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At least 109 records · Page 6

Transitions between electron emission and gas breakdown mechanisms across length and pressure scales

This Perspective outlines theoretical, simulation, and experimental studies linking electron emission and gas breakdown. Many studies have investigated field emission-driven microscale gas breakdown, including recent reviews [Garner et al., IEEE Trans. Plasma Sci. 48, 808–824 (2020); Fu et al., Plasma Res. Express 2, 013001 (2020)]. This Perspective focuses on generalizing field emission-driven microscale gas breakdown to consider the contribution of other forms of electron emission, specifically thermionic and space-charge limited. Recent theoretical studies have unified thermionic, field, and space-charge limited emission with and without collisions to derive “nexuses” where the individual solutions match, indicating transitions in the mechanisms. Reducing device size to nanoscale at atmospheric pressure leads to a transition from field emission to space-charge limited emission for nitrogen at ~250 nm. This Perspective summarizes the derivation of these nexuses and future extensions. We next describe simulation and theoretical studies for field emission-driven microscale gas breakdown and highlight how the nexus theory may be integrated to account for temperature, space-charge, and pulse parameters. Finally, we summarize the development of optical techniques to assess microscale gas breakdown and recent nanoscale experiments at atmospheric pressure that suggest that space-charge may begin to contribute to field emission prior to gas breakdown. We highlight the combination of theory, simulation, and experiment to link electron emission and gas breakdown mechanisms across length, pressure, and temperature scales for applications that include vacuum electronics, pulsed power, and medicine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗

Vulnerable window of yield strength for swelling-driven fracture of phase-transforming battery materials

Abstract Despite numerous experimental and theoretical investigations of the mechanical behavior of high-capacity Si and Ge Li-ion battery anodes, our basic understanding of swelling-driven fracture in these materials remains limited. Existing theoretical studies have provided insights into elasto-plastic deformations caused by large volume change phase transformations, but have not modeled fracture explicitly beyond Griffith’s criterion. Here, we use a multi-physics phase-field approach to model self-consistently anisotropic phase transformation, elasto-plastic deformation, and crack initiation and propagation during lithiation of Si nanopillars. Our computational results reveal that fracture occurs within a “vulnerable window” inside the two-dimensional parameter space of yield strength and fracture energy and highlight the importance of taking into account the surface localization of plastic deformation to accurately predict the magnitude of tensile stresses at the onset of fracture. They further demonstrate how the increased robustness of hollow nanopillars can be understood as a direct effect of anode geometry on the size of this vulnerable window. Those insights provide an improved theoretical basis for designing next-generation mechanically stable phase-transforming battery materials undergoing large volume changes.

25 ENERGY STORAGE↗

Quantum prediction of ultra-low thermal conductivity in lithium intercalation materials

Lithium-intercalated layered transition-metal oxides, Li x TMO 2, brought about a paradigm change in rechargeable batteries in recent decades and show promise for use in memristors, a type of device for future neural computing and on-chip storage. Thermal transport properties, although being a crucial element in limiting the charging/discharging rate, package density, energy efficiency, and safety of batteries as well as the controllability and energy consumption of memristors, are poorly managed or even understood yet. Here, for the first time, we employ quantum calculations including high-order lattice anharmonicity and find that the thermal conductivity κ of Li x TMO 2 materials is significantly lower than hitherto believed. More specifically, the theoretical upper limit of κ of LiCoO 2 is 6 W/m-K, 2–6 times lower than the prior theoretical predictions. Delithiation further reduces κ by 40–70% for LiCoO 2 and LiNbO 2 . Grain boundaries, strain, and porosity are yet additional causes of thermal-conductivity reduction, while Li-ion diffusion and electrical transport are found to have only a minor effect on phonon thermal transport. The results elucidate several long-standing issues regarding the thermal transport in lithium-intercalated materials and provide guidance toward designing high-energy-density batteries and controllable memristors.

