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At least 703 records · Page 39

Universal tight binding model for chemical reactions in solution and at surfaces. I. Organic molecules

As is now well established, a first order expansion of the Hohenberg–Kohn total energy density functional about a trial input density, namely, the Harris–Foulkes functional, can be used to rationalize a non self consistent tight binding model. If the expansion is taken to second order then the energy and electron density matrix need to be calculated self consistently and from this functional one can derive a charge self consistent tight binding theory. In this paper we have used this to describe a polarizable ion tight binding model which has the benefit of treating charge transfer in point multipoles. This admits a ready description of ionic polarizability and crystal field splitting. It is necessary in constructing such a model to find a number of parameters that mimic their more exact counterparts in the density functional theory. We describe in detail how this is done using a combination of intuition, exact analytical fitting, and a genetic optimization algorithm. Having obtained model parameters we show that this constitutes a transferable scheme that can be applied rather universally to small and medium sized organic molecules. We have shown that the model gives a good account of static structural and dynamic vibrational properties of a library of molecules, and finally we demonstrate the model's capability by showing a real time simulation of an enolization reaction in aqueous solution. In two subsequent papers, we show that the model is a great deal more general in that it will describe solvents and solid substrates and that therefore we have created a self consistent quantum mechanical scheme that may be applied to simulations in heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphological descriptors of nanoparticles: The link between atomistic structures and x-ray absorption spectra

Understanding and quantifying the morphology of nanoparticles are essential for linking their atomic structure to diverse applications and verifying theoretical models. While experimental information on the structure of nanoparticles in the size range below ∼5 nm can be extracted from x-ray absorption spectroscopy using a small number of descriptors—most commonly coordination numbers—developing an understanding of morphology descriptors from experimental data remains a challenge. Here, in this study, we introduce NanoGene, a genetic algorithm-based method for generating structurally diverse nanoparticle models guided by user-defined descriptors. We establish correlations among structural, size-related, and morphological descriptors and demonstrate how experimentally accessible parameters, such as coordination numbers, can be leveraged to infer otherwise inaccessible ones, such as the generalized coordination number or particle oblateness. Principal component and clustering analyses reveal the relative importance of descriptors, with the number of atoms emerging as a key discriminant of the nanoparticle structure. By providing both the methodology and an extensive dataset of nanoparticle geometries, this work offers a practical foundation for descriptor-based analysis and interpretation of experimental observations, bridging the gap between local atomic coordinates and global morphological characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Electric field driven domain wall dynamics in BaTiO 3 nanoparticles

We report a detailed investigation into the response of single BaTiO 3 (BTO) nanocrystals under applied electric fields (E-field) using Bragg coherent diffraction imaging. Our study reveals pronounced domain wall migration and expansion of a sample measure under applied electric field. The changes are most prominent at the surface of the nanocrystal, where the lack of external strain allows greater domain wall mobility. The observed domain shifts are correlated to the strength and orientation of the applied E-field, following a side-by-side domain model from Suzana []. Notably, we identified a critical electric field strength of 3 MV/m, which leads to irreversible structural changes, suggesting plastic deformation. The findings highlight how surface effects and intrinsic defects contribute to the enhanced dielectric properties of BTO at the nanoscale, in contrast to bulk materials, where strain limits domain mobility. These findings deepen our understanding of nanoscale dielectric behavior and inform the design of advanced nanoelectronic devices. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structural motifs and bonding in two families of boron structures predicted at megabar pressures

The complex crystal chemistry of elemental boron has led to numerous proposed structures with distinctive motifs as well as contradictory findings. Herein, evolutionary structure searches performed at 100 GPa have uncovered a series of metastable phases of boron, and bonding analyses were carried out to elucidate their electronic structure. These polymorphs, dynamically stable at 100 GPa, were grouped into two families. Here, the first was derived from the thermodynamic minimum at these conditions, α-Ga, whereas channels comprised the second. Two additional intergrowth structures were uncovered, and it was shown they could be constructed by stacking layers of α-Ga-like and channel-like allotropes on top of each other. A detailed bonding analysis revealed networks of four-center σ-bonding functions linked by two-center B-B bonds in the α-Ga based structures, and networks that were largely composed of three-center σ-bonding functions in the channel-based structures. Seven of these high-pressure phases were found to be metastable at atmospheric conditions, and their Vickers hardnesses were estimated to ≈ 36 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Scenario Generation Method for Wind Power Ramp Events Forecasting

Wind power ramp events (WPREs) have received increasing attention in recent years due to their significant impact on the reliability of power grid operations. In this paper, a novel WPRE forecasting method is proposed which is able to estimate the probability distributions of three important properties of the WPREs. To do so, a neural network (NN) is first proposed to model the wind power generation (WPG) as a stochastic process so that a number of scenarios of the future WPG can be generated (or predicted). Each possible scenario of the future WPG generated in this manner contains the ramping information, and the distributions of the designated WPRE properties can be stochastically derived based on the possible scenarios. Actual data from a wind power plant in the Bonneville Power Administration (BPA) was selected for testing the proposed ramp forecasting method. Results showed that the proposed method effectively forecasted the probability of ramp events.

