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At least 1,081 records · Page 60

Bursting at the Seams: Rippled Monolayer Bismuth on NbSe 2

Bismuth, one of the heaviest semimetals in nature, ignited the interest of the materials-physics community for its potential impact on topological quantum-material systems that utilize its strong spin-orbit coupling (SOC) and unique orbital hybridization. In particular, recent theoretical predictions of unique topological and superconducting properties of thin bismuth films and interfaces prompted intense research on the growth of sub- to a few monolayers of bismuth on different substrates. Similar to bulk rhombohedral bismuth, the initial growth of bismuth films on most substrates results in buckled bilayers that either grow in the (111) or (110) directions, with a lattice constant close to that of bulk Bi. By contrast, in this paper we show a new growth pattern for bismuth monolayers on NbSe 2 . We find that the initial growth of Bi can form a strongly bonded commensurate layer, resulting in a compressively strained two-dimensional triangular lattice. A unique pattern of 1D ripples and domain walls is observed. The single layer of bismuth also introduces strong marks on the electronic properties at the surface.

36 MATERIALS SCIENCE↗

Role of initial magnetic disorder: A time-dependent ab initio study of ultrafast demagnetization mechanisms

Despite more than 20 years of development, the underlying physics of the laser-induced demagnetization process is still debated. We present a fast, real-time time-dependent density functional theory (rt-TDDFT) algorithm together with the phenomenological atomic Landau-Lifshitz-Gilbert model to investigate this problem. Our Hamiltonian considers noncollinear magnetic moment, spin-orbit coupling (SOC), electron-electron, electron-phonon, and electron-light interactions. The algorithm for time evolution achieves hundreds of times of speedup enabling calculation of large systems. Our simulations yield a demagnetization rate similar to experiments. We found that (i) the angular momentum flow from light to the system is not essential and the spin Zeeman effect is negligible. (ii) The phonon can play a role but is not essential. (iii) The initial spin disorder and the self-consistent update of the electron-electron interaction play dominant roles and enhance the demagnetization to the experimentally observed rate. The spin disorder connects the electronic structure theory with the phenomenological three-temperature model.

36 MATERIALS SCIENCE↗

$\mathscr{PT}$ symmetry enforced twin exchange as the origin of chirality-induced spin selectivity

Chiral molecules, ubiquitous in chemistry and biology, can differentiate electrons by their spin, a phenomenon known as chirality-induced spin selectivity (CISS). Despite its robustness and technological relevance, CISS has resisted conventional explanation: Spin-orbit coupling (SOC) models cannot fully account for the observed magnitude, room-temperature persistence, or equilibrium signatures. Here, we argue that structural chirality enforces a twin-pair exchange mechanism via the indistinguishability principle, which intrinsically couples spin and spatial degrees of freedom such that wave functions cannot be factorized into spin and spatial components. We derive an effective Hamiltonian that describes both transport and equilibrium CISS phenomena and is non-Hermitian. However, the inherent pseudo-Hermiticity, with $\mathscr{PT}$ symmetry as a special case, ensures real eigenvalues and thermodynamic consistency. We demonstrate that our framework is a step toward resolving long-standing anomalies of CISS. It situates CISS alongside equilibrium symmetry-breaking phenomena such as ferromagnetism and superconductivity, with implications for spintronics, catalysis, and the origins of biological homochirality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo

In this article we consider static Bayesian parameter estimation for partially observed diffusions that are discretely observed. We work under the assumption that one must resort to discretizing the underlying diffusion process, for instance, using the Euler--Maruyama method. Given this assumption, we show how one can use Markov chain Monte Carlo (MCMC) and particularly particle MCMC [C. Andrieu, A. Doucet, and R. Holenstein, J. R. Stat. Soc. Ser. B Stat. Methodol., 72 (2010), 269--342] to implement a new approximation of the multilevel (ML) Monte Carlo (MC) collapsing sum identity. Our approach comprises constructing an approximate coupling of the posterior density of the joint distribution over parameter and hidden variables at two different discretization levels and then correcting by an importance sampling method. The variance of the weights are independent of the length of the observed data set. The utility of such a method is that, for a prescribed level of mean square error, the cost of this MLMC method is provably less than i.i.d. sampling from the posterior associated to the most precise discretization. However the method here comprises using only known and efficient simulation methodologies. Finally, the theoretical results are illustrated by inference of the parameters of two prototypical processes given noisy partial observations of the process: the first is an Ornstein--Uhlenbeck process and the second is a more general Langevin equation.

