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At least 343 records · Page 19

HPC4Mfg with Sepion

We employed ab-initio simulations and quantum chemical calculations to develop a computational framework for simulating the microscopic structure and mechanical properties of novel polymer membranes used in lithium sulfur batteries. To meet industry targets, next generation batteries with high specific energy (Wh/kg) are essential. Efforts to commercialize light-weight, energy-dense lithium-sulfur secondary batteries (2510 Wh/kg) have been stalled by ongoing problems with the battery’s separator membrane, which should prevent cross-over of active material from cathode to anode that, if unchecked, limits cycle-life. However, Sepion Technologies’ polymer membranes yield long-lasting lithium-sulfur cells. Advancing to 10 Ah battery prototypes, Sepion faces challenges in membrane manufacturing related to polymer processing and the molecular basis for membrane performance and durability. High performance computing offers critical new insight into these phenomena, which in turn will accelerate product entry into the market.

25 ENERGY STORAGE↗

Energy storage in magnetic textures driven by vorticity flow

Here, an experimentally feasible energy-storage concept is formulated based on vorticity (hydro)dynamics within an easy-plane insulating magnet. The free energy associated with the magnetic winding texture is built up in a circular easy-plane magnetic structure by injecting a vorticity flow in the radial direction. The latter is accomplished by electrically induced spin-transfer torque, which pumps energy into the magnetic system in proportion to the vortex flux. The resultant magnetic metastable state with a finite winding number can be maintained indefinitely because the process of its relaxation via phase slips is exponentially suppressed when the temperature is brought well below the Curie temperature. We characterize the vorticity-current interaction underlying the energy-loading mechanism through its contribution to the effective electric inductance in the rf response. Our proposal may open an avenue for naturally powering spintronic circuits and nontraditional magnet-based neuromorphic networks.

36 MATERIALS SCIENCE↗

Sandia Academic Alliance Program Collaboration Report: 2020-2021 Accomplishments

University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Spectroscopic Identification of Carbamate Formation and Synergistic Binding in Amide–CO$^{–}_{2}$ Complexes

Carbamate formation is an elementary step that governs nitrogencentered nucleophilic CO 2 capture across diverse environments, yet a direct, structure-specific understanding has been lacking. Here, we report the first gas-phase characterization of closed-shell carbamate formation by deprotonated amides, using cryogenic ion trap vibrational spectroscopy combined with quantum chemical calculations. Reactions of deprotonated benzamide and isophthalamide anions with CO 2 form carbamate species, with the amide nitrogen serving as the nucleophilic site. Diagnostic, strongly red-shifted antisymmetric CO 2 stretching vibrational bands, supported by a bonding analysis, establish chemisorption with substantial charge transfer. In the multiamide system, an intramolecular N−H···O hydrogen bond provides synergistic stabilization, correlating with larger red shifts and more exothermic binding. These structure-assigned benchmarks provide molecular-level insights into the binding motif, charge redistribution, and hydrogen bond-mediated stabilization of amide carbamates, which aid the characterization of carbamate formation in condensed phase.

Amides↗

Beyond Thermodynamics: Assessing the Dynamical Softness of Hydrated Ions from First Principles

Ion (de)hydration is a key rate-determining step in interfacial processes from corrosion to electrochemical energy storage. However, predicting the kinetics of ion (de)hydration remains challenging, prompting the use of static proxies such as hydration energy and valence. While useful for assessing thermodynamic preferences, such descriptors cannot fully capture the dynamical softness of the hydration shell that dictates kinetics. Accordingly, we use first-principles molecular dynamics to analyze hydration shell softness for a diverse set of metal cations. Additionally, three dynamic metrics are introduced to intuitively describe the bond rigidity, shape deformability, and exchange fluidity of the solvation shell. Together, these metrics capture the relevant physics in the static descriptors, while offering a far more complete and efficient representation for the overall propensity for (de)hydration. Application to the hydrated ion set demonstrates a weak connection between dynamical softness and hydration energy, confirming that dynamical descriptors of hydration are key for correctly describing ion transfer processes.

