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DOE OSTI2018

Photovoltaic Array Differential Backside Exposure Conditions: Backsheet Degradation and Site Design

Backsheet exposure conditions and degradation are shown to vary significantly within an array. This is demonstrated by a survey of the NIST ground-mounted photovoltaic array, which is comprised of over 1000 modules of a single brand with a polyester-based backsheet. Site and array design factors are found to have significant effects on the exposure conditions, and thus degradation of the backsheets. Irradiance is found to be the most significant exposure factor which varies within the array.

14 SOLAR ENERGY↗

DOE OSTI2013

Optimizing Hydronic System Performance in Residential Applications, Ithaca, New York (Fact Sheet)

Condensing boiler technology has been around for many years and has proven to be a durable, reliable method of heating. Based on previous research efforts, however, it is apparent that these types of systems are not designed and installed to achieve maximum efficiency. For example, in order to protect their equipment in the field, manufacturers of low-mass condensing boilers typically recommend design strategies and components that ensure steady, high flow rates through the heat exchangers, such as primary-secondary piping, which ultimately result in decreased efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis: Preprint

circular economy↗

DOE OSTI2017

Evaluation of a data fusion approach to estimate daily PM{sub 2.5} levels in North China

PM{sub 2.5} air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM{sub 2.5} exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM{sub 2.5} in grid cells with a resolution of 10 km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM{sub 2.5} concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R{sup 2} of 0.95 and 0.94, respectively and PM{sub 2.5} was overestimated by WRF-Chem (R{sup 2}=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM{sub 2.5}. Current monitoring network in North China was dense enough to provide a reliable PM{sub 2.5} prediction by interpolation technique. - Highlights: • KED and data fusion model predicted daily PM{sub 2.5} with high accuracy. • WRF-Chem performed worse in PM{sub 2.5} prediction compared with KED and data fusion. • The PM{sub 2.5} monitoring network in North China was able to support reliable PM{sub 2.5} interpolation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

An automatic input/output test experience of FPGA-based logic controller with I/O stimulator - 282

This paper describes an automatic testing approach instead of a traditional manual test for an FPGA-based Logic Controller (FLC). It mainly describes an automatic testing of FLC using an I/O stimulator with the initiated manual action. The FLC was developed by Doosan Heavy Industry and KAERI in S. Korea. We also developed a test-bed like I/O stimulator for a burning test based on the operational scenario. Signal sources from the I/O stimulator contain an analog input, an analog output, a digital input and a digital output, a programmable power supply, an RS232C serial interface, and a dual port Ethernet interface. LabVIEW Programming was used for the automatic testing. The FLC consists of a general processor module (FPM-01), a complex processor module (FPM-02), analog input modules (FAI-01), analog output modules (FAO-01), digital input modules (FDI-01), digital output modules (FDO-01), a data link module (FDL-01), and a network module (FNW-01). Among these, in this paper, automatic digital I/O testing and automatic analog I/O testing are described. In addition, for the accuracy of the automatic testing, two graphic recorders are used. One is the output results of general processor based testing, and the other is the output results of complex processor based testing. These are different company products. Redundancy recording was found in the test results. The test results were synchronized internally with the existing I/O stimulator and externally with two graphic recorders. Calibrations of all of the equipment were made before the system testing. Before the testing started, a test plan and the test procedure were set up in advance, and we performed test scenario-based automatic functional testing for the FLC as the qualification process. It can be several executed depending on the scenario and conditional parameters of the test. For validation of the accuracy and reliability in our automated test, manual testing was also performed. Manual tests were conducted in two ways. The first one was a manual test using Fluke 754 and Fluke 715. The other one was using embedded manual features of the I/O stimulator. By performing the automatic input and output testing using the I/O stimulator, the time and expense of FLC testing can be reduced significantly compared with a conventional manual test. We rechecked the automatic test results using Fluke754 manually. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

From Modular ADMS to Plug-and-Play Ops: Distribution Grid Operations with Platform-Level Orchestration to Enable Ambitious App Hosting

