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At least 325 records · Page 18

Visualizing the SEI formation between lithium metal and solid-state electrolyte

The solid electrolyte interphase (SEI) is regarded as the most important factor affecting the durability of lithium-metal anode in all-solid-state batteries (ASSBs). Despite its significance, the nucleation and growth mechanism of SEI is not yet well understood. Here, we elucidate the thermodynamics and kinetics governing SEI formation at the Li|β-Li 3 PS 4 interface at the atomic scale via thermodynamic phase equilibrium analysis and machine-learning-potential-assisted molecular dynamics (MD) simulations. An accurate moment tensor potential using the machine-learning method is developed for a reactive model of Li|β-Li 3 PS 4 . This potential enabled us to perform large-scale MD simulations with the model size expanded to the experimental dimensions (~40 nm) while maintaining the same level of accuracy as density functional theory calculations. The results reveal a four-stage evolution process at the Li|β-Li 3 PS 4 interface, namely (i) fast ion diffusion, (ii) nucleation, (iii) Li 2 S growth, and (iv) stabilization. Notably, we demonstrate that the SEI can be categorized into crystalline and amorphous regions. The simulated SEI thickness, structure, and composition closely match experimental findings, validating the accuracy of the MD simulations. We further disclose the significant impact of ion diffusion kinetic limitations on the phase formation and crystallization of interfacial products. Furthermore, we shed light on the detailed potential energy (PE) distribution of lithium along the direction perpendicular to the interface. Finally, this information is crucial for better understanding interfacial ion mobility.

25 ENERGY STORAGE↗

Monte Carlo modeling of spin-polarized photoemission from p -doped bulk GaAs

Here, the anticorrelation between quantum efficiency (QE) and electron spin polarization (ESP) from a ρ-doped GaAs activated to negative electron affinity is studied in detail using an ensemble Monte Carlo approach. The photoabsorption, momentum and spin relaxation during transport, and tunneling of electrons through the surface potential barrier are modeled to identify fundamental mechanisms, which limit the efficiency of GaAs spin-polarized electron sources. In particular, we study the response of QE and ESP to various parameters, such as the photoexcitation energy, doping density, and electron affinity level. Our modeling results for various transport and emission characteristics are in good agreement with available experimental data. Our findings show that the behavior of both QE and ESP at room temperature can be fully explained by the bulk relaxation mechanisms and the time that electrons spend in the material before being emitted.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials

We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unraveling H2 chemisorption and physisorption on metal decorated graphene using quantum Monte Carlo

Molecular hydrogen has the potential to significantly reduce the use of carbon dioxide emitting energy processes. However, hydrogen gas storage is a major bottleneck for its large-scale use as current storage methods are energy intensive. Among different storage methods, physisorbing molecular hydrogen at ambient pressure and temperatures is a promising alternative—particularly in light of the advancements in tunable lightweight nanomaterials and high throughput screening methods. Nonetheless, understanding hydrogen adsorption in well-defined nanomaterials remains experimentally challenging and reference information is scarce despite the proliferation of works predicting hydrogen adsorption. We focus on Li, Na, Ca, and K, decorated graphene sheets as substrates for molecular hydrogen adsorption, and compute the most accurate adsorption energies available to date using quantum diffusion Monte Carlo (DMC). Building on our previous insights at the density functional theory (DFT) level, we find that a weak covalent chemisorption of molecular hydrogen, known as Kubas interaction, is feasible on Ca decorated graphene according to DMC, in agreement with DFT. This finding is in contrast to previous DMC predictions of the 4H2/Ca+ gas cluster (without graphene) where chemisorption is not favored. However, we find that the adsorption energy of hydrogen on metal decorated graphene according to a widely used DFT method is not fully consistent with DMC. The reference adsorption energies reported herein can be used to find better work-horse methods for application in large-scale modeling of hydrogen adsorption. Furthermore, the implications of this work affect strategies for finding suitable hydrogen storage materials and high-throughput methods.

Chemistry↗

Metal–bicarbonate ion pairing in alkaline aqueous solutions from multilevel embedded correlated wavefunction theory and molecular dynamics

