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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cooperative Research and Development Agreement (CRADA) NFE-18-07194 with TerraPower LLC (Final Report)

Because of the potential economic and safety benefits of the molten salt reactor (MSR) concept, development of several designs has been initiated around the world over the past decade. New international nuclear safeguards needs and verification challenges are likely to arise because of the commercial interests in MSRs and the number of MSR design variants. As a result, work was undertaken to explore the cross-cutting issues specific to the application of international nuclear safeguards (i.e., safeguards) to liquid-fueled molten salt reactors (LFMSRs). Through a public-private partnership, a report was developed that focuses on the TerraPower Molten Chloride Fast Reactor (MCFR) design that has received a funding award from the US Department of Energy (DOE), Office of Nuclear Energy. The report is intended to provide a preliminary analysis for a safeguards-by-design (SBD) effort to inform designers about how safeguards could be applied to LFMSRs by the International Atomic Energy Agency (IAEA).Although the report specifically focuses on the TerraPower design, the conclusions are applicable to the main design features of LFMSRs and can be used to extrapolate how existing IAEA safeguards measures for other fuel cycle facilities can be appropriately applied or modified. The report evaluates the appropriate safeguards approaches for LFMSRs, presents existing safeguards inspection technologies are still valid for LFMSRs, and identifies new challenges that will require novel measurement instruments to meet verification standards of the IAEA and the international safeguards regime. This document summarizes the results of the work performed under the full report developed as part of the Cooperative Research and Development Agreement (CRADA). This summary does not contain any protected CRADA information and is intended for public release.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

SuperCam Calibration Targets: Design and Development

Abstract SuperCam is a highly integrated remote-sensing instrumental suite for NASA’s Mars 2020 mission. It consists of a co-aligned combination of Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), Visible and Infrared Spectroscopy (VISIR), together with sound recording (MIC) and high-magnification imaging techniques (RMI). They provide information on the mineralogy, geochemistry and mineral context around the Perseverance Rover. The calibration of this complex suite is a major challenge. Not only does each technique require its own standards or references, their combination also introduces new requirements to obtain optimal scientific output. Elemental composition, molecular vibrational features, fluorescence, morphology and texture provide a full picture of the sample with spectral information that needs to be co-aligned, correlated, and individually calibrated. The resulting hardware includes different kinds of targets, each one covering different needs of the instrument. Standards for imaging calibration, geological samples for mineral identification and chemometric calculations or spectral references to calibrate and evaluate the health of the instrument, are all included in the SuperCam Calibration Target (SCCT). The system also includes a specifically designed assembly in which the samples are mounted. This hardware allows the targets to survive the harsh environmental conditions of the launch, cruise, landing and operation on Mars during the whole mission. Here we summarize the design, development, integration, verification and functional testing of the SCCT. This work includes some key results obtained to verify the scientific outcome of the SuperCam system.

Manrique, J. A. (ORCID:0000000220532819)↗
DOE OSTI2024

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using non-invasive MEMS pressure sensors for measuring building envelope air leakage

Micro-electromechanical systems (MEMS)-based sensors have seen significant improvements in accuracy and cost over the past several years, and due to the need for altitude sensing in unmanned aerial vehicles and wearable technologies, absolute pressure sensors have shown the most dramatic improvements. This paper investigates applications of MEMS sensors in commercial buildings, including pairing two absolute pressure sensors to determine differential pressures between different locations in and around buildings. Differential pressure measurements are commonly made in commercial buildings for a number of applications, including static pressure measurements for variable-speed supply fan control, air balancing in hospitals, and for envelope and duct air leakage testing. This paper focuses specifically on envelope air-leakage testing applications of these sensors. The use of continuous pressure measurements in addition to one-time non-intrusive outdoor airflow measurements of rooftop packaged units is investigated. A comparison with standardized leakage testing indicated that continuous measurements with MEMS pressure-sensors were able to estimate envelope leakage to within 3–16% of the standardized test result. In addition, the magnitude and stability of differential pressure differences that can be resolved with absolute pressure sensors are also investigated in the laboratory and the field. Results show that the sensors can be effectively used for pressures seen in low rise buildings with rooftop units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools

The rapid development of computational approaches for predicting the structures of T cell receptors (TCRs) and TCR-peptide-major histocompatibility (TCR-pMHC) complexes, accelerated by AI breakthroughs such as AlphaFold, has made it feasible to calculate these structures with increasing accuracy. Although these tools show great potential, their relative accuracy and limitations remain unclear due to the lack of standardized benchmarks. Here, we systematically evaluate seven tools for predicting isolated TCR structures together with six tools for predicting TCR-pMHC complex structures. The methods include homology-based approaches, general prediction tools using AlphaFold, TCR-specific tools derived from AlphaFold2, and the newly developed tFold-TCR model. The evaluation uses a post-training data set comprising 40 αβ TCRs and 27 TCR-pMHC complexes (21 Class I and 6 Class II). Model accuracy is assessed at global, local, and interface levels using a variety of metrics. We find that each tool offers distinct advantages in various aspects of its predictions. AlphaFold2, AlphaFold3, and tFold-TCR excel in overall accuracy of TCR structure prediction, and TCRmodel2 and AlphaFold2 perform well in overall accuracy of TCR-pMHC structure prediction. However, TCR-specific tools derived from AlphaFold2 show lower accuracy in the framework region than both homology-based methods and general-purpose tools such as AlphaFold, and challenges remain for all in modeling CDR3 loops, docking orientations, TCR-peptide interfaces, and Class II MHC-peptide interfaces. Furthermore, these findings will guide researchers in selecting appropriate tools, emphasize the importance of using multiple evaluation metrics to assess model performance, and offer suggestions for improving TCR and TCR-pMHC structure prediction tools.

Chemical structure↗
DOE OSTI2023

Human papillomavirus–associated anal squamous cell carcinoma: sociodemographic, geographic, and county-level economic trends in incidence rates—United States, 2001-2019

Abstract Background Incidence of anal squamous cell carcinoma is increasing, but vaccination against human papillomavirus (HPV) and removal of precancerous anal lesions could prevent new cases. The overall HPV-associated cancer incidence is reported to be higher in rural populations and in counties with lower economic status. We assessed these differences specifically for HPV-associated anal squamous cell carcinoma and described the geographic, county-level economic, and sociodemographic variations in incidence rates and trends. Methods We analyzed data from the US Cancer Statistics to assess age-standardized incidence rates of HPV-associated squamous cell carcinomas among adults aged 18 years and older from 2001 to 2019. We calculated rate ratios and 95% confidence intervals to examine differences in incidence rates. We also quantified changes in incidence rates over time using joinpoint regression. Results From 2001 to 2019, 72 421 new cases of HPV-associated anal squamous cell carcinoma were diagnosed among women (2.8 per 100 000) and 37 147 among men (1.7 per 100 000). Age-standardized incidence rates were higher in the South compared with other census regions and in counties ranked in the bottom 25% and 25%-75% economically than in the top 25%. The overall incidence rate increased in women but remained stable in men during 2009-2019. Incidence rates increased in adults aged 50 years and older but decreased among those aged 40-44 years from 2001 to 2019 in women and from 2007 to 2019 in men. Conclusions There were inequities in HPV-associated anal squamous cell carcinoma incidence by geographic and county-level economic characteristics. Failure to improve vaccine and treatment equity may widen existing disparities.

Oncology↗
DOE OSTI2021

Power Electronics Based Self-Monitoring and Diagnosing for Photovoltaics Systems

Self-monitoring and diagnosing technology for photovoltaic (PV) systems is a method to reduce energy production losses. The proposed technology will enable existing panel-level power optimizers and inverters in a PV system to actively perturb the system, measure its response to these small-signal perturbations, and detect any changes in the small-signal impedances. Impedance measurement will be used to identify specific faults and power degradation trends in a PV panel. This information can be used to instantly alert Operations and Maintenance (O&M) personnel of the need for corrective action, thereby reducing energy production losses earlier relative to standard PV systems.