97 MATHEMATICS AND COMPUTING↗

Spin Berry points as crucial for ultrafast demagnetization

Laser-induced ultrafast demagnetization has puzzled researchers around the world for over two decades. Intrinsic complexity in electronic, magnetic and phononic subsystems is difficult to understand microscopically. So far, it is not possible to explain demagnetization using a single mechanism, which suggests a crucial piece of information still missing. In this paper, we return to a fundamental aspect of physics: spin and its change within each band in the entire Brillouin zone. We employ face-centered cubic (fcc) Ni as an example and use an extremely dense k mesh to map out spin changes for every band close to the Fermi level along all the high symmetry lines. To our surprise, spin angular momentum at some special k points abruptly changes from [Formula: see text] to [Formula: see text] simply by moving from one crystal momentum point to the next. This explains why intraband transitions, which the spin superdiffusion model is based upon, can induce a sharp spin moment reduction, and why electric current can change spin orientation in spintronics. These special k points, which are called spin Berry points [M. V. Berry, Proc. R. Soc. Lond. A 393 (1984) 45], are not random and appear when several bands are close to each other, so the Berry potential of spin majority states is different from that of spin minority states. Although within a single band, spin Berry points jump, when we group several neighboring bands together, they form distinctive smooth spin Berry lines. It is the band structure that disrupts those lines. Spin Berry points are crucial to laser-induced ultrafast demagnetization and spintronics.

Physics↗

The neutron within the deuteron as a surrogate for neutron-induced reactions

We propose the use of neutron poisons in reactions induced by radioactive beams as a test of theoretical models aiming to relate neutron capture in nuclei with neutron surrogate reactions such as ([Formula: see text]) reactions. We exploit the approximations necessary to obtain a direct relation between the two reactions: surrogate versus neutron capture. We also show how this is intimately related to the momentum distribution of the neutron within the deuteron. The models we use are based on the theory of inclusive breakup reactions commonly employed in the treatment of incomplete fusion and surrogate method. Such theories were developed in the 1980s by Ichimura, Austern and Vincent [Phys. Rev. C 32 (1985) 431], Udagawa and Tamura [Phys. Rev. C 24 (1981) 1348] and Hussein and McVoy [Nucl. Phys. A 445 (1985) 124]. We use these theories to derive an expression for the proton yield in the reaction [Formula: see text]. The capture reaction [Formula: see text] is then extracted using reasonable approximations. By recalling an old method proposed by Serber [Phys. Rev. 80 (1950) 1098; Proc. Roy. Soc. A 208 (1951) 559] we explain how the momentum distribution of neutrons within the deuteron will depend on the short-range dependence of the nucleon–nucleon force. The relevance of our work to nucleosynthesis in the rapid neutron capture process is emphasized.

Physics↗

Compiler-Driven FPGA Virtualization with SYNERGY

FPGAs are increasingly common in modern applications, and cloud providers now support on-demand FPGA acceleration in datacenters. Applications in datacenters run on virtual infrastructure, where consolidation, multi-tenancy, and workload migration enable economies of scale that are fundamental to the provider's business. However, a general strategy for virtualizing FPGAs has yet to emerge. While manufacturers struggle with hardware-based approaches, we propose a compiler/runtime-based solution called Synergy. We show a compiler transformation for Verilog programs that produces code able to yield control to software atsub-clock-tickgranularity according to the semantics of the original program. Synergy uses this property to efficiently support core virtualization primitives: suspend and resume, program migration, and spatial/temporal multiplexing, on hardware which is availabletoday.We use Synergy to virtualize FPGA workloads across a cluster of Intel SoCs and Xilinx FPGAs on Amazon F1. The workloads require no modification, run within 3--4x of unvirtualized performance, and incur a modest increase in FPGA fabric usage.

Computer Science↗

Architecture-Aware Models of AI Engines for High-Performance Matrix Matrix Multiplication

The AI Engine (AIE) architecture, available in systems from mobile SoCs to server-class FPGAs, aims to efficiently execute AI/ML tasks through a two-dimensional array of compute tiles. Previous work on AIEs has explored different approaches to mapping computation across spatial arrays, but the compute kernel running on each tile has not been the focus. Additionally, the AIE-ML architecture introduces memory tiles and omits programmable logic, requiring new approaches to staging and moving data throughout the array. In this work we update analytical models developed for CPUs to produce the design of high performance kernels while introducing new model considerations such as memory structure, throughput, and latency as required by the AIE hardware. We evaluate our models by developing AIE-ML kernels for matrix multiplication in low-precision data types showing performance up to 95% of compute peak for the kernel when data resides in local memory and above 90% of compute peak when data resides in main memory.

Binder, Elliott D. [Carnegie Mellon University, Pi↗

A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells

Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.