In this work, we examine ion-pairing mechanisms of bicarbonates in alkaline aqueous solutions with the divalent metal ions most abundantly present in seawater, namely, Ca 2+ and Mg 2+ . We employ a rare-event enhanced sampling approach within first-principles molecular dynamics to explore regions of phase space spanning solvent-shared to contact ion pairs. Second-order Møller–Plesset perturbation theory (MP2) corrections are subsequently applied in an embedding framework (EMB) to refine the electronic structure of stationary states and associated reaction barriers along the free-energy profiles while retaining the extended solvent effects at the density functional theory (DFT) level. Ca 2+ –HCO 3 − was previously hypothesized to exist in a solvent-shared ion pair (SSHIP) by DFT studies with an endergonic contact ion pair (CIP) formation; however, our EMB-MP2 refinement of the DFT ion-pairing pathways reveals that Ca 2+ and HCO 3 − form a virtually barrier-free CIP in alkaline solutions, with even more energetic ease than the widely studied Ca–CO 3 ion pair. We find qualitative agreement between DFT and EMB-MP2 for Mg 2+ —unlike Ca 2+ , Mg 2+ refuses to shed its strong hydration shell, thereby preferring a SSHIP state with a significant activation barrier to crossover to the CIP forms—a trait reminiscent of ion pairing in Mg–CO 3 and closely related to the kinetic limitations underlying the famous subject of the dolomite problem. Our study highlights the importance of improved electronic structure descriptions of liquids, modeled as a condensed phase of matter lacking in long-range crystalline order. It also strongly suggests that Ca 2+ –HCO 3 − CIPs are likely precursors involved in prenucleation of CaCO 3 mineral formation in seawater.

Sharma, Vidushi [Princeton Plasma Physics Laborato↗

Pressure-induced nonmonotonic cross-over of steady relaxation dynamics in a metallic glass

Relaxation dynamics, as a key to understand glass formation and glassy properties, remains an elusive and challenging issue in condensed matter physics. In this work, in situ high-pressure synchrotron high-energy X-ray photon correlation spectroscopy has been developed to probe the atomic-scale relaxation dynamics of a cerium-based metallic glass during compression. Although the sample density continuously increases, the collective atomic motion initially slows down as generally expected and then counterintuitively accelerates with further compression (density increase), showing an unusual nonmonotonic pressure-induced steady relaxation dynamics cross-over at ~3 GPa. Furthermore, by combining in situ high-pressure synchrotron X-ray diffraction, the relaxation dynamics anomaly is evidenced to closely correlate with the dramatic changes in local atomic structures during compression, rather than monotonically scaling with either sample density or overall stress level. In conclusion, these findings could provide insight into relaxation dynamics and their relationship with local atomic structures of glasses.

36 MATERIALS SCIENCE↗

Photoionization of endohedral molecules: N 2 @C 60

Calculations of the photoionization of the nitrogen $1σ_g$, $1σ_u$, and $2σ_g$, states of the N 2 @C 60 molecule are performed at the density functional theory (DFT) level taking full account of the molecular geometry of both N 2 and the C 60 . In this work, the results show that cross sections are sensitive to the parity of the final channels, with a complex interplay between the native $σ_u$ resonance in free N 2 and confinement resonances. A quite different behavior is obtained for the asymmetry parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

Intentional carbon doping reveals CH as an abundant charged impurity in nominally undoped synthetic WS 2 and WSe 2

Understanding the physical properties and controlling the generation of intrinsic and extrinsic defects is central to the technological adoption of 2D materials in devices. Here we identify a charged carbon-hydrogen complex at a chalcogen site (CH X ) as a common, charged impurity in synthetically grown transition metal dichalcogenides (TMDs). This conclusion is drawn by comparing high resolution scanning probe microscopy measurements of nominally undoped and intentionally carbon doped TMD samples. While CH impurity densities in undoped CVD-grown WS 2 and MOCVD-grown WSe 2 can range anywhere from parts per million to parts per thousand, CH densities in the percentage levels were selectively generated by a post-synthetic methane plasma treatment. Our study indicates that methane plasma treatment is a selective and clean method for the controlled introduction of a charged carbon-hydrogen complex at a surface chalcogen site, adefect that is commonly present in synthetic TMDs.

36 MATERIALS SCIENCE↗

Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning

Abstract Artificial intelligence and machine learning (AI/ML) can be used to automatically analyze large image datasets. One valuable application of this approach is estimation of plant trait data contained within images. Here we review 39 papers that describe the development and/or application of such models for estimation of stomatal traits from epidermal micrographs. In doing so, we hope to provide plant biologists with a foundational understanding of AI/ML and summarize the current capabilities and limitations of published tools. While most models show human-level performance for stomatal density (SD) quantification at superhuman speed, they are often likely to be limited in how broadly they can be applied across phenotypic diversity associated with genetic, environmental, or developmental variation. Other models can make predictions across greater phenotypic diversity and/or additional stomatal/epidermal traits, but require significantly greater time investment to generate ground-truth data. We discuss the challenges and opportunities presented by AI/ML-enabled computer vision analysis, and make recommendations for future work to advance accelerated stomatal phenotyping.

