ultimate potential of hydrogen and oxygen production; however, regulating the rate and efficiency of water splitting is highly dependent on the accessibility of extremely efficient electrode materials for slow performance kinetics and large overpotential of both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Ruthenium oxide (RuO 2 ) based materials display high performance for OER and HER because of their capacity to bind oxygen, eminent catalytic activity, low cost compared to other precious metals, and stability in a wide pH range. However, there is still much space to promote the OER and HER activity and stability of RuO 2 to fulfill the necessity for practical applications in water splitting. Different researchers applied multiple approaches that boosted the catalytic performance of RuO 2 -based electrocatalysts toward overall water splitting. Herein, this review provides a comprehensive overview of recent advancements in RuO 2 -based materials in the field of water electrolysis for the generation of alternative energies. It gives a general description of water splitting in acidic and alkaline settings, including reaction mechanisms as well as common evaluation elements for the catalytic function of the materials. Most of the reviews reported based on RuO 2 materials are only focused on OER performance, but this review highlighted comprehensive ideas on different strategies like morphology design, electronic structure, electrolytes, and compositions for optimizing both electrocatalytic HER and OER functioning of RuO 2 -based electrocatalysts.

KC, Binod Raj (ORCID:0009000885806906)↗

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗

Self-Sorting vs Coassembly in Peptide Amphiphile Supramolecular Nanostructures

The functionality of supramolecular nanostructures can be expanded if systems containing multiple components are designed to either self-sort or mix into coassemblies. This is critical to gain the ability to craft self-assembling materials that integrate functions, and our understanding of this process is in its early stages. Here, in this work, we have utilized three different peptide amphiphiles with the capacity to form β-sheets within supramolecular nanostructures and found binary systems that self-sort and others that form coassemblies. This was measured using atomic force microscopy to reveal the nanoscale morphology of assemblies and confocal laser scanning microscopy to determine the distribution of fluorescently labeled monomers. We discovered that PA assemblies with opposite supramolecular chirality self-sorted into chemically distinct nanostructures. In contrast, the PA molecules that formed a mixture of right-handed, left-handed, and flat nanostructures on their own were able to coassemble with the other PA molecules. We attribute this phenomenon to the energy barrier associated with changing the handedness of a β-sheet twist in a coassembly of two different PA molecules. This observation could be useful for designing biomolecular nanostructures with dual bioactivity or interpenetrating networks of PA supramolecular assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Insights into Phase Equilibria Between Wide-Gap Semiconductors and Contact Materials

Novel wide-band-gap semiconductors are needed for next-generation power electronics, but there is a gap between a promising material and a functional device. Finding stable (metal) contacts is one of the major challenges that is currently dealt with mainly via trial and error. Herein, we computationally investigate the thermochemistry and phase coexistence at the junction between three wide-gap semiconductors, ..beta..-Ga2O3, GeO2, and GaN, and possible contact materials. The pool of possible contacts includes 47 elemental metals and a set of 4 common, n-type transparent conducting oxides (ZnO, TiO2, SnO2, and In2O3). We use first-principles thermodynamics to model the Gibbs free energies of chemical reactions as a function of gas pressure (pO2/pN2) and equilibrium temperature. We deduce whether a semiconductor/contact interface will be stable at relevant conditions or a chemical reaction between them is to be expected, possibly influencing the long-term reliability and performance of devices. We generally find that most elemental metals tend to oxidize or nitridize and form various interface oxide/nitride layers. Exceptions include select late- and post-transition metals and, in the case of GaN, also the alkali metals, which are predicted to exhibit stable coexistence, although in many cases at relatively low gas partial pressures. Similar is true for the transparent conducting oxides, for which, in most cases, we predict a preference toward forming ternary oxides when in contact with ..beta..-Ga2O3 and GeO2. The only exception is SnO2, which we find to form stable contacts with both oxides. Finally, we show how the same approach can be used to predict gas partial pressure vs temperature phase diagrams to help direct synthesis of ternary compounds. We believe these results provide a valuable guidance in selecting contact materials to wide-gap semiconductors and suitable growth conditions.

contact materials↗

Correlation between complex spin textures and the magnetocaloric and Hall effects in Eu⁢(Ga 1−𝑥 ⁢Al 𝑥 ) 4 (𝑥=0.9, 1)