25 ENERGY STORAGE↗

An Efficient Electrochemical Tanks-in-Series Model for Lithium Sulfur Batteries

This article applies and efficiently implements the Tanks-in-Series methodology ( J. Electrochem. Soc. , 167 , 013534 (2020)) to generate a computationally efficient electrochemical model for Lithium-Sulfur batteries. The original Tank model approach for Lithium-ion batteries is modified to account for porosity changes with time. In addition, an exponential scaling method is introduced that enables efficient simulation of the model equations to address the wide range of time constants present for different reactions in the Lithium-Sulfur system. The Tank Model achieves acceptable voltage error even for transport-limited discharged conditions. Predictions of internal electrochemical variables are examined, and electrochemical implications of the approximations discussed. This suggests significant potential for real-time applications such as optimal charging, cell-balancing, and estimation, and represents a step forward in efforts to incorporate detailed electrochemical models in advanced Battery Management Systems for Lithium-Sulfur batteries.

Parke, Caitlin D. (ORCID:0000000177324044)↗

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: The Effect of Particle Morphology

As the search for improved and next-generation cathodes continues, it is clear that a deeper understanding of synthesis–structure–electrochemical property relationships is of critical importance. The effects of primary and secondary particle morphologies on various transition metal oxides have been studied, but new findings are still being reported. To date, few studies have focused on the effects of particle morphologies on Li- and Mn-rich oxides (>50% Mn) and even fewer studies have focused on the influence over key properties such as electrode-level impedance. In this study, we report the effects of particle morphologies on the area-specific-impedance (ASI) and thermal behavior of Li- and Mn-rich oxides. Samples with a fixed, layered–layered–spinel (LLS), composition were synthesized with differing primary morphologies and tested under standardized, full-cell protocols. The results suggest that smaller primary particle size (i.e., higher surface area) leads to lower overall ASI, a delay in the increasing impedance at low states-of-charge (SOCs), and surprisingly, improved thermal behavior.

33 ADVANCED PROPULSION SYSTEMS↗

A Tanks-in-Series Approach to Estimate Parameters for Lithium-Ion Battery Models

Advanced Battery Management Systems (BMS) play a vital role in monitoring, predicting, and controlling the performance of lithium-ion batteries. BMS employing sophisticated electrochemical models can help increase battery cycle life and minimize charging time. However, in order to realize the full potential of electrochemical model-based BMS, it is critical to ensure accurate predictions and proper model parameterization. The accuracy of the predictions of an electrochemical model is dependent on the accuracy of its parameters, the values of which might change with battery cycling and aging. Parameter estimation for an electrochemical model is generally challenging due to the nonlinear nature and computational complexity of the model equations. To this end, this work utilizes the recently proposed Tanks-in-Series model for Li-ion batteries (J.Electrochem. Soc., 167, 013534 (2020)) to perform parameter estimation. The Tanks-in-Series approach allows for substantially faster parameter estimation compared to the original pseudo two-dimensional (p2D) model. The objective of this work is thus to demonstrate the gain in computational efficiency from the Tanks-in-Series approach. A sensitivity analysis of model parameters is also performed to benchmark the fidelity of the Tanks-in-Series model.

25 ENERGY STORAGE↗

Electro–Oxidation of Nitroxide Radicals: Adsorption–Mediated Charge Transfer Probed Using SERS and Potentiometry

Organic compounds containing nitroxide radicals such as 4–hydroxy–2,2,6,6–tetramethylpiperidine–1–oxyl (4–hydroxy–TEMPO) are redox–active and are of interest for potential applications in redox flow batteries. The mechanisms governing charge–transfer reactions of such compounds are not well understood. Specifically, the anodic charge transfer coefficient (αa) corresponding to the electro–oxidation of 4–hydroxy–TEMPO in an aqueous medium is ~0.9, i.e., αa deviates considerably from the expected value (0.5) for a symmetric single–step one–electron transfer redox reaction. In a previous publication (J. Electrochem. Soc., 2020, 167, 143505), we have proposed a reaction mechanism to explain such asymmetric behavior by invoking adsorption–desorption processes. In the proposed mechanism, reversible oxidation of 4–hydroxy–TEMPO leads to the adsorption of the oxidation product, which then undergoes slow rate–limiting desorption from the electrode surface. In the present contribution, supporting evidence is provided for this mechanism. In situ surface–enhanced Raman spectroscopy combined with density functional theory simulations are employed to confirm the presence of surface–adsorbed species at a Au electrode during electro–oxidation of 4–hydroxy–TEMPO. Furthermore, we employ chronopotentiometry to track the gradual re–equilibration of the electrode–electrolyte interface following the electro–oxidation of 4–hydroxy–TEMPO. Analysis of the chronopotentiometry data further suggests the presence of adsorbed species, which were previously proposed and are now confirmed by direct spectroscopic evidence.