Plant Sciences↗

Optical response and band structure of LiCoO 2 including electron-hole interaction effects

The optical response functions and band structures of LiCoO 2 are studied at different levels of approximation, from density functional theory (DFT) in the generalized gradient approximation (GGA) to quasiparticle self-consistent QSGW (with G for Green's function and W for screened Coulomb interaction) without and with ladder diagrams ($QSG\hat{W}$) and the Bethe Salpeter Equation (BSE) approach. The QSGW method is found to strongly overestimate the band gap and electron-hole or excitonic effects are found to be important. They lower the quasiparticle gap by only about 11~\% but the lowest energy peaks in absorption are found to be excitonic in nature. The contributions from different band to band transitions and the relation of excitons to band-to-band transitions are analyzed. Finally, the excitons are found to be strongly localized. Finally, a comparison to experimental data is presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Landscape of nuclear deformation softness with spherical quasiparticle random-phase approximation

We investigate the stability and softness of nuclei against quadrupole, octupole, and hexadecapole deformation. By applying the spherical Skyrme-force Hartree-Fock Bardeen-Cooper-Schrieffer quasiparticle random phase approximation, we diagnose ground-state deformation when imaginary solutions are obtained, i.e., the spherical ground state collapses. We also calculate the multipole polarizability in spherical nuclei with no collapse, as a measure of softness. This numerically light and theoretically sound method is found able to capture deformation patterns across the nuclide chart. As a result, the connection between the intrinsic shape of nuclei and the dynamics of their low-lying collective states is established and the role of shell structure is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantum Computing for AI-based Design and Optimization of Electric Motors

Knowledge-based artificial intelligence and hierarchical fuzzy logic offer an interpretable framework for electricvehicle motor preliminary design, but their computational burden grows with linguistic granularity and coupled design-space size. This paper presents a reduced quantum reformulation of the hierarchical fuzzy inference of air-gap flux density, a representative level-one motor-design parameter. Starting from the published electric-vehicle motor-design framework, a three-term fuzzy prototype is constructed from the original inference structure. The reduced model is then reformulated as a modular quantum register-oracle system, in which each hierarchical subrelation is encoded as a block oracle and evaluated through superpositionbased candidate-label testing. The proposed modular quantum formulation reproduces the reduced classical prototype after block fusion. A resource analysis shows that the reduced modular system requires seven qubits per block and twenty-two qubits in a straightforward four-block implementation. Finally, a crossovercomplexity model is derived to identify the regime in which quantum candidate search may become favorable relative to hierarchical fuzzy inference. The results show that no quantum advantage should be claimed for the present one-output reduced benchmark, but that a plausible crossover emerges for larger joint candidate spaces and higher linguistic granularity. The work therefore establishes a technically consistent starting point for future quantum-assisted electric-vehicle motor-design optimization.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗

Water use of co‐occurring loblolly ( Pinus taeda ) and shortleaf ( Pinus echinata ) in a loblolly pine plantation in the Piedmont

Abstract Measuring water use in co‐occurring loblolly pine (Pinus taedaL.) and shortleaf pine (Pinus echinataMill.) enhances our understanding of their competitive water use and aids in refining watershed water budget model parameters. This study was conducted in a 12‐ha forested headwater catchment in the Piedmont of North Carolina, southeastern U.S., from 2018 to 2019 (pre‐thinning) to 2020 (post‐thinning). Sap flux density (J s ), species‐level transpiration (T s ), and watershed‐level transpiration (T w ) were quantified. Water use efficiency (WUE) in loblolly and shortleaf pines was compared, alongside an investigation into how both species'J s andT s responded to atmospheric vapor pressure deficit (VPD). Loblolly pine had 19%–36% higherJ s than shortleaf pine. DailyT s for loblolly pine ranged from 15.0 to 29.0 L/day whileT s in shortleaf pine ranged from 3.0 to 6.8 L/day. TheT s was significantly higher in loblolly pine when compared to shortleaf pine likely due to higher canopy position and higher growth rates of the former. WUE, defined by annual tree biomass growth per tree water use, was not significantly different between the two. DailyJ s andT s in both species responded nonlinearly to VPD, with loblolly pine being more sensitive and variable. Species‐specific water use should be considered when quantifyingT w and developing reliable models to predict the effects of forest management practices on water resources.

Engineering↗

Trojan horse method as an indirect approach to study resonant reactions in nuclear astrophysics

The primary goal of the Trojan horse method (THM) is to analyze resonant rearrangement reactions when the density of the resonance levels is low and statistical models cannot be applied. The main difficulty of the analysis is related with the facts that in the final state the THM reaction involves three particles and that the intermediate particle, which is transferred from the Trojan horse particle to the target nucleus to form a resonance state, is virtual. Another difficulty is associated with the Coulomb interaction between the particles, especially, taking into account that the goal of the THM is to study resonant rearrangement reactions at very low energies important for nuclear astrophysics. The exact theory of such reactions with three charged particles is very complicated and is not available. This is why different approximations are used to analyze THM reactions. In this review paper we describe a new approach based on a few-body formalism that provides a solid basis for deriving the THM reaction amplitude taking into account rescattering of the particles in the initial, intermediate and final states of the THM reaction. Since the THM uses a two-step reaction in which the first step is the transfer reaction populating a resonance state, we address the theory of the transfer reactions. The theory is based on the surface-integral approach and R-matrix formalism. We also discuss application of the THM to resonant reactions populating both resonances located on the second energy sheet and subthreshold resonances, which are subthreshold bound states located at negative energies close to thresholds. We consider the application of the THM to determine the astrophysical factors of resonant radiative-capture reactions at energies so low that direct measurements can hardly be performed due to the negligibly small penetrability factor in the entry channel of the reaction. Here, we elucidated the main ideas of the THM and outline necessary conditions to perform the THM experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

