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At least 1,135 records · Page 63

Overcoming the doping limit in GaAs by ion implantation and pulsed laser melting

Most semiconductors exhibit a saturation of free carriers when heavily doped with extrinsic dopants. This carrier saturation or “doping limit” is known to be related to the formation of native compensating defects, which, in turn, depends on the energy positions of their conduction band minimum and valence band maximum. Here, we carried out a systematic study on the n-type doping limit of GaAs via ion implantation and showed that this doping limitation can be alleviated by the transient process of pulsed laser melting (PLM). For n-type doping, both group VI (S) and amphoteric group IV (Si and Ge) dopants were implanted in GaAs. For comparison, p-type doping was also studied using Zn as the acceptor. Implanted dopants were activated by the PLM method, and the results are compared to rapid thermal annealing (RTA). Our results reveal that for all n-type dopants, while implantation followed by the RTA results in a similar saturation electron concentration of 2–3 × 10 18 cm –3 , the transient PLM process is capable of trapping high concentration of dopants in the substitutional site, giving rise to a carrier concentration of >10 19 cm –3 , exceeding the doping limit of GaAs. However, due to scatterings from point defects generated during PLM, the mobility of n-type GaAs after PLM is low (~80–260 cm 2 /V s). Subsequent RTA after PLM (PLM + RTA) is able to remove these point defects and recover the mobility to ~1000–2000 cm2/V s. The carrier concentrations of these PLM + RTA samples are reduced but are still a factor of 3 higher than RTA only GaAs. This can be understood as the dopants are already incorporated in the substitutional site after PLM; they are less likely to be “deactivated” by subsequent RTA. This work is significant to the understanding of doping mechanisms in semiconductors and provides a means for device applications, which require materials with ultra-high doping.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scintillation of colloidal nanocrystals

Scintillators are materials that convert ionizing radiation in the form of particles or photons into low-energy photons in the ultraviolet to near-infrared spectral range. Here, this work reviews efforts to use colloidal nanocrystals as scintillator materials. To date, research on colloidal nanocrystals as scintillators has focused on doped phosphor systems, quantum dots and related structures, and perovskite-based nanocrystals. Among various material classes and forms, colloidal semiconductor nanocrystals stand out thanks to their appealing fluorescence properties, yet understanding of their radioluminescence and cathodoluminescence is incomplete. This review discusses fundamental limits and material design challenges toward achieving high brightness, fast speed, and durable scintillator performance with nanocrystal scintillators. First, this review describes the basic principles and efficiency limitations of scintillation, particularly the large influence of multiple exciton generation in many nanocrystal species, as well as performance metrics. Second, methods for measurement are described. Third, we review the results of the main classes of nanocrystal scintillators, including quantum dots and related particles, perovskites, and doped-phosphor particles. Fourth, scintillation imaging is discussed in terms of the relevant performance metrics and results obtained using nanocrystal materials. Finally, we note the strengths and weaknesses of nanocrystal scintillators and discuss potential areas of further development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prospects for the observation of Primordial Black Hole evaporation with the Southern Wide field of view Gamma-ray Observatory

We report primordial Black Holes (PBHs) are remnants of objects formed in the early Universe. Their lifetime is an increasing function of their mass, so PBHs in the right mass range can end their lives in an evaporation event that is potentially detectable by our instruments now. This evaporation may result in a γ-ray flash that can be detected by the current generation of Very-High-Energy γ-ray detectors. The Southern Wide field of view Gamma-ray Observatory (SWGO) will be part of the next generation of these instruments. It will be able to establish limits on PBH evaporations for integration windows between 0.5 and 5 s, in a radius of 0.25 pc around the Earth, being sensitive to a rate of the order of ~50 pc -3 yr -1 , more than one order of magnitude more constraining than the currently established best limits.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrating agrivoltaics into smallholder farming systems to enhance food production and irrigation efficiency under climate stress

Smallholder agricultural growers and entrepreneurs (SAGE) have a crucial role in sustaining food security; their cultivation accounts for roughly 30% of global crop production and contributes substantially to the diversity and nutritional value of food systems. Despite their awareness of and flexibility to adapt to productivity challenges, SAGE communities remain highly vulnerable to heat and drought stress, which threatens both livelihoods and local food availability. While intensification and adaptive farm practices offer partial resilience, their capacity to buffer sudden climatic extremes remains limited. Agrivoltaics, the dual use of land for solar electricity generation and crop cultivation, has emerged as a promising strategy to enhance agricultural productivity and its resilience to climate extremes by altering microclimatic conditions. Although proven effective in hot and arid regions, the benefits of agrivoltaics for temperate climates and small-scale farms remain minimally explored. To address this gap, we evaluated the performance of a small-scale agrivoltaics system in a temperate climate for high-value crops, including leafy vegetables and garlic. We investigate whether the system can (i) protect crops during extreme heat events and (ii) enhance productivity and reduce irrigation requirements during hot and dry periods unsuitable for conventional production. Our findings provide evidence that agrivoltaics is a climate-resilient farming strategy under current and projected climate scenarios, capable of improving yields (by +43% to +127% for the leafy vegetables grown) and reducing water consumption, while creating complementary economic opportunities through decentralized energy generation systems. This work supports the integration of agrivoltaics into small-scale agricultural systems as an innovative pathway to strengthen food security, bolster farmer livelihoods, and enable multiple co-benefits from broader solar energy adoption.