36 MATERIALS SCIENCE↗

Ferroelectrically switched valley-dependent transmission in SnTe-PbTe-SnTe monolayer lateral heterostructures

A special class of valleytronic two-dimensional (2D) semiconductors possesses carrier pockets (i.e., valleys) along certain directions in the first Brillouin zone, which can be applied as a new degree of freedom for information storage and processing. Here we show that members of this family that are ferroelectric allow the location of these valleys to be switched by rotating the ferroelectric polarization. This makes possible the control of electronic state transmission probability through an energy barrier by ferroelectrically switching the polarization direction, thereby creating or eliminating valley matching in reciprocal space. We apply molecular beam epitaxy to grow lateral sandwich heterostructures with monolayer-thick ferroelectric SnTe separated by nanometer-wide paraelectric PbTe as the barriers. Using scanning tunneling microscopy, we show that the transmission probability of the 2D hole states at the valence band maximum of SnTe monolayer strongly relies on the relative orientation between the polarization directions of the two SnTe electrodes. The transmission can be switched from a suppressed state to a permitted state by rotating the ferroelectric polarization of one SnTe electrode by 90 degrees. Our work demonstrates the electric-field-control of valley locations and its potential for tunnel junction valleytronic devices.

electronic devices↗

Measurement of the muon anomalous precession frequency at the Muon g − 2 Experiment at Fermilab

The anomalous magnetic moment of the muon, $a_\mu = \frac{g-2}{2}$ is the fractional deviation of the muon $g$-factor from the value of 2. It emerges as the cumulative effect of the virtual particles participating in the muon interaction with a magnetic field via quantum loop corrections. Its value encodes all the possible interactions between the virtual particles and, for this reason, represents an important test of the Standard Model (SM). In particular, any deviation from the SM theoretical evaluation could be due to new physics contributions. The new Muon $g-2$ (E989) Experiment at Fermilab is currently operating to repeat and improve the previous E821 experiment at Brookhaven National Laboratory (BNL), aiming to reduce the experimental error by a factor of 4 to the final accuracy of 140 parts per billion (ppb). On April 7th, 2021, the E989 collaboration published the first result based on the first year of data taking (Run-1), measuring $a_\mu = 0.001~165~920~40(54)$ with a precision of 460 ppb. The measured value is consistent with the BNL measurement and strengthens the long-standing tension with the data-driven SM prediction to a combined discrepancy of 4.2$\sigma$. On the theory side, however, new efforts involving lattice-QCD techniques are starting to question the current consensus on the theoretical prediction, demanding new improvements on both the experimental and theoretical sides. The E989 collaboration is now finalizing the analysis of Run-2 and Run-3 data and a new publication is expected in the first half of 2023 with a combined statistical uncertainty of 200 ppb. The anomalous magnetic moment $a_\mu$ is measured as the ratio between the muon spin anomalous precession frequency, $\omega_a$, and the average magnetic field experienced by the muons as they circulate in the storage ring. This thesis presents a precession frequency analysis of the Run-1 data and an evaluation of the related systematic uncertainties. A new positron reconstruction developed for the analysis of the subsequent data-taking periods, aiming to reduce some of the major systematic uncertainties of the $\omega_a$ measurement, is presented. The author's involvement in the production of the Run-2/5 data and in the precise calibration of the detectors is discussed. Finally, the complete Run-1 $a_\mu$ result is presented.

43 PARTICLE ACCELERATORS↗

Dynamic Promotion of the Oxygen Evolution Reaction via Programmable Metal Oxides

Hydrogen gas is a promising renewable energy storage medium when produced via water electrolysis, but this process is limited by the sluggish kinetics of the anodic oxygen evolution reaction (OER). Herein, we used a microkinetic model to investigate promoting the OER using programmable oxide catalysts (i.e., forced catalyst dynamics). We found that programmable catalysts could increase current density at a fixed overpotential (100–600× over static rates) or reduce the overpotential required to reach a fixed current density of 10 mA cm –2 (45–140% reduction vs static). In our kinetic parametrization, the key parameters controlling the quality of the catalytic ratchet were the O*-to-OOH* and O*-to-OH* activation barriers. Furthermore, our findings indicate that programmable catalysts may be a viable strategy for accelerating the OER or enabling lower-overpotential operation, but a more accurate kinetic parametrization is required for precise predictions of performance, ratchet quality, and resulting energy efficiency.

Catalysts↗

Simultaneous measurement of the exchange parameter and saturation magnetization using propagating spin waves

The exchange interaction in ferromagnetic ultra thin films is a critical parameter in magnetization-based storage and logic devices, yet the accurate measurement of it remains a challenge. While a variety of approaches are currently used to determine the exchange parameter, each has its limitations, and good agreement among them has not been achieved. To date, neutron scattering, magnetometry, Brillouin light scattering, spin-torque ferromagnetic resonance spectroscopy, and Kerr microscopy have all been used to determine the exchange parameter. Here, we present a method that exploits the wavevector selectivity of Brillouin light scattering to measure the spin wave dispersion in both the backward volume and Damon–Eshbach orientations. The exchange, saturation magnetization, and magnetic thickness are then determined by a simultaneous fit of both dispersion branches with general spin wave theory without any prior knowledge of the thickness of a magnetic “dead layer.” In this study, we demonstrate the strength of this technique for ultrathin metallic films, typical of those commonly used in industrial applications for magnetic random-access memory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Observation of skyrmion bubbles in multilayer [Pt/Co/Cu] n using spin-polarized STM