A Redox-Electrodialysis Model with Zero Fitting Parameters: Insights into Process Limitations, Design, and Material Interventions

Redox-Electrodialysis (r-ED) is an electrochemical desalination cell architecture that has recently received considerable interest, due to its low energy demand relative to electrochemical desalination technologies that rely on electrode-based ion removal. To further improve the energy efficiency of r-ED, we developed a lumped mathematical model with no adjustable parameters to investigate the various sources of overpotential within the cell. Existing models of electrodialysis and r-ED cells either do not accurately incorporate all phenomena contributing to the overpotential or utilize empirical fitting parameters. The model developed here indicates that ohmic overpotentials, especially in the diluate chamber, are the most significant contributors to energy losses. Based on this insight, we hypothesized that adding an ion exchange resin wafer in the diluate compartment would increase the ionic conductivity and decrease the energy demand. Experimental results showed an 18% reduction in specific energy use while achieving the same degree of salt removal (20 mM to 12 mM). Furthermore, the resin wafer enabled complete desalination to potable drinking levels at a current density previously unachievable within practical operating voltage limits (4.93 mA cm -2 ). We also expanded the model to explore differences in r-ED energy use between configurations using multiple cells and a single cell with increased area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

Chisholm, Paul J. (ORCID:0000000238784707)↗

MODELING OF ENHANCED AIR DEHUMIDIFICATION THROUGH ELECTRICALLY CHARGED VAPOR CAPTURING ELECTROSTATIC DROPLETS

This paper investigated the potential of a new electrostatic-based water vapor separation system for humidity control in buildings. The Electrospray Vortical Flow eXchanger (EVFX) consists of small electrically charged water droplets released inside air vortexes to attract water vapor molecules, effectively wiping out the humidity from the air. Larger droplets are then removed at the outer wall of the vortex. If a water molecule is placed in a gradient electric field, such a polar molecule experiences a dielectrophoresis force, which moves the molecules and produces a vapor concentration gradient. When the vapor density exceeds the saturation level, nucleation occurs. A thermodynamic model that captures this phenomenon was described in this paper. Electrosprayed droplets were initially charged close to their maximum electrical charge dictated by the Rayleigh limit; these droplets were used as nucleation centers. The high electric charge decreased the pressure of the vapor, which was in equilibrium with the droplets. This enhanced the charged droplets' nucleation and growth that depleted the vapor phase near the droplets, which was compensated for by the dielectrophoresis flow and diffusion. Significant water vapor condensation was predicted for small droplets at a high electrical charge. Beyond a specific droplet size, while the condensation of water vapor was still theoretically possible, it was somewhat limited because the further growth of the large charged droplets was inhibited due to their high inherent water vapor pressure near the surface. A case study illustrated the potentials and limitation of the EVFX for droplets charged to the Rayleigh limit, for which the effective range of diameters resulted between 10 nm up to few micron.

Morcelli, Stefano↗

Adaptive Machine Learning for Bragg Coherent Diffraction Imaging (BCDI) of 3D Electron Density Maps with Application to La 2-x Ba x CuO 4 (LBCO) High Temperature Superconductor Studies [PowerPoint]

Understanding mesoscale heterogeneity is important for evaluating fatigue and failure of structural materials and for manufacturing processes. Data-driven tools can facilitate in guiding effort investment (measurements and computations) at various stages of the materials development. Our 3D reconstruction approach is to find a set of coefficients which define a bounding surface of the electron density. Data for training the 3D CNN was generated by sampling coefficients from uniform distributions. Test vs. prediction values are shown for the 28 even-valued coefficients for 1000 test structures, with the best and worst performers highlighted. The adaptive part of this work utilized a model independent extremum seeking (ES). The predictions of the CNN were used as the starting point for the ES algorithm. The convergence of the ES algorithm for 3 different structures is illustrated, and the robustness of the adaptive ML approach was demonstrated on experimentally measured 3D crystal from high energy diffraction microscopy. Reconstruction of a non-uniform density volume with different levels of Poisson noise is also shown. Preliminary attempts at reconstructing measured La 2-x Ba x CuO 4 diffraction patterns have so far failed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