14 SOLAR ENERGY↗

Large-scale Genetic Characterization of a Model Sulfate-Reducing Bacterium

ABSTRACTSulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources, and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Trotter, Valentine V↗

Coupled Charge and Radiation Transport Processes in Thermophotovoltaic and Thermoradiative Cells

Accurate modeling of charge transport and both thermal and luminescent radiation is crucial to the understanding and design of radiative thermal energy converters. Charge-carrier dynamics in semiconductors are well-described by the Poisson-drift-diffusion equations, and thermal radiation in emitter-absorber structures can be computed using multilayer fluctuational electrodynamics. These two types of energy flows interact through radiation absorption or luminescence and charge-carrier generation or recombination. However, past research has typically only assumed limited interaction, with thermal radiation absorption as an input for charge-carrier models to predict device performance. To examine this assumption, we develop a fully coupled iterative model of charge and radiation transport in semiconductor devices, and we use our model to analyze near-field and far-field GaSb thermophotovoltaic and thermoradiative systems. By comparing our results with past methods that do not consider cross-influences between charge and radiation transport, we find that a fully coupled approach is necessary to accurately model photon recycling and near-field enhancement of external luminescence. As these effects can substantially alter device performance, our modeling approach can aid in the design of efficient thermophotovoltaic and thermoradiative systems.

30 DIRECT ENERGY CONVERSION↗

Insights on the peak in the speed of sound of ultradense matter

In this work we investigate the minimal physical requirements needed for generating a speed of sound that surpasses its asymptotic conformal limit. It is shown that a peak in the speed of sound of homogeneous matter naturally emerges in the transition from a phase with broken chiral symmetry to one with a gapped Fermi surface. We argue that this could be relevant for understanding the peak in the speed of sound displayed by some of the current models for cold ultradense matter. A minimal model implementation of this mechanism is presented, based on the spontaneous breakdown of an approximate particle-antiparticle symmetry, and its thermodynamic properties are determined.

79 ASTRONOMY AND ASTROPHYSICS↗

Universal Anomalous Diffusion of Quantized Vortices in Ultraquantum Turbulence

In classical viscous fluids, turbulent eddies are known to be responsible for the rapid spreading of embedded particles. However, in inviscid quantum fluids where the turbulence is induced by a chaotic tangle of quantized vortices, dispersion of the particles can be achieved via a nonclassical mechanism, i.e., their binding to the evolving vortices. However, knowledge on how the vortices diffuse and spread in quantum-fluid turbulence is very limited, especially for the so-called ultraquantum turbulence (UQT) generated by a random tangle of vortices. Here we report a systematic numerical study of the apparent diffusion of vortices in UQT in superfluid helium-4 using the full Biot-Savart simulation. We reveal that the vortices in the superfluid exhibit a universal anomalous diffusion (superdiffusion) at small times, which transits to normal diffusion at large times. This behavior is found to be the result of a generic scaling property of the vortex velocity. Our simulation at finite temperatures also nicely reproduces recent experimental observations. Lastly, the knowledge obtained from this study may form the base for understanding turbulent transport and universal vortex dynamics in various quantum fluids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Grid Utility Asset Vulnerability Assessment (GUAVA) Software Tool

Increasing demand and changes in generation portfolios is pushing power grid to operate towards the limit. However, due to lack of analytical tools for understanding various scales of impact on grid, it is becoming more vulnerable to wide scale power outages and blackouts. A vulnerable grid operating at its limit can be easily disrupted by asset failures caused by devastating hurricanes which has been known to damage transmission and distribution lines along its track. In this direction, researchers have focused on determining these assets by conducting Monte Carlo simulations of hurricanes with uncertainties and collected a large set of simulation data. To determine the infrastructure updates necessary for mitigating wide scale impact of hurricanes on the grid, we propose a software tool named “Grid Utility Asset Vulnerability Analysis” (GUAVA) framework. GUAVA presents a novel data-driven probabilistic analytical approach to (1) post-process hurricane failure scenarios, (2) identify/rank assets that are most vulnerable and critical to failing and are associated with highest impact/risk, and (3) to inform system upgrade decisions & prioritization. Based on the observed results and employed data-driven methodology, it is expected GUAVA can be adapted to provide power system planners with a recommendation engine for making informed decisions to improve resilience of grid.

