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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integral Field Probe for Mapping of Curved Magnets

The Single Stretched Wire (SSW) method allows highly precise integral field measurements by recording voltage across a tensioned wire mounted to 2-axis linear stages at either end of the magnet aperture. However, traditional SSW probes are not well suited for curved accelerator magnets, which are essential for steering charged particles along arced trajectories in storage rings or beamlines. The tension required to eliminate sag demands a purely straight path, making them incompatible with non-linear magnet geometries. To address this limitation for curved magnets, a modified approach was developed using a segmented, 3D-printed support structure that incorporates a pre-shaped anti-sag curve. Under its own weight and that of the wire bundle, the structure deforms to lie flat while conforming to the curvature of the magnet in the horizontal plane. The optimal geometry of the probe was derived using an iterative process combining FEA simulations in Ansys Mechanical with testing of various carbon fiber-reinforced filaments. The printed and assembled probe was successfully used to measure the SDD-059 magnet at Fermilab, yielding promising results.

Jakopin, Alexander [Northern Illinois U.]↗
DOE OSTI2021

Optoelectronic property comparison for isostructural Cu 2 BaGeSe 4 and Cu 2 BaSnS 4 solar absorbers

To target mitigation of anti-site defect formation in Cu 2 ZnSnS 4–x Se x , a new class of chalcogenides, for which Ba or Sr (group 2) replace Zn (group 12), has recently been introduced for prospective solar absorber application. Cu 2 BaGeSe 4 (CBGSe) and Cu 2 BaSnS 4 (CBTS) are two such compounds, which share a common trigonal crystal structure (P3 1 space group) and similar quasi-direct band gap (~2 eV). While CBTS-based films have already been studied, there are no reports yet on films and solar cells based on related CBGSe. To identify key differences and similarities in the electronic properties between these two materials, electronic characteristics (e.g., carrier concentration, mobility, electron affinity, defect levels, recombination, and charge carrier kinetics) of vacuum-deposited CBGSe and CBTS films are compared using a variety of characterization methods. Hall effect measurements reveal that CBGSe films have relatively higher hole carrier concentration and lower mobility (3 × 10 15 cm –3 , 0.6 cm 2 V –1 s –1 ) compared to CBTS (5 × 10 12 cm –3 , 3.5 cm 2 V –1 s –1 ). Photoelectron spectroscopy yields low electron affinity values for both CBGSe (3.7 eV) and CBTS (3.3 eV), pointing to the necessity of pursuing low electron affinity buffer materials for both types of absorbers. At low temperatures, CBGSe films show free-exciton photoluminescence, as well as pronounced deep-level emission at ~1.4 eV, while CBTS films exhibit a strong bound-exciton signal with noticeably less intense deep-level emission than for CBGSe. Charge carrier kinetics, transport, and recombination properties of both types of films are also analyzed using optical-pump terahertz-probe spectroscopy and time-resolved microwave conductivity. The first CBGSe prototype solar cells (using chemical bath deposited CdS as a buffer layer) show a maximum of 1.5% efficiency with ~0.62 V open-circuit voltage. Furthermore, the measured properties point to possible limiting factors for CBGSe and related films for PV and optoelectronics and provide insights on possible approaches for improvement within this multinary chalcogenide family.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Increased Static Charge–Induced Threshold Voltage Shifts and Memristor Activity in Pentacene OFETs Comprising Polystyrene–Based Gate Dielectrics Containing Electroactive Small Molecule Crystallites