25 ENERGY STORAGE↗

Achieving 5.9% elastic strain in kilograms of metallic glasses: Nanoscopic strain engineering goes macro

The ideal elastic limit is the upper bound of the achievable strength and elastic strain of solids. However, the elastic strains that bulk materials can sustain are usually below 2%, due to the localization of inelastic deformations at the lattice scale. In this study, we achieved >5% elastic strain in bulk quantity of metallic glass, by exploiting the more uniform and smaller-magnitude atomic-scale lattice strains of martensitic transformation as a loading medium in a bulk metallic nanocomposite. The self-limiting nature of martensitic transformation helps to prevent lattice strain transfer that leads to the localization of deformation and damage. This lattice strain egalitarian strategy enables bulk metallic materials in kilogram-quantity to achieve near-ideal elastic limit. This concept is verified in a model in situ bulk amorphous (TiNiFe)-nanocrystalline (TiNi(Fe)) composite, in which the TiNiFe amorphous matrix exhibits a maximum tensile elastic strain of similar to 5.9%, which approaches its theoretical elastic limit. As a result, the model bulk composite possesses a large recoverable strain of similar to 7%, a maximum tensile strength of above 2 GPa, and a large elastic resilience of similar to 79.4 MJ/m 3 . The recoverable strain and elastic resilience are unmatched by known high strength bulk metallic materials. This design concept opens new opportunities for the development of high-performance bulk materials and elastic strain engineering of the physiochemical properties of glasses.

36 MATERIALS SCIENCE↗

Extreme high-field superconductivity in thin Re films

We report the high-field superconducting properties of thin, disordered Re films via magnetotransport and tunneling density of states measurements. Films with thicknesses in the range of 9 to 3 nm had normal-state sheet resistances of ~0.2 kΩ to ~1 kΩ and corresponding transition temperatures in the range of 6 to 3 K. Tunneling spectra were consistent with those of a moderate coupling BCS superconductor. Notwithstanding these unremarkable superconducting properties, the films exhibited an extraordinarily high upper critical field. Here, we estimate their zero temperature H c2 to be more than twice the Pauli limit. Indeed, in 6-nm samples the estimated reduced critical field H c2 /T c ~ 5.6T/K is among the highest reported for any elemental superconductor. Although the sheet resistances of the films were well below the quantum resistance R Q = h/4e 2 , their H c2 's approached the theoretical upper limit of a strongly disordered superconductor for which k F ℓ ~ 1.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Entropy of the Quantum–Classical Interface: A Potential Metric for Security

Hybrid quantum–classical systems are emerging as key platforms in quantum computing, sensing, and communication technologies, but the quantum–classical interface (QCI)—the boundary enabling these systems—introduces unique and largely unexplored security vulnerabilities. This position paper proposes using entropy-based metrics to monitor and enhance security, specifically at the QCI. We present a theoretical security outline that leverages well-established information-theoretic entropy measures, such as Shannon entropy, von Neumann entropy, and quantum relative entropy, to detect anomalous behaviors and potential breaches at the QCI. By linking entropy fluctuations to scenarios of practical relevance—including quantum key distribution, quantum sensing, and hybrid control systems—we promote the potential value and applicability of entropy-based security monitoring. While explicitly acknowledging practical limitations and theoretical assumptions, we argue that entropy-based metrics provide a complementary approach to existing security methods, inviting further empirical studies and theoretical refinements that can strengthen future quantum technologies.