17 WIND ENERGY↗

Field Harmonic Measurement of High-Gradient Permanent Magnet Quadrupoles for NSLS- II Upgrade

The National Synchrotron Light Source II (NSLS-II) is preparing for a major upgrade based on a new lattice concept, known as “Complex Bend,” to replace its existing double bend achromat (DBA) lattice. Here, this novel lattice will use high-gradient permanent magnet quadrupoles (PMQs) with small apertures in the range of 16–22 mm. A prototype complex bend branch with PMQs has been installed in the NSLS-II linac to evaluate the lattice's performance. An accurate and precise magnetic measurement system is required for field harmonic characterization and magnetic tuning of these PMQs. As part of this project a Rotating-Coil bench, based on a Printed Circuit Board (PCB) coil with a 12 mm diameter, has been configured to measure nine PMQs with bore diameter of 12.7 mm. This PCB coil has an active length of 270 mm, and is able to measure fields up to the 15th harmonic of the main field at a reference radius of 5 mm, while maintaining field quality levels within 10 ppm of the main field. This article presents the PCB coil setup, the harmonic measurement results and their temperature dependencies and repeatability. Simulation results on compensation of undesired multipoles using “IDBuilder”, a genetic algorithm-based optimizer code for magnetic tuning is included for field harmonic corrections.

36 MATERIALS SCIENCE↗

Multi-Timescale Three-Phase Unbalanced Distribution System Operation With Variable Renewable Generations

This paper proposes a multi-timescale operational approach for a three-phase unbalanced distribution system, which contains hourly scheduling at substation level and minutes power flow operation at feeder level. In the substation scheduling model, the objective is to minimize the system cost with variable renewable generations. The given error distribution model of renewable generation is formulated as a chance constraint, and derived into a deterministic form by Gaussian mixture model (GMM) with genetic algorithm-based expectation-maximization (GAEM). In the feeder scheduling model, the system cost is further reduced with the optimal power flow (OPF) at a timescale of minutes. Considering the nonconvexity of the three-phase unbalanced OPF problem in distribution systems, the semidefinite programming (SDP) is used to relax the problem into a convex problem, and a distributed computation approach is built based on alternating direction method of multiplier (ADMM). The IEEE 123-bus distribution system, DU (University of Denver) campus distribution system, and the IEEE 8500-bus distribution system are used as the test bench for the proposed approach. And the numerical results demonstrate the effectiveness and validity of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mild hybridisation of turboprop engine with high-power-density integrated electric drives

Here this paper shares with the aerospace community a case study of turboprop mild hybridisation using a recently developed integrated drive system in the University of Nottingham, UK, within the ACHIEVE project under EU H2020 CleanSky 2 program (project No. 737814). The developed drive system enables green taxiing of a turboprop aircraft while on the ground with its engine off, and as an electrical generator when the turboprop is in the air. The entire system is designed to be able to integrate within the power auxiliary gear box (PAGB) of a turboprop aircraft. Some of the key features of the developed system include a high-speed permanent magnet machine (up to 14,200rpm) with dual three-phase design, SiC-based high power density (11.8kW/L for the power converter, 35.3kW/L and 7.2kW/kg for the machine active parts), integrated cooling design for high-temperature operation (>130°C ambient temperature), fault tolerance consideration with dual channel operation capabilities and sensorless control for entire operational conditions. This paper is giving an overview of the design process of the electrical machine, power converters, and its cooling of the entire drive. Numerical analysis (FEM and CFD) and some experimental results are presented to demonstrate the effectiveness and the desired performance of the developed integrated drive system.

42 ENGINEERING↗

Comparative Analysis of Direct and Indirect Cooling of Wide-Bandgap Power Modules and Performance Enhancement of Jet Impingement-Based Direct Substrate Cooling

With the development of high-power and high-torque machines, requirements for high-power density electronics are increasing. Thermal management of such systems requires high heat extraction. Conventional air cooling based heat sinks and cold plate based liquid cooling have their own benefits for various applications but has limitations for high power density applications. The current study explores a jet impingement based direct substrate cooling system that was implemented for a SiC based direct bonded Cu substrate for various power losses. Numerical comparison between jet impingement cooling and conventional horizontal/indirect cooling (pin fin heat sink and genetic algorithm-optimized heat sink) showed that the area weighted average of the heat transfer coefficient (HTC) is high for both horizontal cooling designs, and the local HTC is higher for jet impingement. Design iterations were undertaken to resolve the bottleneck of this cooling system. Increasing the number of nozzles helped to cover more area at the direct bonded Cu bottom plate, which drops the chip temperature considerably. With a constant flow rate, increasing the number of nozzles would decrease local jet velocity, which reduces the heat extraction by jet impingement. This issue can be addressed by reducing the diameter of nozzle but doing so results in a high pressure drop where the design constraint is 2 psi. A flared nozzle design is proposed, which has a higher spreading angle of the jet that increases the flow coverage and reduces the pressure drop of the coolant loop.