Top-contact bottom-gate pentacene OFETs are fabricated with single layer dielectrics comprised of either polystyrene (PS), poly(4-methylstyrene) (P4MS), or poly(4-tert-butylstyrene) (P4TBS). The polystyrenes are blended with varying concentrations of two different small molecules, dibenzotetrathiafulvalene (DBTTF) and 2,8-difluoro-5,11-bis(triethylsilylethynyl)anthradithiophene (diF-TES-ADT), to form small, separated crystallites contained throughout the polymer dielectric layer. The OFET characteristics of these devices are investigated and their threshold voltage shifts are measured after –70 V static charging for 5 min. Two-terminal measurements are conducted using multiple different gate biases in the range of –50 to +50 V to investigate memristor behavior in the devices. OFETs containing DBTTF exhibited ΔVth increases as large as 330% relative to control OFETs containing no DBTTF, while OFETs containing at least 7.5 wt.% DBTTF exhibited memristor activity, with currents ranging from 20 nA to 44 µA depending on the applied bias. Furthermore, this work demonstrates that including small, separated crystallites in polymer dielectrics enhances their charge storage ability and can be promising for creating nonbinary memory devices for data processing. Additionally, the observed memristor activity indicates the OFETs in this work can be used in development of neuromorphic systems that aim to mimic the synaptic behavior of the human nervous system.

25 ENERGY STORAGE↗
DOE OSTI2023

Characterizing Ion Transport in Electrolytes via Concentration and Velocity Profiles

Abstract Current flowing through an electrolyte is accompanied by continuum motion of ions and solvent, species concentration profiles, and the electric field. While, historically, the understanding of electrolyte transport has predominantly relied on interpreting macroscopic voltage (or current) measurements, recent advances in imaging and spectroscopic techniques allow velocity and concentration profiles to be probed directly. Such detailed information creates exciting opportunities—ranging from verifying theories describing transport in previously studied Li‐ion electrolytes, to new approaches for measuring properties as well as accurately and precisely quantifying transport in more complex electrolytes. Such emerging directions are herein discussed.

25 ENERGY STORAGE↗
DOE OSTI2021

Influence of the Bulk Resistivity on Silicon Heterojunction Solar Cells and Module Reliability

Recent developments in industry on surface passivation open the possibility of using less doped substrates in silicon solar cells. In this report we investigate how the bulk resistivity affects the performance of silicon cells and the reliability of modules. Herein, n- and p-type silicon heterojunction cells with bulk resistivities between 3 and 15 000 Ωcm are studied. We measure the current–voltage characteristics of n-type cells across the resistivity range, and we find comparable responses to illumination intensities between 0.1 and 1 suns. The cells with bulk resistivities over 1000 Ωcm show breakdown voltages larger than -1000 V, almost two orders of magnitude higher than in typical commercial cells. Although modules have bypass-diodes to prevent cells from going into breakdown, higher breakdown voltages can improve the reliability of modules in case of bypass-diode failure and reduce the module cost by easing the number of bypass-diodes required. Finally, the cells have been submitted to light soaking. The float-zone p-type cells with bulk resistivities over 10 000 Ωcm are less sensitive to light-induced degradation than cells with bulk resistivities below 10 Ωcm. The former show to recover few hours after light soaking, while the latter recover only after dark annealing.

14 SOLAR ENERGY↗
DOE OSTI2020

Direct nanoscale mapping of open circuit voltages at local back surface fields for PERC solar cells

The open circuit voltage (V OC) is a critical and common indicator of solar cell performance as well as degradation, for panel down to lab-scale photovoltaics. Detecting V OC at the nanoscale is much more challenging, however, due to experimental limitations on spatial resolution, voltage resolution, and/or measurement times. Accordingly, in this work an approach based on Conductive Atomic Force Microscopy is implemented to directly detect the local V OC , notably for monocrystalline Passivated Emitter Rear Contact (PERC) cells which are the most common industrial-scale solar panel technology in production worldwide. This is demonstrated with cross-sectioned monocrystalline PERC cells around the entire circumference of a poly-Aluminum-Silicide via through the rear emitter. The V OC maps reveal a local Back Surface Field extending ~2 μm into the underlying p-type Si absorber due to Al in-diffusion as designed. Such high spatial resolution methods for photovoltaic performance mapping are especially promising for directly visualizing the effects of processing parameters, as well as identifying signatures of degradation for silicon and other solar cell technologies.