The core function of the distribution grid is to provide electricity to consumers affordably, reliably, and securely. In pursuing these core objectives, distribution utilities are accountable to customers, regulators, and in some cases, shareholders. Other third parties such as aggregators and microgrids can also have a stake in the smooth operation of the grid. Each of these stakeholders has economic, business, and/or governance objectives that inform their expectations of the distribution grid. This multi-objective, multi-stakeholder environment creates tension that must be reconciled to successfully design and operate the distribution grid. Innovative companies are competing to bring high-tech solutions to electric utilities and their customers that address each of these objectives. Many developers of advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) have adopted a modular architecture that allows grid operators to select functions and features according to their individual system needs. A modular platform also allows the solution provider to develop and integrate specific new product modules; however, the need to pursue multiple objectives with a fixed set of controllable devices makes integration expensive whether it is done at the product development stage or the deployment stage. This cost creates a significant barrier to adoption and can lengthen the product to market time of new solutions. To fundamentally address the complexity of system integration for distribution grid operations, the U.S. Department of Energy Office of Electricity has funded the GridAPPS-D project at PNNL, which streamlines integration by contributing to standards development, defining system architecture, applying advanced mathematics, and developing open-source software to demonstrate the concept of an open data-integration platform for distribution operations. The open data-integration platform concept enables system operators and solution providers to deploy ambitious, best-of-breed applications (or apps) without continually reengineering for integration. Ambitious apps developed by different solution providers will inevitably attempt to achieve different control objectives with the same set of controllable devices. If the open platform itself can resolve these conflicts in a way that achieves the best available outcomes for all apps, doesn’t restrict the ambitious design of apps, and ensures safe and secure operations, apps will be able to plug-and-play with the platform at the same time as other ambitious apps. In this paper, we describe a framework called App Deconfliction that empowers a platform to assign setpoints to controllable devices based on the values preferred by different apps (and even external stakeholder entities like customers or aggregators). The App Deconfliction framework is compatible with several methods for determining setpoint values. We present two methods based on game theory that provide a subtle built-in incentive structure for developers to adapt their apps to the fact that they will be operating in a moderated multi-app environment and to favor device setpoints that have the most effect on their objectives over those that have the least effect. Our simulation-based demonstrations have shown that game-theory-based deconfliction can lead to a 7% improvement in control space utilization compared to design-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

The WRF-Solar Ensemble Prediction System: Development, Test, and Validation

Providing reliable probabilistic solar radiation information is needed to improve management of the uncertainty and variability of solar generation. Thus, guidance on how to develop skillful and accurate ensemble forecasts is essential and it will ultimately contribute to integration of high amounts of solar energy on the grid. A team from the National Renewable Energy Laboratory and the National Center for Atmospheric Research had been collaborating to develop the WRF-Solar ensemble prediction system (WRF-Solar EPS) in the past three years to produce probabilistic solar irradiance forecasts and better predict solar energy by quantifying forecast uncertainty. The WRF-Solar EPS basically generates ensemble members for solar irradiance based on stochastic perturbations to provide intraday and day-ahead probabilistic forecasts. This study will present main research steps in developing the WRF-Solar EPS including: (a) tangent linear analysis for identifying key input variables of six WRF-Solar modules significantly related to predicting of cloud and solar irradiance, (b) combining stochastic perturbation technique with the WRF-Solar model, and (c) ensemble calibration method to decrease error and uncertainty of ensemble-based solar forecasts. The capability of WRF-Solar EPS is now updated to the most recent version of standard WRF model. This presentation will summarize comprehensive results from the evaluation of forecasts against the National Solar Radiation Data Base as well as ground-measured observations. Moreover, we will introduce the user's guide for WRF-Solar EPS (e.g., parameters to configure stochastic perturbations) and future extension of this research.

day-ahead forecast↗

DOE OSTI2018

Computing resonant modes of accelerator cavities by solving nonlinear eigenvalue problems via rational approximation

Here, we present an efficient and reliable algorithm for solving a class of nonlinear eigenvalue problems arising from the modeling of particle accelerator cavities. The eigenvalue nonlinearity in these problems results from the use of waveguides to couple external power sources or to allow certain excited electromagnetic modes to exit the cavity. We use a rational approximation to reduce the nonlinear eigenvalue problem first to a rational eigenvalue problem. We then apply a special linearization procedure to turn the rational eigenvalue problem into a larger linear eigenvalue problem with the same eigenvalues, which can be solved by existing iterative methods. By using a compact scheme to represent both the linearized operator and the eigenvectors to be computed, we obtain a numerical method that only involves solving linear systems of equations of the same dimension as the original nonlinear eigenvalue problem. We refer to this method as a compact rational Krylov (CORK) method. We implemented the CORK method in the Omega3P module of the Advanced Computational Electromagnetic 3D Parallel (ACE3P) simulation suite and validated it by comparing the computed cavity resonant frequencies and damping Q factors of a small model problem to those obtained from a fitting procedure that uses frequency responses computed by another ACE3P module called S3P. We also used the CORK method to compute trapped modes damped in an ideal eight 9-cell SRF cavity cryomodule. This was the first time it was possible to compute these modes directly. The damping Q factors of the computed modes match well with those measured in experiments and the difference in resonant frequencies is within the range introduced by cavity imperfection. Therefore, the CORK method is an extremely valuable tool for computational cavity design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