25 ENERGY STORAGE↗

Evaluation of Cathode Materials with Lithium-Metal Anodes: Baseline Performance and Protocol Standardization of Coin Cells

The collaborative evaluation of electrode materials across multiple research entities requires standardized electrochemical testing protocols to produce reliable, one-to-one comparisons between different systems of interest. Similar to the work done by Long et al. on protocol standardization for coin-cell testing with graphite anodes [J. Electrochem. Soc., 163, A2999, (2016)], here we introduce two standardized testing protocols designed to quickly evaluate important electrochemical properties of cathode materials using lithium-metal anodes. The two protocols measure kinetic and thermodynamic capacity losses, rate- and voltage-dependent cycling capacities, instabilities at high voltage and high cycling rate, and overpotentials at various states of charge. We then apply these protocols to four commercially available cathode materials to establish benchmark performance metrics that can be used to screen and evaluate new cathode materials.

25 ENERGY STORAGE↗

Electrochemical Modeling and Performance of a Lithium- and Manganese-Rich Layered Transition-Metal Oxide Positive Electrode

The impedance of a lithium- and manganese-rich layered transition-metal oxide (MR-NMC) positive electrode, specifically Li 1.2 Ni 0.15 Mn 0.55 Co 0.1 O 2 , is compared to two other transition-metal layered oxide materials, specifically LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA) and Li 1.05 (Ni 1/3 Co 1/3 Mn 1/3 ) 0.95 O 2 (NMC). A more detailed electrochemical impedance spectroscopy (EIS) study is conducted on the LMR-NMC electrode, which includes a range of states-of-charge (SOCs) for both current directions (i.e. charge and discharge) and two relaxation times (i.e. hours and one hundred hours) before the EIS sweep. The LMR-NMC electrode EIS studies are supported by half-cell constant current and galvanostatic intermittent titration technique (GITT) studies. Two types of electrochemical models are utilized to examine the results. The first type is a lithium ion cell electrochemical model for intercalation active material electrodes that includes a complex active material/electrolyte interfacial structure. In conclusion, the other is a lithium ion half-cell electrochemical model that focuses on the unique composite structure of the bulk LMR-NMC materials.

25 ENERGY STORAGE↗

The cell-in-series method: A technique for accelerated electrode degradation in redox flow batteries

Here, we demonstrate a novel method to accelerate electrode degradation in redox flow batteries and apply this method to the all-vanadium chemistry. Electrode performance degradation occurred seven times faster than in a typical cycling experiment, enabling rapid evaluation of materials. This method also enables the steady-state study of electrodes. In this manner, it is possible to delineate whether specific operating conditions induce performance degradation; we found that both aggressively charging and discharging result in performance loss. Post-mortem x-ray photoelectron spectroscopy of the degraded electrodes was used to resolve the effects of state of charge (SoC) and current on the electrode surface chemistry. For the electrode material tested in this work, we found evidence that a loss of oxygen content on the negative electrode cannot explain decreased cell performance. Furthermore, the effects of decreased electrode and membrane performance on capacity fade in a typical cycling battery were decoupled from crossover; electrode and membrane performance decay were responsible for a 22% fade in capacity, while crossover caused a 12% fade.

25 ENERGY STORAGE↗

Effect of Initial State of Lithium on the Propensity for Dendrite Formation: A Theoretical Study

Mechanical constraints have been widely used experimentally to prevent the growth of dendrites within lithium metal. The only article known to the authors that tries to theoretically understand how mechanical forces prevent dendrite growth was published by Monroe and Newman [J. Electrochem. Soc., 150 (10) A1377 (2005)]. Based on the assumption that surface tension prevents the growth of interfacial roughness, Monroe and Newman considered pre-stressed conditions of the lithium electrodes. This scenario indicates that prevention of dendrite growth by mechanical means is only possible by using electrolytes with shear modulus at least two times larger than that of lithium metal. Here, a different scenario of relaxed lithium metal (without any pre-existing surface stresses) has been considered in the present analysis. Deposition of lithium due to electrochemical reaction at the lithium/electrolyte interface induces compressive stress at the electrode, the electrolyte, and the newly deposited lithium metal. Present simulations indicate that during operation at low current densities, the scenario of relaxed lithium leads to no dendrites. Rather, the present study points to the importance of including the effect of current distribution to accurately capture the mechanical forces needed to prevent dendrite growth.

25 ENERGY STORAGE↗