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DOE OSTI2021

In 2 O 3 -Ga 2 O 3 Alloys as Potential Buffer Layers in CdTe Thin-Film Solar Cells

The efficiency of state-of-the-art Cd Te solar cells remains limited by the relatively low open-circuit voltage (V OC ). Improving the front interface is key towards realizing a higher V OC after achieving the necessary bulk carrier density and lifetime. Recent efforts in identifying buffer layers beyond Cd S have focused on Mg x Zn 1-x O, which offers tunability of the band offsets, but often suffers from high interfacial defect densities. Ga 2 O 3 -based buffer layers demonstrate tremendous improvements in interfacial defect passivation in crystalline silicon and dye-sensitized solar cells, leading to record high V OC , yet remain largely unexplored in Cd Te-based devices. Here, we perform hybrid density-functional-theory calculations to investigate pure Ga 2 O 3 and InGaO 3 alloys as a window layer in Cd Te photovoltaics. We report calculated band offsets for several pairs of solid-solid interfaces comprising transparent conducting oxide (TCO) and Cd Te heterojunctions. The results support a large conduction band offset spike of 0.67 eV for the Cd Te/Ga 2 O 3 (100) interface, while the offset is reduced to 0.18 eV for the InGaO 3 alloy and matches closely with the preferred optimum value of 0.2 eV. Device-level modeling tests of Cd Te solar cells integrating our results indicate that the highest efficiency is achieved with InGaO 3 acting both as a buffer layer and TCO. Finally, our results suggest that alloys of In 2 O 3 and Ga 2 O 3 may be attractive alternatives to Mg x Zn 1-x O for tailoring optimal conduction-band offsets of the buffer and TCO layers in high-efficiency Cd Te thin-film solar cells.

14 SOLAR ENERGY↗

DOE OSTI2024

Slope Efficiency and Voltage Reduction at High Current Densities in AlInGaAs Diode Lasers

Here, the slope efficiency and drive voltage of broad area AlInGaAs laser diodes near 865 nm is observed to decrease significantly under quasi-CW pulsed operation at currents well above threshold, in a manner that cannot be explained by thermal effects or carrier leakage over heterojunction barriers. Simulations show that the slope efficiency reduction is explicable by increased free carrier absorption in the waveguide region. Empirical formulas are presented to represent these effects in a closed analytic form suitable for use in simulators for diode-pumped laser systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

New Radiation Tolerant LGAD for High Energy Physics

Low Gain Avalanche Detectors (LGADS) have recently been studied for applications in high energy physics. However, radiation hardness remains a problem. Here, we propose new LGAD process flow that allows for the creation of a very steep born profile in the multiapplication region, reducing the fractional acceptor removal and resulting performance degradation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

STEPS: A Portable Numerical Simulation Toolkit for Electrical Power System Dynamic Studies

Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. In this paper we introduce an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.

42 ENGINEERING↗

DOE OSTI2021

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this work proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Optimizing an Integrated Renewable-Electrolysis System

Hydrogen is a versatile energy carrier that is used in a wide variety of chemical and industrial processes. Producing hydrogen using electrolysis can enable integration of multiple sectors including electricity, heating, and industrial sectors; however, the cost of producing hydrogen from electrolysis remains a challenge for encouraging greater adoption. With growing amounts of renewable generation on the California grid, there is downward pressure on wholesale electricity prices, particularly during the afternoon from photovoltaics (PV). These lower, or even potentially negative prices, challenge the business cases for new and existing PV plants. In addition, as the grid transitions to less flexible generation, there is greater need for system flexibility. To help improve the economics for both solar PV and hydrogen production using electrolyzers, we explore the benefit of combining PV and electrolysis systems. The optimal breakeven hydrogen production cost for six unique market participation configurations is calculated at six candidate locations where PV is already installed. The six market configurations include islanded, separated, retail, net energy metering (NEM), hybrid retail/wholesale and wholesale. Using the Revenue Operation and Device Optimization Model (RODeO) model, the optimal breakeven hydrogen price over the lifetime of the equipment is calculated. The cost includes production, storage, and compression in preparation for gaseous delivery trucks. Revenue streams include the sale of hydrogen, low carbon fuel standard (LCFS) credits, renewable electricity sold to the grid, and Renewable Energy Credits (REC). The costs included are the electricity costs, capital and fixed operation and maintenance cost (FOM) for the electrolyzer, PV, and storage and compression systems as well as taxes and financing costs. In addition, cost reductions are achieved through retail and wholesale rate optimization, by which electricity is purchased at the lowest price and sold, if possible, at the highest price. For all locations, the breakeven hydrogen production cost results show that, in the order of decreasing cost, the system configurations are islanded (highest), separated, NEM, retail, hybrid retail/wholesale, and wholesale (lowest). The resulting system design balances between the capital and maintenance cost components, the operation costs (i.e., electricity costs) and the additional market revenues. The integration of solar PV and electrolysis is shown to provide a mutually beneficial relationship. For PV, integration with electrolysis offers the potential to hedge against wholesale market price volatility, and integration with electrolysis may offer the potential to defer or avoid transmission investment to deliver power to the point-of-use and instead use it on-site. When compared with SMR without considering any renewable hydrogen premiums, this study finds that PV + Electrolysis systems with current costs are likely not competitive; however, with cost reductions for electrolysis equipment consistent with DOE projections, it was found that systems with wholesale market access would be competitive, largely on account of both low capital costs and low-cost electricity. The electrolysis units can provide greater flexibility than is required based on retail rate optimization, so there is an opportunity for a utility or CAISO to increase system flexibility with PV + Electrolysis systems in return for commensurate compensation. In this way, there are potentially several solutions that fall between the hybrid configuration and the wholesale configuration that could provide sufficient compensation for a PV + Electrolysis unit to compete with SMR while also providing greater flexibility to the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Fleet-wide Electrification Impacts Assessment for the Valley Transportation Authority