Panchal, Jeet↗
DOE OSTI2024

Trust Model Measurements for the Energy Grid of Things

Information security is essential for the reliable operation of an Energy Grid of Things (EGoT). In addition to basic information security protocols as defined by published standards, there is a need for a monitoring function that measures the trustworthiness of the various actors participating in an EGoT. We describe in this paper the implementation and evaluation of a Distributed Trust Model that was developed specifically for monitoring communication within an EGoT. We then show how the model parameters are set using statistical measures for hypothesis testing.

Energy Grid of Things, EGoT, Smart Grid Security, ↗
DOE OSTI2022

Clang UPC2C Translator (Clang UPC2C) v9.0.1-1

Clang Unified Parallel C 2 C (Clang UPC2C) translator compiles programs written in the UPC (Unified Parallel C) language to ISO C99, with calls to the Berkeley UPC runtime system. The Clang UPC2C compiler extends the capabilities of the Clang LLVM C frontend to comply with the UPC Language Specification version 1.3. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. In addition to the standard UPC libraries, Clang UPC2C also provides access to Berkeley UPC library extensions.

Hargrove, Paul↗
DOE OSTI2025

sourcePy

Pollutant source identification techniques (of which there are many variations) are either locked behind researchers writing their own code for each use case or GUI platforms that are easy to use but inflexible and opaque. The Python package sourcePy brings together many of the pollutant source identification algorithms, giving the user full control out of the box. It aims to create a platform for source identification experiments where the full analysis from beginning to end can be done in Python, with a level of specificity in design that isn't available in the GUI options. sourcePy provides users with a few key features: -A Python interface with HYSPLIT, which can be used to generate trajectories and concentration plumes -Several Python classes which standardize the preparation and processing of data related to source identification experiments -Example scripts and notebooks that allow even new python users to get started with their own experiments quickly -Visualization methods

Arseneau, Isaac [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Machine Learning Framework for Conotoxin Class and Molecular Target Prediction

Conotoxins are small and highly potent neurotoxic peptides derived from the venom of marine cone snails which have captured the interest of the scientific community due to their pharmacological potential. These toxins display significant sequence and structure diversity, which results in a wide range of specificities for several different ion channels and receptors. Despite the recognized importance of these compounds, our ability to determine their binding targets and toxicities remains a significant challenge. Predicting the target receptors of conotoxins, based solely on their amino acid sequence, remains a challenge due to the intricate relationships between structure, function, target specificity, and the significant conformational heterogeneity observed in conotoxins with the same primary sequence. We have previously demonstrated that the inclusion of post-translational modifications, collisional cross sections values, and other structural features, when added to the standard primary sequence features, improves the prediction accuracy of conotoxins against non-toxic and other toxic peptides across varied datasets and several different commonly used machine learning classifiers. Here, we present the effects of these features on conotoxin class and molecular target predictions, in particular, predicting conotoxins that bind to nicotinic acetylcholine receptors (nAChRs). We also demonstrate the use of the Synthetic Minority Oversampling Technique (SMOTE)-Tomek in balancing the datasets while simultaneously making the different classes more distinct by reducing the number of ambiguous samples which nearly overlap between the classes. In predicting the alpha, mu, and omega conotoxin classes, the SMOTE-Tomek PCA PLR model, using the combination of the SS and P feature sets establishes the best performance with an overall accuracy (OA) of 95.95%, with an average accuracy (AA) of 93.04%, and an f1 score of 0.959. Using this model, we obtained sensitivities of 98.98%, 89.66%, and 90.48% when predicting alpha, mu, and omega conotoxin classes, respectively. Similarly, in predicting conotoxins that bind to nAChRs, the SMOTE-Tomek PCA SVM model, which used the collisional cross sections (CCSs) and the P feature sets, demonstrated the highest performance with 91.3% OA, 91.32% AA, and an f1 score of 0.9131. The sensitivity when predicting conotoxins that bind to nAChRs is 91.46% with a 91.18% sensitivity when predicting conotoxins that do not bind to nAChRs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Inpainting Galactic Foreground Intensity and Polarization Maps Using Convolutional Neural Networks