Determining the electronic phase diagram of a quantum material as a function of temperature (𝑇) and applied magnetic field (𝐻) forms the basis for understanding the microscopic origin of transport properties, such as the anomalous Hall effect (AHE) and topological Hall effect (THE). For many magnetic quantum materials, including Eu⁢Al 4 , a THE arises from a topologically protected magnetic skyrmion lattice with a nonzero scalar spin chirality. We identified a square skyrmion lattice (sSkL) peak in Eu⁢(Ga 1−𝑥 ⁢Al 𝑥 ) 4 (𝑥=0.9) identical to the peak previously observed in Eu⁢Al 4 by performing neutron-scattering measurements throughout the phase diagram. Here, comparing these neutron results with transport measurements, we found that in both compounds the maximal THE does not correspond to the sSkL area. Instead of the maximal THE, the maximal magnetocaloric-effect boundaries better identify the sSkL lattice phase observed by neutron-scattering measurements. The maximal THE therefore arises from interactions of itinerant electrons with frustrated spin fluctuations in a topologically trivial magnetic state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancement of Carbon Capture Reactor Performance (Final Technical Report)

Significant challenges are still present in post-combustion CO 2 capture and new technologies and advanced components are needed to significantly advance the deployment of CO 2 capture for natural gas combined cycle (NGCC) plants. Critical elements of CO 2 capture that still need to be addressed include how to increase CO 2 mass transfer in the absorber column with liquid to gas ratios of <1.2, while reducing the size of the absorber column to reduce capital costs. Research involving chemical mechanism with design, synthesis, and assembly of materials with targeted functionally were combined with advanced additive manufacturing techniques towards development of enhanced CO 2 capture reactors that can lead to safe, reliable, and low-cost carbon capture technologies. The objective of the project was to develop and test novel carbon capture materials and reactor components that contribute to increased CO 2 mass transfer through increased turbulent gas-liquid interface and improved solvent wetting within the absorber. A technoeconomic analysis (TEA) was completed showing how the proposed technology decreases capital costs by reducing the size of the absorber column and the amount of packing required for high CO 2 capture rates. A technology maturation plan (TMP) was also developed to describe the current technology readiness levels (TRL) and outline additional research and development (R&D) needed to further develop these advanced components for NGCC CO 2 capture plants. The successful completion of this project has shown a pathway to reduce the absorber size and associated construction costs of post-combustion NGCC CO 2 capture systems at 97% capture and promote the utilization of abundant natural gas for production of reliable electricity.

20 FOSSIL-FUELED POWER PLANTS↗

3D Printing of Inconel 718 with Enhanced Boron Composition as a Novel Solar Absorber Tube Material in the Concentrated Solar Power (CSP) System

The growing demands for elevated efficiency in the solar energy industry led researchers to focus on the development of functional solar absorber tube material in concentrated solar power (CSP) systems, when molten salts are adopted as the heat transfer fluid. In this study, the typical solar absorber tube material, Inconel 718, was enhanced with boron to achieve a higher solar absorptivity in the visible light spectrum. Combined with an additive manufacturing (AM) method, the boron composition exceeded the traditional manufacturing limit of 60 ppm without microstructural defects. The boron-enhanced Inconel 718 exhibited a high solar absorptivity of nearly 90 % while maintaining a high thermal cycle fatigue resistance after thermal cycling treatment between 550°C and 720°C. The boron composition was increased to the manufacturing failure point, and the effects of different boron compositions on mechanical properties, microstructure, and optical properties were studied. The provided microstructure-property map in this study delivers high potentials of functional AM-printed alloy material in CSP applications.

13 HYDRO ENERGY↗

Exploring Quantum Materials with Resonant Inelastic X-Ray Scattering

Understanding quantum materials—solids in which interactions among constituent electrons yield a great variety of novel emergent quantum phenomena—is a forefront challenge in modern condensed matter physics. This goal has driven the invention and refinement of several experimental methods, which can spectroscopically determine the elementary excitations and correlation functions that determine material properties. Here we focus on the future experimental and theoretical trends of resonant inelastic x-ray scattering (RIXS), which is a remarkably versatile and rapidly growing technique for probing different charge, lattice, spin, and orbital excitations in quantum materials. We provide a forward-looking introduction to RIXS and outline how this technique is poised to deepen our insight into the nature of quantum materials and of their emergent electronic phenomena. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nanocrystal Assemblies: Current Advances and Open Problems

Here we explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

M PX 3 van der Waals magnets under pressure ( M = Mn, Ni, V, Fe, Co, Cd; X = S, Se)

van der Waals antiferromagnets with chemical formula MPX 3 (M = V, Mn, Fe, Co, Ni, Cd; X = S, Se) are superb platforms for exploring the fundamental properties of complex chalcogenides, revealing their structure-property relations and unraveling the physics of confinement. Pressure is extremely effective as an external stimulus, able to tune properties and drive new states of matter. In this review, we summarize experimental and theoretical progress to date with special emphasis on the structural, magnetic, and optical properties of the MPX 3 family of materials. Under compression, these compounds host inter-layer sliding and insulator-to-metal transitions accompanied by dramatic volume reduction and spin state collapse, piezochromism, possible polar metal and orbital Mott phases, as well as superconductivity. Some responses are already providing the basis for spintronic, magneto-optic, and thermoelectric devices. We propose that strain may drive similar functionality in these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ionization-driven competitive (recovery) process in pre-damaged KTaO 3 : A brief review