DIF3D-VARIANT 12.0: Updates and New Features

The DIF3D code has been a workhorse of fast reactor analysis work at Argonne National Laboratory for over 40 years. In 1995, a transport option called VARIANT was added to DIF3D to improve the flux solutions for fast reactor problems which we term DIF3D-VARIANT today. DIF3D-VARIANT performs nodal neutron transport calculations using P N or SP N theory in Cartesian and hexagonal two- and three-dimensional geometries. The limited computing capabilities of the time restricted DIF3D-VARIANT to use at most a 6 th order spatial approximation combined with a P3 flux approximation and P1 scattering kernel for a 33 group structure on most studied reactor problems. Computer capabilities have increased steadily since 1995 and today much larger space-angle-energy approximations are possible. This manuscript serves as an update to the theory section of the original DIF3D-VARIANT manual and details more than twenty years of changes made to DIF3D to make version 12 which was released on November 1 st , 2024. The primary focus of the initial work was to extend the space-angle approximations available in DIF3D-VARIANT such that the error due to transport approximations could be better understood. This work was started and completed in 2002 and marked the official version 10. Unfortunately, those higher order approximations could not be used at that time due to the memory constraints of the BPOINTER part of DIF3D (limited to 2 GB). In version 11, completed in 2012, BPOINTER was circumvented in DIF3D-VARIANT for the largest arrays by introducing a Fortran 90 module called LMA (Large Memory Array). This seamlessly replaces all of the functionality of the BPOINTER concept, but it allows 64 bit addressing for every array such that they can be larger than 2 GB. It is now common for DIF3D-VARIANT jobs to consume 50 GB of memory on modern workstations when using high order space-angle approximations and a large number of groups. Many improvements were made to version 11 from 2012 to 2022 when work to create version 12 started. For version 12, several parts of DIF3D were updated to improve performance and thread parallelism was introduced to further reduce the runtime. Numerous minor bugs were discovered in DIF3D-VARIANT as part of the process of creating the perturbation and sensitivity code PERSENT. All of these algorithmic problems were identified in the transition from version 10 to version 11 which prevented DIF3D-VARIANT from running efficiently and reliably. Firstly, the coarse mesh rebalance scheme would routinely diverge and a study detailed in this report demonstrates how it was also typically not effective. This is not a failure of the coarse mesh rebalance methodology, but a failure of its implementation in DIF3D-VARIANT for hexagonal geometries. The fission source extrapolation algorithm was also found to be unreliable on larger group structure problems, leading to divergence in some cases and a negligible improvement in performance overall. Finally, the “Omega” acceleration applied to the partial current solver routine of DIF3D-VARIANT was found to cause DIF3D-VARIANT to converge to the wrong answer. To resolve these issues, both the coarse mesh rebalance and fission source extrapolation were permanently disabled in version 11. The Tchebychev acceleration was put in as a temporary reliable alternative but it is generally inferior to coarse mesh rebalance or coarse mesh finite difference. For the Omega acceleration, the factor was restricted to guarantee that it would not cause follow-on errors in PERSENT. Due to limited funding to support maintenance and development of DIF3D in the last 10 years, no effort was spent since to resolve the outer iteration acceleration. Except for the threading work, all of the changes discussed in this manuscript refer to changes made between version 10 and version 11. Performance comparisons are done to demonstrate the improvements from version 9 to version 12. As will be demonstrated, the updated versi

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

Clinical practice and evaluation of electronic portal imaging device for VMAT quality assurance

Volumetric-modulated arc therapy (VMAT) is a novel extension of the intensity-modulated radiation therapy (IMRT) technique, which has brought challenges to dose verification. To perform VMAT pretreatment quality assurance, an electronic portal imaging device (EPID) can be applied. This study's aim was to evaluate EPID performance for VMAT dose verification. First, dosimetric characteristics of EPID were investigated. Then 10 selected VMAT dose plans were measured by EPID with the rotational method. The overall variation of EPID dosimetric characteristics was within 1.4% for VMAT. The film system serving as a conventional tool for verification showed good agreement both with EPID measurements ([94.1 ± 1.5]% with 3 mm/3% criteria) and treatment planning system (TPS) calculations ([97.4 ± 2.8]% with 3 mm/3% criteria). In addition, EPID measurements for VMAT presented good agreement with TPS calculations ([99.1 ± 0.6]% with 3 mm/3% criteria). The EPID system performed the robustness of potential error findings in TPS calculations and the delivery system. This study demonstrated that an EPID system can be used as a reliable and efficient quality assurance tool for VMAT dose verification.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

Surface heat flux feedback controlled impurity seeding experiments with Alcator C-Mod’s high-Z vertical target plate divertor: performance, limitations and implications for fusion power reactors