Mahapatra, Kaveri↗

An Algebraic Quantum Circuit Compression Algorithm for Hamiltonian Simulation

Quantum computing is a promising technology that harnesses the peculiarities of quantum mechanics to deliver computational speedups for some problems that are intractable to solve on a classical computer. Current generation noisy intermediate-scale quantum (NISQ) computers are severely limited in terms of chip size and error rates. Shallow quantum circuits with uncomplicated topologies are essential for successful applications in the NISQ era. In this work, based on matrix analysis, we derive localized circuit transformations to efficiently compress quantum circuits for simulation of certain spin Hamiltonians known as free fermions. The depth of the compressed circuits is independent of simulation time and grows linearly with the number of spins. The proposed numerical circuit compression algorithm behaves backward stable and scales cubically in the number of spins enabling circuit synthesis beyond O(10 3 ) spins. The resulting quantum circuits have a simple nearest-neighbor topology, which makes them ideally suited for NISQ devices.

Hamiltonian simulation↗

Perspective—Enhancing Active Anode Material Performance for Lithium-Ion Batteries via Manipulation of Interfacial Chemistry

Over the past decade, conversion-type anodes have been viewed as an attractive frontrunner for use in the next-generation of high-capacity battery materials. However, many technological limitations exist in the stability and long-term reliability of these anodes for the commercialization of these electrodes. This perspective studies how interfacial interactions between different components of the electrode can help elucidate the key physical and chemical properties needed for the development of high-capacity materials for battery applications.

25 ENERGY STORAGE↗

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗

Hybrid Energy Resources Bidding Model (HERB) v1.0

The HERB Model provides a stochastic optimization framework for hybrid power plants (Storage plus Renewables) participating in day-ahead electricity markets. It considers uncertainty in market prices and renewable energy generation and generated risk-constrained price-quantity bid curves with limited, non-decreasing price steps.

Heleno, Miguel [Lawrence Berkeley National Laborat↗

Use-Inspired, Process-Oriented GCM Selection: Prioritizing Models for Regional Dynamical Downscaling

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).

54 ENVIRONMENTAL SCIENCES↗

Constant-depth circuits for dynamic simulations of materials on quantum computers

Abstract Dynamic simulation of materials is a promising application for near-term quantum computers. Current algorithms for Hamiltonian simulation, however, produce circuits that grow in depth with increasing simulation time, limiting feasible simulations to short-time dynamics. Here, we present a method for generating circuits that are constant in depth with increasing simulation time for a specific subset of one-dimensional (1D) materials Hamiltonians, thereby enabling simulations out to arbitrarily long times. Furthermore, by removing the effective limit on the number of feasibly simulatable time-steps, the constant-depth circuits enable Trotter error to be made negligibly small by allowing simulations to be broken into arbitrarily many time-steps. For an N -spin system, the constant-depth circuit contains only $\mathcal {O}(N^{2})$ O ( N 2 ) CNOT gates. Such compact circuits enable us to successfully execute long-time dynamic simulation of ubiquitous models, such as the transverse field Ising and XY models, on current quantum hardware for systems of up to 5 qubits without the need for complex error mitigation techniques. Aside from enabling long-time dynamic simulations with minimal Trotter error for a specific subset of 1D Hamiltonians, our constant-depth circuits can advance materials simulations on quantum computers more broadly in a number of indirect ways.

Materials simulation↗

Applying the ATOM drug discovery platform to small-molecule antivirals (Annual Report)

The objective of this project is to advance our understanding of the ML approaches needed to find the most potent inhibitor through an AI guided search that simultaneously optimizes for limited off-target safety activity and desirable pharmacokinetics (PK) properties. The methods will be tested for inhibiting SARS-CoV-2 activity through inhibition of the main protease as a demonstration, but the methodology will be developed to apply to any biothreat target using a small-molecule protein binding-based intervention, with limited experimental data. Computational experiments are conducted using our ATOM generative molecular design (GMD) loop software, which is the implementation of our AI/ML drug design pipeline.

59 BASIC BIOLOGICAL SCIENCES↗

Efficient approach to kinetic simulation in the inner magnetically insulated transmission line on Z

This project explores the idea of performing kinetic numerical simulations in the Z inner magnetically insulated transmission line (inner MITL) by reduced physics models such as a guiding center drift kinetic approximation for particles and electrostatic and magnetostatic approximation for the fields. The basic problem explored herein is the generation, formation, and evolution of vortices by electron space charge limited (SCL) emission. The results indicate that for relevant to Z values of peak current and pulse length, these approximations are excellent, while also providing tens to hundreds of times reduction in the computational load. The benefits could be enormous: Implementation of these reduced physics models in present particle-in-cell (PIC) codes could enable them to be routinely used for experimental design while still capturing essential non-thermal (kinetic) physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