The nuclear (S n ) and electronic (S e ) energy dissipation processes have been considered to be independent and largely uncorrelated, influencing our understanding of ion–solid interaction and damage processes in the last decades. Recently, however, it has become more generally accepted that S n and S e are coupled as they interact both in time and space. To decouple these processes, separating these effects in experiments using sequential dual-beam irradiations have become accepted as the logical path to advance the understanding of complex interactions between S e and pre-existing defects that may be created from displacement events. This experimental approach has been recently applied to studies of KTaO 3 to reveal new insights into this critical research topic. Here, we offer a forward-looking and comprehensive perspective on the fundamental coupling between Se and pre-existing defects in KTaO 3 . The origins behind the competitive two-stage phase transition process leading to damage healing are revealed and discussed. Furthermore, the evidence resulting from synergistic effects is also included for comparison. Additionally, our findings are rationalized using both Se and the ion velocity as key parameters. We highlight how the inelastic thermal spike (i-TS) calculations provide insights into the nature of this coupled process and further confirm that the ion velocity effect governs annealing kinetics. This work emphasizes that through the introduction of a small amount of local disorder in materials, MeV ion irradiation (i.e., not extreme S e ) may also be one additional option in subsequent material modification and functionalization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Influence of strain-rate on the response of elastomeric architected materials

Architected materials have shown substantial promise in impact mitigation and protective applications, and there has accordingly been great interest in better characterizing their response at elevated strain rates due to impact. There remains ambiguity regarding the contribution of inertial and material responses to strain rate sensitivity, and, in particular, when these effects begin to gain dominance in the impact response of an architected material. The response of soft polymer architected materials as a function of strain rate, in particular, has been little investigated. We characterize the experimental impact response of four soft polymer architected lattice geometries across varying strain rates in the intermediate strain rate regime (∼10 3 s −1 ) using split-Hopkinson pressure bar loading and high speed video characterization of the resulting deformation fields. In conclusion, our results highlight the interplay of influence between constituent material, lattice geometry, length scale, and strain rate in determining the onset of significant inertia effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

AI for Materials Design and Discovery Using Atomistic Scale Information [Industrial and Governmental Activities]

The design and discovery of materials with desired functional properties is pivotal to the scientific mission of the United States Department of Energy (US-DOE) [1], which includes within its portfolio several important applications for the national economy and security. Importantly, these applications range from: renewable energy (e.g., solar cells, organic photovoltaics, and organic light-emitting diodes), energy storage (e.g., batteries and supercapacitors), and carbon capture and sequestration, to synthesis of manufacturing of new materials (e.g., drugs, or materials with desired conductivity, thermal stability, and catalytic activity), and nuclear energy (e.g., highly performant nuclear fuels and materials with improved nuclear shielding properties).

97 MATHEMATICS AND COMPUTING↗

The mechanical properties of Kel-F 800 (FK-800) as a function of crystallinity

Kel-F 800 is a copolymer of chlorotrifluoroethylene PTFE (75 wt. %) and vinylidene fluoride PVDF (25 wt. %). It has previously been used as a PBX binder for insensitive explosives such as PBX 9502 and LX-17. 3M started production of Kel-F 800 in 1957 and small-scale batches continued to be made until 2002 when production ceased due to environmental concerns regarding one of the emulsifiers used during production. Around 2000 the Kel-F 800 name was changed to FK-800 to avoid trademark concerns because rights to produce another polymer with a similar tradename (Kel-F 81) had been sold to another manufacturer. The Kel designation came from the original manufacturer of PCTFE (Kel-F 81), the Kellog company. To avoid confusion this document will only refer to Kel-F 800. In 2006, production of small-scale batches of Kel-F 800 was started again by 3M in response to customer enquiries. This new material, the first blended batch is referred to as LOT 1, was produced with a different emulsifier than used previously. Because Kel-F 800 is made in a small batch reactor, considerable variation in crystallinity can be expected from lot to lot and year to year. In many ways, this is not significant since the material is dissolved in a solvent (often MEK, ethylmethyl ketone or ethyl acetate) for PBX production purposes. This destroys the as received crystallinity and the resulting crystallinity in the processed material is a function of polymer molecular weight and thermal history. Producing large billets of Kel-F 800 from solvent extraction is not practical and so a compression molding technique has been used above the melting temperature. This method also removes residual crystallinity from the supplied granules. The molecular weight of a polymer can be estimated by several techniques, the most common being gel permittivity chromatography (GPC), size exclusion chromatography (SEC) and shear rheometry measurements of polymer/solvent solutions. Changes in molecular weight will affect the crystallization rate and the maximum crystallinity reached for a specific thermal history. Both references agree that the new LOT 1 material molecular weight falls within the deviation found from averaging previous historical lots of Kel-F 800.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