97 MATHEMATICS AND COMPUTING↗

From physics to fixtures to food: current and potential LED efficacy

Light-emitting diodes (LEDs) have enabled a historic increase in the conversion of electric energy to photons, but this is approaching a physical limit. The theoretical maximum efficiency occurs when all input energy is converted to energy in photosynthetic photons. Blue LEDs can be 93% efficient, phosphor-converted “whites” 76% efficient, and red LEDs 81% efficient. These improvements open new opportunities for horticultural lighting. Here we review (1) fundamental physics and efficiency of LEDs, (2) the current efficacy of LEDs, (3) the effect of spectral quality on crop yield, and (4) the potential efficacy of horticultural fixtures. Advances in the conversion of photons to yield can be achieved by optimization of spectral effects on plant morphology, which vary among species. Conversely, spectral effects on photosynthesis are remarkably similar across species, but the conventional definition of photosynthetic photons (400–700 nm) may need to be modified. The upper limit of LED fixture efficacy is determined by the LED package efficacy multiplied by four factors inherent to all fixtures: current droop, thermal droop, driver (power supply) inefficiencies, and optical losses. With current LED technology, the calculations indicate efficacy limits of 3.4 µmol J- 1 for white + red fixtures, and 4.1 µmol J -1 for blue + red fixtures. Adding optical protection from water and high humidity reduces these values by ~10%. We describe tradeoffs between peak efficacy and cost.

Agriculture↗

Experimental Demonstration of Dark‐State Metasurface Laser with Controllable Radiative Coupling

Abstract Lasing at the nanoscale using plasmonic nanoparticles offers the prospect of strong field concentration, hence strong light−matter interactions, low lasing thresholds, and ultrafast operation. However plasmonic nanoparticles suffer from high dissipative and radiative losses, the latter being rigidly tied to the shape of the nanoparticles and symmetry of their localized plasmon resonant modes. To overcome this limitation, recent theoretical work proposes using direct lasing into dark surface states to construct lasers that conceptually allow for independent implementation of the lasing state and its coherent radiation output. Here, lasing in dark resonant states of a metasurface laser and controllable coherent outcoupling of radiation with the aid of a tightly coupled, weakly radiative metasurface are demonstrated experimentally. The laser is implemented using a thin, low‐loss dielectric film supporting surface mode‐like dark dielectric bound states and the coupling metasurface is composed of small non‐resonant scatterers that controllably but weakly perturb the dark mode and turn it partially bright. Distinct far‐field signatures that can be observed experimentally for both dark and bright lasing are identified and demonstrated. The scalability of this design, here implemented for lasing in the near‐infrared, enables large‐aperture ultra‐thin coherent light sources with controllable emission from the infrared to the visible.

36 MATERIALS SCIENCE↗

Toward the analytic bootstrap of energy correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in $\mathcal{N}$ = 4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators in the multi-collinear limit with equal and unequal energy weights, where the latter are crucial ingredients for projected N -point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

jet substructure↗

Accelerated computation of lattice thermal conductivity using neural network interatomic potentials

We report with the development of the density functional theory (DFT) and ever-increasing computational capacity, an accurate prediction of lattice thermal conductivity based on the Boltzmann transport theory becomes computationally feasible, contributing to a fundamental understanding of thermal conductivity as well as a choice of the optimal materials for specific applications. However, steep costs in evaluating third-order force constants limit the theoretical investigation to crystals with high symmetry and few atoms in the unit cell. Currently, machine learning potentials are garnering attention as a computationally efficient high-fidelity model of DFT, and several studies have demonstrated that the lattice thermal conductivity could be computed accurately via the machine learning potentials. However, test materials were mostly crystals with high symmetries, and the applicability of machine learning potentials to a wide range of materials has yet to be demonstrated. Furthermore, establishing a standard training set that provides consistent accuracy and computational efficiencies across a wide range of materials would be useful. To address these issues, herein we compute lattice thermal conductivities at 300 K using neural network interatomic potentials. As test materials, we select 25 materials with diverse symmetries and a wide range of lattice thermal conductivities between 10 -1 and 10 3 Wm -1 K -1 . Among various choices of training sets, we find that molecular dynamics trajectories at 50–700 K consistently provide results at par with DFT for the test materials. In contrast to pure DFT approaches, the computational cost in the present approach is uniform over the test materials, yielding a speed gain of 2–10 folds. When a smaller reduced training set is used, the relative efficiency increases by up to ~50 folds without sacrificing accuracy significantly. The current work will broaden the application scope of machine learning potentials by establishing a robust framework for accurately computing lattice thermal conductivity with machine learning potentials.