Magnetic multilayers are a promising platform for storage and logic devices based on skyrmion spin textures, due to the large materials phase space for tuning properties. Epitaxial superlattice structures of [Pt/Co/Cu]n thin films were grown by molecular beam epitaxy at room temperature. Spin-polarized scanning tunneling microscopy (SP-STM) of these samples was used to probe the connection between surface structure and skyrmion morphology with nanoscale spatial resolution. Irregular-shaped skyrmion bubbles were observed, with effective diameters from 20 to 200 nm that are much larger than the nanoscale grain structure of the surface topography. Nucleation, annihilation, and motion of skyrmion bubbles could be driven using the stray field of the ferromagnetic tip in repeated imaging, and spin-polarized current/voltage pulses. Furthermore, our detailed comparison of STM topography and differential conductance images shows that there are no surface defects or inhomogeneities at length scales that could account for the range in skyrmion bubble size or shape observed in the measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deep learning-based quasi-continuum theory for structure of confined fluids

Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfacial structure of fluids. In this work, we develop a deep learning-based quasi-continuum theory (DL-QT) to predict the concentration and potential profiles of a Lennard-Jones (LJ) fluid and water confined in a nanochannel. The deep learning model is built based on a convolutional encoder–decoder network (CED) and is applied for high-dimensional surrogate modeling to relate the fluid properties to the fluid–fluid potential. The CED model is then combined with the interatomic potential-based continuum theory to determine the concentration profiles of a confined LJ fluid and confined water. Further, we show that the DL-QT model exhibits robust predictive performance for a confined LJ fluid under various thermodynamic states and for water confined in a nanochannel of different widths. The DL-QT model seamlessly connects molecular physics at the nanoscale with continuum theory by using a deep learning model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sustainable Electric Vehicle Batteries for a Sustainable World: Perspectives on Battery Cathodes, Environment, Supply Chain, Manufacturing, Life Cycle, and Policy

Abstract Li‐ion batteries (LIBs) can reduce carbon emissions by powering electric vehicles (EVs) and promoting renewable energy development with grid‐scale energy storage. However, LIB production and electricity generation still heavily rely on fossil fuels at present, resulting in major environmental concerns. Are LIBs as environmentally friendly and sustainable as expected at the current stage? In the past 5 years, a skyrocketing growth of the EV market has been witnessed. LIBs have garnered huge attention from academia, industry, government, non‐governmental organizations, investors, and the general public. Tremendous volumes of LIBs are already implemented in EVs today, with a continuing, exponential growth expected for the years to come. When LIBs reach their end‐of‐life in the next decades, what technologies can be in place to enable second‐life or recycling of batteries? Herein, life cycle assessment studies are examined to evaluate the environmental impact of LIBs, and EVs are compared with internal combustion engine vehicles regarding environmental sustainability. To provide a holistic view of the LIB development, this Perspective provides insights into materials development, manufacturing, recycling, legislation and policy, and beyond. Last but not least, the future development of LIBs and charging infrastructures in light of emerging technologies are envisioned.

36 MATERIALS SCIENCE↗

Aliovalent Substitution Tunes Physical Properties in a Conductive Bis(dithiolene) Two-Dimensional Metal–Organic Framework

Two-dimensional conductive metal–organic frameworks have emerged as promising electronic materials for applications in (opto)electronic, thermoelectric, magnetic, electrocatalytic, and energy storage devices. Many bottom-up or postsynthetic protocols have been developed to isolate these materials or further modulate their electronic properties. However, some methodologies commonly used in classic semiconductors, notably, aliovalent substitution, are conspicuously absent. Here, in this work, we demonstrate how aliovalent Fe(III) to Ni(II) substitution enables the isolation of a Ni bis(dithiolene) material from a previously reported Fe analogue. Detailed characterization supports the idea that aliovalent substitution of Fe(III) to Ni(II) results in an in situ oxidation of the organic dithiolene linker. This substitution-induced redox tuning modulates the electronic properties in the system, leading to higher electrical conductivity and Hall mobility but slightly lower carrier densities and weaker antiferromagnetic interactions. Moreover, this aliovalent substitution improves the material’s electrochemical stability and thus enables pseudocapacitive behavior in the Ni material. These results demonstrate how classic aliovalent substitution strategies in semiconductors can also be leveraged in conductive MOFs and add further support to this class of compounds as emerging electronic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion Solvation and Transport in Narrow Carbon Nanotubes: Effects of Polarizability, Cation-π Interaction, and Confinement