The Deep Convolutional Neural Networks (DCNNs) have been a popular tool for image generation and restoration. In this work, we applied DCNNs to the problem of inpainting non-Gaussian astrophysical signal, in the context of Galactic diffuse emissions at the millimetric and submillimetric regimes, specifically Synchrotron and Thermal Dust emissions. Both signals are affected by contamination at small angular scales due to extragalactic radio sources (the former) and dusty star-forming galaxies (the latter). Furthermore, we compare the performance of the standard diffusive inpainting with that of two novel methodologies relying on DCNNs, namely Generative Adversarial Networks and Deep-Prior. We show that the methods based on the DCNNs are able to reproduce the statistical properties of the ground-truth signal more consistently with a higher confidence level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Repository of HydroSMADE: Hydropower Site-level Monthly Availability Data Ensemble for 1950-2100 at Existing and Potential Global Sites

This repository presents HydroSMADE—Hydropower Site-level Monthly Availability Data Ensemble, a new open dataset that provides monthly hydropower availability for 1,593 existing and 124,333 potential sites worldwide over the period 1950–2100. The dataset is generated by using a global hydrologic model (Xanthos) with explicit representation of hydropower operation. Specifically, HydroSMADE distinguishes between storage and diversion sites, applies optimized operating rules, and incorporates site-specific characteristics such as generation capacity, maximum turbine flow, and reservoir storage. Driven by bias-corrected meteorological inputs, the data is provided for 30 alternative future scenarios. The scenarios consist of the full factorial combination of three standard CMIP6 atmospheric forcing pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) and ten CMIP6 General Circulation Models (GCMs): GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, EC-Earth3, CanESM5, MIROC6, CNRM-ESM2-1, UKESM1-0-LL, and CNRM-CM6-1. The repository contains a total of 122 files: a text file (readme.txt) containing a brief description of the included data, a CSV file containing site attributes, and the remaining 120 files (in CSV) containing site-level monthly hydropower availability. Example Jupyter Notebooks to explore the HydroSMADE dataset are available on GitHub at https://github.com/kamal0013/HydroSMADE More details on the methods and technical validation of HydroSMADE are available in the following paper by the same authors: Chowdhury, A. K., Abeshu, G. W., Zhao, M., Wild, T. B., Hassan, N., Ying, Z., Kim, G. J., Matthew, B., Jonathan, L., & Li, H.-Y. (Submitted). Hydropower Site-level Monthly Availability Data Ensemble for 1950-2100 at Existing and Potential Global Sites.