This report explores the long-term electrification opportunities for the Valley Transit Authority’s (VTA) transit bus fleet. The potential for transit bus electrification at VTA as well as the economic impacts of partial and complete electrification are explored. We use the Revenue Operation and Device Optimization model to determine the optimal charging, operation and lowest capital and operating cost solution to achieve different levels of electrification to meet their existing routes. This study finds that, relying on only depot charging, around 70% of the daily trips by VTA’s transit bus fleet can be replaced with battery electric buses (BEBs) today. The benefits and drawbacks of five methods for improving the electrification potential beyond that achievable with only depot charging are discussed including (1) increase charger power, (2) purchase of larger vehicle batteries, (3) en-route charging, (4) purchasing additional buses and swapping them to enable the existing routes/blocks1 to be met, and (5) route/block redesign. A strategy is developed to enable full fleet electrification by increasing charger power or allowing intraday charging as a proxy for the options mentioned above. This method allows us to develop an understanding of the impacts and trade-offs of full fleet electrification. Two charging strategies are examined. Immediate charging, when the bus is charged as soon as it arrives at a depot or en-route charging station, and smart charging, which uses a controller to determine the best times to charge to achieve the lowest charging cost, while maintaining the same trip schedules. Smart charging is effective at reducing the peak power consumption, which can be reduced by between 31% and 65% compared to immediate charging. This translates directly to lower electricity demand charges and lower costs for possible distribution system upgrades. The total lifetime net present value (NPV) costs for different scenarios are presented in Figure ES-1. Scenarios are separated into three sections. The first stacked bar on the left is the base case (business-as-usual) where all buses are diesel hybrids, the next four bars include partial and full fleet electrification utilizing only immediate charging, and the last four bars include partial and full fleet electrification utilizing smart charging. The results show that smart charging scenarios are within ±4% of the lifetime NPV cost of the diesel-hybrid only (business-as-usual) scenario. The scenarios with full fleet electrification (i.e., including intraday charging) are 4% lower cost and those with partial fleet electrification (i.e., without intraday charging) are 2%–3% higher. However, it is important to note that the intraday charging scenarios do not include any additional costs for the equipment necessary to achieve intraday charging (e.g., additional chargers, larger batteries, new route design). Additionally, it is worth noting that the Low Carbon Fuel Standard (LCFS) credit received for implementing electric buses is essential to achieving these results.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Cybersecurity Certification Requirements for Distributed Energy Resources: A Survey of SunSpec Alliance Standards

This survey paper explores the cybersecurity certification requirements defined by the SunSpec Alliance for Distributed Energy Resource (DER) devices, focusing on aspects such as software updates, device communications, authentication mechanisms, device security, logging, and test procedures. The SunSpec cybersecurity standards mandate support for remote and automated software updates, secure communication protocols, stringent authentication practices, and robust logging mechanisms to ensure operational integrity. Furthermore, the paper discusses the implementation of the SAE J3072 standard using the IEEE 2030.5 protocol, emphasizing the secure interactions between electric vehicle supply equipment (EVSE) and plug-in electric vehicles (PEVs) for functionalities like vehicle-to-grid (V2G) capabilities. This research also examines the SunSpec Modbus standard, which enhances the interoperability among DER system components, facilitating compliance with grid interconnection standards. This paper also analyzes the existing SunSpec Device Information Models, which standardize data exchange formats for DER systems across communication interfaces. Finally, this paper concludes with a detailed discussion of the energy storage cybersecurity specification and the blockchain cybersecurity requirements as proposed by SunSpec Alliance.