Understanding ion solvation and transport under confinement is critical for a wide range of emerging technologies, including water desalination and energy storage. While molecular dynamics (MD) simulations have been widely used to study the behavior of confined ions, considerable deviations between simulation results depending on the specific treatment of intermolecular interactions remain. In the following, we present a systematic investigation of the structure and dynamics of two representative solutions, that is, KCl and LiCl, confined in narrow carbon nanotubes (CNTs) with a diameter of 1.1 and 1.5 nm, using a combination of first-principles and classical MD simulations. Our simulations show that the inclusion of both polarization and cation-π interactions is essential for the description of ion solvation under confinement, particularly for large ions with weak hydration energies. Beyond the variation in ion solvation, we find that cation-π interactions can significantly influence the transport properties of ions in CNTs, particularly for KCl, where our simulations point to a strong correlation between ion dehydration and diffusion. Finally, our study highlights the complex interplay between nanoconfinement and specific intermolecular interactions that strongly control the solvation and transport properties of ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dissolved CO 2 Modulates the Electrochemical Capacitance on Gold Electrodes

The presence of CO 2 at an electrified interface between an aqueous electrolyte and a metal electrode is the prerequisite for many electrochemical CO 2 capture technologies. To understand the behavior of dissolved CO 2 at an aqueous electrified interface, we characterized the electrochemical interface of planar gold electrodes with cyclic voltammetry, electrochemical impedance spectroscopy (EIS), electrochemical surface plasmon resonance (EC–SPR), and attenuated total reflectance surface-enhanced infrared spectroscopy (ATR–SEIRAS). Under all investigated conditions, we observed a decrease in the electrochemical capacitance upon saturation of the electrolyte with CO 2 , as compared to an electrolyte saturated with Ar. EIS and EC–SPR showed that this capacitance reduction was also potential dependent: it reached a minimum near the point of zero charge and became more significant as the applied potential moved further away from the point of zero charge. Hybrid quantum–classical simulations of the gold/aqueous electrolyte interface indicate that bicarbonate decreases the capacitance and modifies the composition of the electric double layer. In addition to the binding of bicarbonate under positive bias, we propose that molecular CO 2 can be induced by applied potential to concentrate in the diffuse layer of the electric double layer, leading to a reduction in the electrochemical capacitance under both negative and positive bias. Furthermore, this work advances the understanding of non-Faradaic effects of dissolved CO 2 at aqueous electrified interfaces of relevance for electrochemical CO 2 capture.

25 ENERGY STORAGE↗

On-demand magnon resonance isolation in cavity magnonics

Cavity magnonics is a promising field focusing on the interaction between spin waves (magnons) and other types of signal. In cavity magnonics, isolation of magnons from the cavity to allow signal storage and processing fully in the magnonic domain is highly desired, but its realization is often hindered by the lack of necessary tunability of the interaction. This work shows that by using the collective mode of two yttrium iron garnet spheres and applying Floquet engineering, magnonic signals can be switched on demand to a magnon dark mode that is protected from the environment, enabling a variety of manipulation over the magnon dynamics. Furthermore, our demonstration can be scaled up to systems with an array of magnonic resonators, paving the way for large-scale programmable hybrid magnonic circuits.

42 ENGINEERING↗

Graphene-supported single atom catalysts for high performance lithium-oxygen batteries

The optimal choice of d-block metals in single atom catalysts (SACs) is crucial for designing efficient electrocatalysts for activating the Oxygen reduction reaction (ORR)/ Oxygen evolution reaction (OER) in lithiumoxygen batteries (LOBs). Herein, we used the Quantum Mechanics methods to understand the origin of reactivity for a series of 16 d-block metals supported on nitrogen-doped graphene as SACs for ORR and OER in LOBs. Based on the Gibbs free energy calculations, we found that among the 16 SACs investigated, Zn-SAC exhibits the highest electrochemical activity with the lowest overpotential of 0.17 V. Here we then used machine learning (ML) to develop an intrinsic descriptor, phi, that correlates the catalytic activity with electronic and chemical properties of the catalytic centers at the M-N 4 active site on graphene surface. We established a linear relationship between phi and the catalytic activity that provides guidance for designing efficient SACs for electrocatalysis in LOBs. To validate these predictions, we report electrochemical measurements showing that Zn-SAC exhibits an ultra-stable cyclability with reduced overpotentials over Mo-SAC and nitrogen-doped graphene (NG), confirming our theoretical prediction. This fundamental work provides a deep understanding on the rational design of efficient SACs for OER/ ORR in LOBs.

25 ENERGY STORAGE↗

Ultrastrong magnon-magnon coupling and chiral spin-texture control in a dipolar 3D multilayered artificial spin-vortex ice

Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16 N microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{Δf}{v}$ = 0.57, GHz mode shifts in zero applied field and chirality-control of magnetic vortex microstates with corresponding magnonic spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