The Alcator C-Mod team has recently developed a feedback system to measure and control surface heat flux in real-time. The system uses real-time measurements of surface heat flux from surface thermocouples and a pulse-width modulated piezo valve to inject low-Z impurities (typically N2) into the private flux region. It has been used in C-Mod to mitigate peak surface heat fluxes >40 MW/m2 down to <10 MW/m2 while maintaining excellent core confinement, H98>1. While the system works quite well under relatively steady conditions, use of it during transients has revealed important limitations on feedback control of impurity seeding in conventional vertical target plate divertors. In some cases, the system is unable to avoid plasma reattachment to the divertor plate or the formation of a confinement-damaging x-point MARFE. This is due to the small operational window for mitigated heat flux in the parameters of incident plasma heat flux, plasma density, and impurity density as well as the relatively slow response of the impurity gas injection system compared to plasma transients. Given the severe consequences for failure of such a system to operate reliably in a reactor, there is substantial risk that the conventional vertical target plate divertor will not provide an adequately controllable system in reactor-class devices. These considerations motivate the need to develop passively stable, highly compliant divertor configurations and experimental facilities that can test such possible solutions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Adhesion and debonding kinetics of photovoltaic encapsulation in moist environments: Adhesion and debonding kinetics of photovoltaic encapsulation

Debonding of photovoltaic (PV) encapsulation in moist environments is frequently reported but presently not well understood or quantified. Temperature cycling, moisture, and mechanical loads often cause loss of encapsulation adhesion and interfacial debonding, initially facilitating back-reflectance and reduced electrical current, but ultimately leading to internal corrosion and loss of module functionality. To investigate the effects of temperature (T) and relative humidity (RH) on the kinetics of encapsulation debonding, we developed a mechanics-based technique to measure encapsulation debond energy and debond growth rates in a chamber of controlled environment. The debond energy decreased from 2.15 to 1.75 kJ m-2 in poly(ethylene-co-vinyl acetate) (EVA) and from 0.67 to 0.52 kJ m-2 in polyvinyl butyral when T increased from 25 to 50 degrees C and 20 to 40 degrees C, respectively. The debond growth rates of EVA increased up to 1000-fold with small increases of T (10 degrees C) and RH (15%). To elucidate the mechanisms of environmental debonding, we developed a fracture-kinetics model, where the viscoelastic relaxation processes at the debonding-tip are used to predict debond growth. The model and techniques constitute the fundamental basis for developing accelerated aging tests and long-term reliability predictions for PV encapsulation.

14 SOLAR ENERGY↗

DOE OSTI2025

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗

DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

High-efficiency micro-energy generation based on free-carrier-modulated ZnO:N piezoelectric thin films

The free-carrier-modulated ZnO:N thin film-based flexible nanogenerators (NZTF-FNGs) are proposed and experimentally demonstrated. The suggested flexible nanogenerators (FNGs) are fabricated using N-doped ZnO thin films (NZTFs) as their piezoelectric active elements, which are deposited by a radio frequency magnetron sputtering technique with an N{sub 2}O reactive gas as an in situ dopant source. Considerable numbers of N atoms are uniformly incorporated into NZTFs overall during their growth, which would enable them to significantly compensate the unintentional background free electron carriers both in the bulk and at the surface of ZnO thin films (ZTFs). This N-doping approach is found to remarkably enhance the performance of NZTF-FNGs, which shows output voltages that are almost two orders of magnitude higher than those of the conventionally grown ZnO thin film-based FNGs. This is believed to be a result of both substantial screening effect suppression in the ZTF bulk and more reliable Schottky barrier formation at the ZTF interfaces, which is all mainly caused by the N-compensatory doping process. Furthermore, the NZTF-FNGs fabricated are verified via charging tests to be suitable for micro-energy harvesting devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Rapid Characterization and Statistical Analysis of High-Volume Field-Harvested Photovoltaic Connectors

Photovoltaic (PV) installations heavily depend on connectors for efficient module and string interconnections without requiring skilled labor. Yet this seemingly innocuous component of PV systems is a leading cause of module failures, multiple high-profile fires, and lawsuits in the PV industry. This work aims to answer critical questions regarding why connectors fail and the contributing factors to their failure. The study involves collecting and analyzing more than 17,000 field-harvested connectors from various solar installations across the United States. The vast dataset, which includes connector metadata, visual inspections, and resistance measurements, provides unprecedented insight into the state of health of PV connectors across the US, including the geographic locations, connector types, and installation practices most prone to failures. The work presented here describes a novel rapid characterization method for processing large numbers of connectors and is supported by parallel forensic analysis to discern the root causes of failures as well as a levelized cost of lifetime model to determine the economic ramifications of connector failure. Ultimately, the findings may inform PV developers about the best practices to extend connector longevity and lead to more resilient and reliable PV systems.

connectors↗