Tsikteris, Sean (ORCID:0009000524202250)↗

DOE OSTI2020

Economic Analysis of Integrated Solar Power, Hydrogen Production, and Electricity Markets

decarbonized economy↗

DOE OSTI2023

Self-tuning wave energy converter (WEC) controller for changing sea states

Systems and methods for a WEC controller that uses a self-tuning proportional-integral control law prescribing motor torques to maximize electrical power generation and automatically tune the controller to maximize power absorption. In an embodiment, the controller may be part of any resonant WEC system. The control law relies upon an identified model of device intrinsic impedance to generate a frequency-domain estimate of the wave-induced excitation force and measurements of device velocities. The control law was tested in irregular sea-states that evolved over hours (a rapid, but realistic time-scale) and that changed instantly (an unrealistic scenario to evaluate controller response).

Bacelli, Giorgio↗

DOE OSTI2025

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2025

Foundational Research for Fusion Systems Safety Assessment Overview

Presentation detailing work package to develop comprehensive fusion device safety models over the course of the next three years, including references to a blanket, divertor and magnet design, and statistical reliability models

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2020

Absorber Column CFD model validation against PNNL’s device-scale absorber column on the LCFS unit

Absorber column has been widely used for CO 2 capture in the coal-fired power plants. High-fidelity CFD models play an important role in absorber column design and solvents optimization, which help enhance the CO 2 capture efficiency and reduce the operation cost. This report provides a comprehensive description of the development of CFD absorber models at two different levels, the design and implementation of PNNL’s device-scale absorber column experiment, and the methodology to combine the CFD results, experiment data, and Aspen model for a better understanding of the interface area in packed column. A composite model is firstly proposed in the Discrete Element Method (DEM) packing process, which can model the complex geometry of various packing elements. This generates a realistic packing pattern and accurate packing porosity ε and specific area a p compared to the actual values for absorber column used in LCFS. Two level of CFD absorber models were developed, namely the full-size column model (FCM) to simulate the entire packed column with a focus on the wall/entrance effects, and the representative column model (RCM) to simulate a section of column with a focus on the sensitivity study of interface area. A Design of Experiment (DoE) plan was developed to guide the collection of 100 run CFD data and 12 experiment runs. The 100 CFD runs were carried out in the RCM with Pro-Pak packing and cover a wide operation range and solvent properties. Impact of influential factors on the interface area in packed column were investigated in details. The CFD interface area was then combined with the experimental data and Aspen model to infer some information of the effective contact angle in the column. The accuracy and uncertainties in the interface area and contact angle can be quantified.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Exchange of Ions across the TiN/TaO x Interface during Electroformation of TaO x -Based Resistive Switching Devices

The valence change model describes the resistive switching in metal oxide-based devices as due to electroreduction of the oxide and subsequent electromigration of oxygen vacancies. Here, we present cross-sectional X-ray energy-dispersive spectroscopy elemental maps of Ta, O, N, and Ti in electroformed TiN/TaO 2.0 /TiN structures. O, N, and Ti were exchanged between the anode and the functional oxide in devices formed at high power (~1 mW), but the exchange was below the detection limit at low power (<0.5 mW). All structures exhibit a similar Ta-enriched and O-depleted filament formed by the elemental segregation in the functional oxide by the temperature gradient. The elemental interchange is interpreted as due to Fick’s diffusion caused by high temperatures in the gap of the filament and is not an essential part of electroformation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Core-edge modeling of gyrokinetic turbulence by coupling the delta-f and total-f models in the XGC code

Whole device gyrokinetic turbulence is modeled using a delta-f model in the core coupled to a total-f model in the edge. This new model is implemented in the gyrokinetic code X-Point Included Gyrokinetic Code (XGC) and works within a single simulation. It employs a canonical Maxwellian background in the core and the usual local Maxwellian in the edge. These different core and edge backgrounds are coupled over an overlap region. A thermal-bath operator is used to keep δf small in the core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.

Austria, Phillipe [ORNL] (ORCID:0000000236223973)↗