36 MATERIALS SCIENCE↗

Exceptional strength and wear resistance in an AA7075/TiB 2 composite fabricated via friction consolidation

The friction consolidation method successfully reinforced aluminum 7075 alloy (AA7075) with high-volume fractions (12 and 24 vol%) of titanium diboride (TiB 2 ) by high pressure and severe plastic deformation at elevated temperatures. The consolidated AMCs have a uniform dispersion of submicron- and micron-sized TiB 2 particles in the AA7075 matrix, with significant refinement of the matrix grain size and the particles. The addition of TiB 2 significantly increases hardness by up to 50 %, Young’s modulus by up to 62 %, and ultimate tensile strength by up to 28 % to 672 MPa, while reducing ductility by 80 %. Wear resistance of 7075/24 vol% TiB 2 improves seven-fold compared to baseline, making it comparable to that of carburized steels. Microstructure-based finite element modeling provided a theoretical strength limit of ~730 MPa for the composites and indicated that high triaxiality in conjunction with severe equivalent plastic strain in a narrow area between the TiB 2 particles led to early fracture initiations, limiting the ductility.

36 MATERIALS SCIENCE↗

Not all fugitives are bad: The case for using them to form low tortuosity - high porosity electrodes

This work focuses on the inclusion of an insoluble fugitive phase during slurry processing to form composite battery electrodes. The fugitive phases consist of natural derived products like alginic acid, sucrose, rice and potato starch, and carrageenans such as Irish Moss and synthetic pore-formers based on polymethyl methacrylate. The fugitive phases can be anaerobically thermally removed (350 °C) during binder crosslinking and electrode drying steps, resulting in electrodes with low tortuosities (approaching theoretical Bruggemann limits for spherical particles) and high porosities approaching 80%. The resulting ∼3 mg/cm 2 loaded electrodes suffer from poor electrical connectivity, lowering the effective material utilization, but represent an approach that could be utilized for the formation of solid-state batteries with infilling of materials into well-defined pores and optimized transport pathways.

25 ENERGY STORAGE↗

Investigating the Role of Copper in Arsenic Doped Cd(Se,Te) Photovoltaics

The open circuit voltage (VOC) deficit in Cd(Se,Te)-based photovoltaics remains a critical obstacle for pushing the technology closer to theoretical performance limits. Arsenic doping has become a dominant and promising route to achieve the higher p-type carrier concentrations necessary for higher VOC, but challenges associated with this alternate defect chemistry and higher doping density have hindered progress. Here we show that while arsenic doping enables high carrier concentrations (>1016 cm-3), co-doping with copper can provide a boost to VOC without a significant change to carrier concentration. A large data set is initially used to explore current-voltage and capacitance-voltage trends associated with arsenic doped devices with and without copper. A smaller subset is then used to probe these trends using a wide variety of characterization techniques. Copper is found to facilitate reduced interface recombination and potentially improved bulk absorber characteristics, though the mechanisms for these improvements are not yet clear. Despite the improved performance of co-doped devices, VOC is still far below its potential especially for highly doped devices. Low emitter doping in conjunction with high absorber doping seems to be a plausible cause for this significant deficit, though other device properties may exacerbate this problem.

CdSeTe↗

Promoting Reversibility of Multielectron Redox in Alkali-Rich Sulfide Cathodes through Cryomilling

We report conventional cathodes for Li-ion batteries (LIBs) are reaching their theoretical capacity limits. One way to meet the growing demands for high-capacity LIBs is by developing so-called Li-rich cathode materials that greatly benefit from additional capacities from anionic moieties in the structure. Li-rich materials are intrinsically subject to higher degrees of (de)intercalation, leaving the particles more prone to fractures and thus rapid capacity fade. Alkali-rich LiNaFeS 2 reversibly cycles with capacities exceeding 300 mAh g -1 , but its capacity fades faster than an isostructural material Li 2 FeS 2 . Using synchrotron-based transmission X-ray microscopy (TXM), we demonstrate that the capacity fade of LiNaFeS 2 stems from particle fractures in the first charge cycle. We improve the cycling performance of LiNaFeS 2 by means of cryomilling, which enhances capacity retention at cycle 50 by 76%. Through crystallographic and morphological characterization techniques, we confirm that cryomilling not only decreases particle and crystallite size while increasing microstrain but also prevents particles from fracturing. Cryomilling is a powerful tool to engineer nanoscale battery materials, and TXM allows the direct observation of morphological changes of the particles, which can be leveraged to develop next-generation cathode materials for LIBs.