14 SOLAR ENERGY↗
DOE OSTI2021

Mismatch losses in a PV system due to shortened strings

Numerous events may require intentional removal of one or more photovoltaic modules from a string, shortening the length of the string relative to others within the array, resulting in a string length mismatch. The impact of such a mismatch is not well understood either in measurable operational effects (voltage, current, power) or in the potential effects on long-term module health. It is impractical to solely approach this problem experimentally due to the size and complexity of arrays that may experience string length shortening. Here this work presents simulations, validated through limited field experiments on a two string array, providing a basis from which more complex arrays and scenarios may be explored. Refinement of the simulation achieves an overall error in IMPP for the nominal (S 1 ) and test strings (S 2 ) between the simulation and experimental values, through all test conditions, of +0.35 ± 1.46% and -0.36 ± 1.58% respectively. Shortening one of two strings by one module results in a power loss greater than the power contribution of the module alone (1.29 module equivalents); the impact increases through the maximum test case of a six module mismatch with a power loss equivalent to more than 11 modules. The impact of using string-end blocking diodes is presented with an emphasis at the array maximum power point and at open circuit. Implications are discussed for arrays of higher complexity.

14 SOLAR ENERGY↗
DOE OSTI2023

Ensemble models for circuit topology estimation, fault detection and classification in distribution systems

This paper presents a methodology for simultaneous fault detection, classification, and topology estimation for adaptive protection of distribution systems. The methodology estimates the probability of the occurrence of each one of these events by using a hybrid structure that combines three sub-systems, a convolutional neural network for topology estimation, a fault detection based on predictive residual analysis, and a standard support vector machine with probabilistic output for fault classification. The input to all these sub-systems is the local voltage and current measurements. A convolutional neural network uses these local measurements in the form of sequential data to extract features and estimate the topology conditions. The fault detector is constructed with a Bayesian stage (a multitask Gaussian process) that computes a predictive distribution (assumed to be Gaussian) of the residuals using the input. Since the distribution is known, these residuals can be transformed into a Standard distribution, whose values are then introduced into a one-class support vector machine. The structure allows using a one-class support vector machine without parameter cross-validation, so the fault detector is fully unsupervised. Finally, a support vector machine uses the input to perform the classification of the fault types. All three sub-systems can work in a parallel setup for both performance and computation efficiency. In conclusion, we test all three sub-systems included in the structure on a modified IEEE123 bus system, and we compare and evaluate the results with standard approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Robust passivation of CdSeTe based solar cells using reactively sputtered magnesium zinc oxide

Magnesium zinc oxide (MZO, Mg x Zn 1-x O) is a leading emitter for CdTe-based solar cells due to its transparency and the ability to tune its conduction band offset with the absorber. Devices employing alloyed cadmium selenide telluride (CST, CdSe y Te 1-y ) absorbers achieved high efficiency (>19%) using MZO deposited by reactive sputtering over a broad composition range (3.68–3.92 eV, x: 0.20–0.35). Minimal differences in implied and measured open circuit voltage indicate that the contacts are well passivated and highly selective across the spectrum of MZO employed. Device performance insensitivity to MZO composition, which is not observed in CdTe devices, is attributed to the formation of an oxygenated interface layer. Se volatility creates a group VI deficiency at the interface that drives O migration from the MZO into the absorber. This introduces conductivity in the emitter not present in its as-deposited state, contributing to the exceptional performance observed. It is shown that the quality of device passivation depends on the oxidation state of the as-deposited MZO such that intelligent control and management of the reactive sputtering process is required.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Discharging Behavior of Hollandite α-MnO 2 in a Hydrated Zinc-Ion Battery