Barua, Himel↗

Gene Expression Programming for Quantum Computing

Here, we introduce QuantumGEP, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (1) maps a given set of input states to a given set of output states or (2) transforms a fixed initial state to minimize a given physical quantity of the output state. QuantumGEP is a driver program that uses evendim, a generic computational engine for GEP, both of which are free and open source. We apply QuantumGEP as a powerful solver for MaxCut in graphs and for condensed matter quantum many-body Hamiltonians.

97 MATHEMATICS AND COMPUTING↗

Protection settings optimizer

SAND2023-06672O The Protection Settings Optimizer (PSO) uses system and fault data as inputs to formulate the problem of calculating relay settings as a mixed integer, nonlinear optimization problem (MINLP). The MINLP is solved using a genetic algorithm-based optimizer that attempts to find settings to reduce the relay operating times. The PSO protects the power system by using the steady-state fault voltages and currents, which then calculates the optimal device setting to protect the power system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Patel, Trupal↗

Iterative wavefront optimization of ultrafast laser beams carrying orbital angular momentum

Structured intense laser beams offer degrees of freedom that are highly attractive for high-field science applications. However, the performance of high-power laser beams in these applications is often hindered by deviations from the desired spatiotemporal profile. This study reports the wavefront optimization of ultrafast Laguerre-Gaussian beams through the synergy of adaptive optics and genetic algorithm-guided feedback. The results indicate that the intensity fluctuations along the perimeter of the target ring-shaped profile can be reduced up to ~15%. Furthermore, the radius of the ring beam profile can be tailored to a certain extent by establishing threshold fitting criteria. The versatility of this approach is experimentally demonstrated in conjunction with different focusing geometries.

47 OTHER INSTRUMENTATION↗

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗

Miniaturized Air-to-Refrigerant Heat Exchangers

Air-to-refrigerant Heat eXchangers (HX) are an essential component of Heating, Ventilation, Air-Conditioning, and Refrigeration (HVAC&R) systems, serving as the main heat transfer component. The major limiting factor to HX performance is the large airside thermal resistance. Recent literature aims at improving heat transfer performance by utilizing enhancement methods such as fins and small tube diameters; this has lead to almost exhaustive research on the microchannel HX (MCHX). The objective of this project is to develop a miniaturized air-to-refrigerant HX with at least 20% reduction in volume, material volume, and approach temperature compared to current state-of-the-art multiport flat tube designs and also be capable of production within five years. Moreover, the proposed HX’s are expected to have good water drainage and should succeed in both evaporator and condenser applications. The project leveraged Parallel-Parametrized Computational Fluid Dynamics (PPCFD) and Approximation-Assisted Optimization (AAO) techniques to perform multi-scale analysis and shape optimization with the intent of developing novel HX designs whose thermal-hydraulic performance exceeds that of state-of-the-art MCHX. Nine heat exchanger geometries were initially chosen for detailed analysis, selected from 35+ geometries which were identified in previous work at the University of Maryland, College Park. The newly developed optimization framework was exercised for three design optimization problems: (DP I) 1.0kW radiator, (DP II) 10kW radiator and (DP III) 10kW two-phase HX. DP I consisted of the design and optimization of 1.0kW air-to-water HX’s which exceeded the project requirements of 20% volume/material reduction and 20% better performance. Two prototypes for the 1.0kW HX were prototyped, tested and validated using newly-designed airside and refrigerant side test facilities. DP II, a scaled version DP I for 10kW air-to-water HX applications, also yielded optimized HX designs which met project requirements. Attempts to prototype a 10kW have presented unique manufacturing challenges, especially regarding tube blockages and structural stability. DP III comprised optimizing two-phase HX’s for a 3.0Ton capacity in a heat pump / air-conditioning unit for cooling mode application using R410A as the working fluid. The HX’s theoretically address the project requirements. System-level analysis showed the HX’s achieved up to 15% improvement in COP while also reducing overall unit charge by 30-40%. The project methodology was capable of developing HX’s which can outperform current state-of-the-art MCHX by at least 20% reduction in volume, material volume, and approach temperature. Additionally, the capability for optimization using refrigerant charge as an objective function was developed. The five-year manufacturing feasibility of the proposed HX’s was shown to have a good outlook. Successful prototyping through both conventional manufacturing methods and next generation methods such as additive manufacturing was achieved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