25 ENERGY STORAGE↗

Characterization of Carrier Cooling Bottleneck in Silicon Nanoparticles by Extreme Ultraviolet (XUV) Transient Absorption Spectroscopy

Silicon nanoparticles have the promise to surpass the theoretical efficiency limit of single-junction silicon photovoltaics by the creation of a “phonon bottleneck,” a theorized slowing of the cooling rate of hot optical phonons that in turn reduces the cooling rate of hot carriers in the material. Verifying the presence of a phonon bottleneck in silicon nanoparticles requires simultaneous resolution of electronic and structural changes at short timescales. Here, extreme ultraviolet transient absorption spectroscopy is used to observe the excited-state electronic and lattice dynamics in polycrystalline silicon nanoparticles following 800 nm photoexcitation, which excites carriers with 0.35 ± 0.03 eV excess energy above the Δ 1 conduction band minimum. The nanoparticles have nominal 100 nm diameters with crystalline grain sizes of about ~16 nm. The extracted carrier–phonon and phonon–phonon relaxation times of the nanoparticles are compared to those for a silicon (100) single-crystal thin film at similar carrier densities (2 × 10 19 cm –3 for the nanoparticles and 6 × 10 19 cm –3 for the film). The measured carrier–phonon and phonon–phonon scattering lifetimes for the polycrystalline nanoparticles are 870 ± 40 fs and 17.5 ± 0.3 ps, respectively, versus 195 ± 20 fs and 8.1 ± 0.2 ps, respectively, for the silicon thin film. Furthermore, the reduced scattering rates observed in the nanoparticles are consistent with the phonon bottleneck hypothesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay of Surface and Interior Modes in Exciton–Phonon Coupling at the Nanoscale

Exciton-phonon coupling (EXPC) plays a key role in the optoelectronic properties of semiconductor nanocrystals (NCs), but a microscopic picture of EXPC is still lacking, particularly regarding the magnitude and scaling with NC size, the dependence on phonon frequency, and the role of the NC surface. The computational complexity associated with accurately describing excitons and phonons has limited previous theoretical studies of EXPC to small NCs, noninteracting electron-hole models, and/or a small number of phonon modes. We develop an atomistic approach for describing EXPC in NCs of experimentally relevant sizes. We validate our approach by calculating the reorganization energies, a measure of EXPC, for CdSe and CdSe-CdS core-shell NCs, finding good agreement with experimental measurements. We demonstrate that exciton formation distorts the NC lattice primarily along the coordinates of low-frequency acoustic modes. Modes at the NC surface play a significant role in smaller NCs while interior modes dominate for larger systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

In Silico Discovery of Multistep Chemistry Initiated by a Conical Intersection: The Challenging Case of Donor–Acceptor Stenhouse Adducts

Detailed mechanistic understanding of multistep chemical reactions triggered by internal conversion via a conical intersection is a challenging task that emphasizes limitations in theoretical and experimental techniques. We present a discovery-based, hypothesis-free computational approach based on first-principles molecular dynamics to discover and refine the switching mechanism of donor–acceptor Stenhouse adducts (DASAs). We simulate the photochemical experiment in silico, following the “hot” ground state dynamics for 10 ps after photoexcitation. Using state-of-the-art graphical processing units-enabled electronic structure calculations we performed in total ~2 ns of nonadiabatic ab initio molecular dynamics discovering (a) critical intermediates that are involved in the open-to-closed transformation, (b) several competing pathways which lower the overall switching yield, and (c) key elements for future design strategies. Finally, our dynamics describe the natural evolution of both the nuclear and electronic degrees of freedom that govern the interconversion between DASA ground-state intermediates, exposing significant elements for future design strategies of molecular switches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