Hollandite, α-MnO 2 , is of interest as a prospective cathode material for hydrated zinc ion batteries (ZIBs); however, the mechanistic understanding of the discharge process remains limited. Herein, a systematic study on the initial discharge of α-MnO 2 cathode under hydrated environment was reported using density functional theory (DFT) in combination with complementary experiments, where the DFT predictions well described the experimental measurements on discharge voltages and manganese oxidation states. According to the DFT calculations, both protons (H + ) and zinc ions (Zn 2+ ) contribute to the discharging potentials of α-MnO 2 observed experimentally, where the presence of water plays an essential role during the process. This study provides valuable insights into the mechanistic understanding of the discharge of α-MnO 2 in hydrated ZIBs, emphasizing the crucial interplay among the H 2 O molecules, the intercalated Zn 2+ or H + ions, and the Mn 4+ ions on the tunnel wall to enhance the stability of discharged states and, thus, the electrochemical performances in hydrated ZIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Current distribution monitoring enables quench and damage detection in superconducting fusion magnets

Abstract Fusion magnets made from high temperature superconducting ReBCO CORC ® cables are typically protected with quench detection systems that use voltage or temperature measurements to trigger current extraction processes. Although small coils with low inductances have been demonstrated, magnet protection remains a challenge and magnets are typically operated with little knowledge of the intrinsic performance parameters. We propose a protection framework based on current distribution monitoring in fusion cables with limited inter-cable current sharing. By employing inverse Biot-Savart techniques to distributed Hall probe arrays around CORC ® Cable-In-Conduit-Conductor (CICC) terminations, individual cable currents are recreated and used to extract the parameters of a predictive model. These parameters are shown to be of value for detecting conductor damage and defining safe magnet operating limits. The trained model is then used to predict cable current distributions in real-time, and departures between predictions and inverse Biot-Savart recreated current distributions are used to generate quench triggers. The methodology shows promise for quality control, operational planning and real-time quench detection in bundled CORC ® cables for compact fusion reactors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The influence of electrochemical cycling protocols on capacity loss in nickel-rich lithium-ion batteries

The transition towards electric vehicles and more sustainable transportation is dependent on lithium-ion battery (LIB) performance. Ni-rich layered transition metal oxides, such as NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ), are promising cathode candidates for LIBs due to their higher specific capacity and lower cost compared with lower Ni content materials. However, complex degradation mechanisms inhibit their use. In this work, tailored aging protocols are employed to decouple the effect of electrochemical stimuli on the degradation mechanisms in graphite/NMC811 full cells. Using these protocols, impedance measurements, and differential voltage analysis, the primary drivers for capacity fade and impedance rise are shown to be large state of charge changes combined with high upper cut-off voltage. Focused ion beam-scanning electron microscopy highlights that extensive microscale NMC particle cracking, caused by electrode manufacturing and calendering, is present prior to aging and not immediately detrimental to the gravimetric capacity and impedance. Scanning transmission electron microscopy electron energy loss spectroscopy reveals a correlation between impedance rise and the level of transition metal reduction at the surfaces of aged NMC811. The present study provides insight into the leading causes for LIB performance fading, and highlights the defining role played by the evolving properties of the cathode particle surface layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decentralised Reinforcement Learning for Dynamic Cyberattack Response in Microgrid Networks

Microgrids rely on communication networks for reliable operation, which makes them inherently vulnerable to cyberattacks. Such attacks can destabilise system dynamics and drive states away from their nominal operating trajectories. Although several physics-informed and machine learning-based strategies have been developed to counter these threats, the rapidly evolving cyber landscape enables adversaries to bypass static defences or rules-based mitigation approaches. This paper proposes a dynamic, online-trained and fully decentralised reinforcement learning (RL)-based cyberattack response framework to protect microgrids from evolving cyberattacks. The proposed framework deploys multiple deep Q-networks (DQNs), each associated with a distributed energy resource (DER), to enable localised and adaptive attack mitigation. In this framework, each DQN processes local voltage and frequency measurements—combined with intrusion detection system (IDS) alerts—as observations and rewards to guide decision-making. Extensive simulation studies demonstrate the robustness of the proposed framework under diverse attack scenarios and varying IDS-induced detection delays. Comparative analysis highlights its superiority over existing static or preexisting rules-based mitigation approaches. Finally, we present an analysis that shows the framework's scalability to real-life microgrids with more interacting agents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Electronegative ligands enhance charge transfer to Mn 12 single-molecule magnets deposited on graphene

Combining single-molecule magnets (SMMs) and emergent two-dimensional substrates such as graphene may lead to device configurations that are promising for spintronics and quantum computing. Yet, to fully consider the unique features of SMMs anchored to two-dimensional substrates, the choice of ligand attachments, which could affect the magnetic and electronic properties, is critical. In this work, we focus on hybrid junctions comprising CVD-grown graphene and [Mn 12 O 12 (O 2 CR) 16 (H 2 O) 4 ]( R = CH 3 , CHCl 2 ) SMMs with different ligands. We find that [Mn 12 O 12 (O 2 CCH 3 ) 16 (H 2 O) 4 ] SMMs barely change the graphene’s conductivity, while [Mn 12 O 12 (O 2 CCHCl 2 ) 16 (H 2 O) 4 ] SMMs with more electronegative ligands, by means of charge transfer, remarkably modify the electronic transport in graphene as revealed by gate-voltage dependent magnetotransport measurements.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Mg x Zn 1−x O contact to CuGa 3 Se 5 absorber for photovoltaic and photoelectrochemical devices

Abstract CuGa 3 Se 5 is a promising candidate material with wide band gap for top cells in tandem photovoltaic and photoelectrochemical (PEC) devices. However, traditional CdS contact layers used with other chalcopyrite absorbers are not suitable for CuGa 3 Se 5 due to the higher position of its conduction band (CB) minimum. Mg x Zn 1− x O (MZO) is a transparent oxide with adjustable band gap and CB position as a function of magnesium composition, but its direct application is hindered by CuGa 3 Se 5 surface oxidation. Here, MZO is investigated as a contact (n-type ‘buffer’ or ‘window’) material to CuGa 3 Se 5 absorbers pretreated in Cd 2+ solution, and an onset potential close to 1 V vs reversible hydrogen electrode in 10 mM hexaammineruthenium (III) chloride electrolyte is demonstrated. The Cd 2+ surface treatment changes the chemical composition and electronic structure of the CuGa 3 Se 5 surface, as demonstrated by photoelectron spectroscopy measurements. The performance of CuGa 3 Se 5 absorber with Cd 2+ treated surface in the solid-state test structure depends on the Zn/Mg ratio in the MZO layer. The measured open circuit voltage of 925 mV is promising for tandem PEC water splitting with CuGa 3 Se 5 /MZO top cells.

36 MATERIALS SCIENCE↗
DOE OSTI2025

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2026

Temporal Convolutional Network Using Empirical Mode Decomposition to Detect Faults in Grid Connected Systems

Grid-connected power electronic systems require timely and reliable fault detection to prevent equipment damage and reduce downtime. This paper presents a forecasting-based anomaly detection pipeline that decomposes voltage and current measurements into intrinsic mode functions (IMFs) using empirical mode decomposition (EMD), then trains a causal temporal convolutional network (TCN) on normal-operation IMF data to predict short-horizon future dynamics. Deviations between forecasts and observations are summarized as reliability-weighted residual scores and thresholded per sensor using robust statistics with temporal persistence constraints to suppress false positives. To reduce runtime, EMD is performed on downsampled signals for detection, while raw-rate EMD is applied only within a short region of interest for high-frequency interpretability near detected events. Results on a simulated grid-connected converter system demonstrate that IMF-domain forecasting improves anomaly separability relative to raw-signal forecasting and provides interpretable evidence of faults across decomposition channels.

Sutton, Elizabeth [ORNL] (ORCID:0009000078885935)↗
DOE OSTI2026

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