Existing and Potential Sites↗
DOE OSTI2022

Restoration Hydro: A Watershed Approach to Standard Modular New Hydropower

The objectives of FOA DE- FOA-0001836- “Standard Modular Hydropower” included designing a standardized, modular, and environmentally compatible hydropower schematic for implementation in greenfield sites that generate up to 10 MW of capacity. Utilizing funds competitively awarded under DOE’s Water Power Technologies Office, the Natel Energy team developed a concept for modular new stream reach (NSR) hydropower that incorporates multi species upstream and downstream fish passage, improved river channel connectivity, and recreational modules. The in-stream design of the collective modules minimized site specific design and maximized the opportunities for modularity. Financial data was also presented using actual costs from regional suppliers, with figures provided in 2022 dollars. While the project team did not address potential permitting process improvements, the site selection criteria did consider established barriers to hydropower development such as tribal and preserved lands, interconnection proximity, and endangered species to exclude or deprioritize. The project’s design schematic met the objectives of the FOA, and presented a unique solution that targets alluvial pockets as natural features for sustainable development. Natel’s concept also incorporated the company's fish-safe Restoration Hydro Turbine for safe downstream passage, while featuring a rock arch that integrates fish passage, water, recreation, and grade control modules (including sediment). Alignment with the Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) “Innovative Design Concepts for Standard Modular Hydropower and Pumped-Storage Hydropower” Program: According to the Hydropower Vision (DOE, 2016), approximately 16 GW of hydropower growth is possible with the development of technology solutions that balance efficiency, economics, and environmental sustainability. The desired outcome of the SMH program is transformational innovation specifically in the site identification, conceptual, and detailed design phases of technology development lifecycles (DOE, 2018). In developing the SMH design schematic, the team aimed to address the opportunities outlined in the Vision through an inverted design philosophy; rather than singularly prioritizing efficiency and power production, the team focused on integrating hydropower with restoration of degraded streams to optimal ecosystem function and provision of exceptional recreation value as design criteria. To achieve this, Restoration Hydro incorporates the principles of nature-based engineering (WWAP, 2018) and biomimicry (Biomimicry NL.) to strategically deploy complementary combinations of permanent, semi-permanent, and ephemeral low-head structures - such as natural and engineered log jams - that harness geomorphological and hydrological processes at the landscape-scale. Primary applications of Restoration Hydro include: 1) restoration of degraded watersheds’ natural ecological function and enhancement of hydrological connectivity; and 2) creation of associated co-benefits to hydro production, including increased groundwater recharge, improved sediment transport and management, improved water security and water quality. Restoration Hydro projects build upon proven watershed restoration engineering techniques by integrating hydropower turbines into low-head structures using innovative and evolving civil works concepts that facilitate fish and sediment passage, and in some cases create additional revenue-generating recreational opportunities. Powering low-head structures creates a directly monetizable layer of economic value in the form of flexible, reliable, renewable energy on top of the already high-value water, environmental and recreational benefits of watershed and river restoration. The approach aims to create a virtuous, self-reinforcing cycle whereby Restoration Hydro projects support the scaling of ecosystem restoration activities, creating a water-energy-carbon multiplier effect that, through the principles of adaptive change management: 1) improves the resilience of landscapes and downstream population centers for changing hydrological cycles; 2) creates a reliable energy resource that facilitates the integration of intermittent renewable power sources into grids; and 3) supports climate change mitigation through grid decarbonization and enhanced ecosystem carbon capture and retention.

13 HYDRO ENERGY↗
DOE OSTI2022

Ensuring a Nuclear Power Plant Safe State Following an EMP Event - Task 7 Deliverable: EMP Testing of Secondary Coupling to Instrumentation Cables

Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

PV Performance Modeling and Stakeholder Engagement (Final Technical Report)

This core capability project’s objective is to increase the value of photovoltaic (PV) performance models by improving their functionality, demonstrating, and quantifying their validity, and offering a wide range of stakeholder engagement opportunities. In FY22-24, we developed new and improved modeling algorithms and functions to represent PV performance more accurately in a variety of environments and conditions. The “Model parameter toolkit” was developed and includes functions to translate between different module temperature models, incidence angle modifier models, and single-diode models. A new modeling capability named “PV Atlas” was also developed leveraging Sandia’s High Performance Computing resources. This capability allows us to investigate several questions and provide climate-specific best practices and geographic data files; all these are hosted on an interactive website on Sandia’s GitHub and can be used for training, system optimization, or to provide best practices for uncertainty reduction. For model validation, we published high-quality PV performance, and weather data; these data are well documented, filtered, and processed for quality and include examples on how to run PV simulations. We also developed well documented, standardized methods for validating PV models and ran independent model validation and 2 blind modeling intercomparisons engaging with 49 organizations from 17 countries. We co-led and contributed to a growing, well documented and maintained suite of open-source functions for PV modeling (i.e., the pvlib-python) and we outreached to the PV modeling stakeholders via the PVPMC workshops and web resources. In addition, this project supported US representation and leadership for the International Energy Agency (IEA) PVPS Task 13; specifically, members of our team led and supported 3 subtasks on: 1) Best practices for the optimization of bifacial photovoltaic tracking, 2) Extreme weather events and their multiple impact on PV power plants: Risks, failure mechanisms and mitigation strategies, and 3) Best practice guidelines for the use of economic and technical Key Performance Indicators (KPIs). This project resulted in the publications of 14 peer reviewed journal papers, 37 conference presentations, 6 SAND reports, 5 public datasets and 6 new webpages on the PVPMC website. It supported the release of 13 pvlib-python versions where 28 enhancements were from this PV Performance Modeling project. We co-organized 5 PVPMC workshops in FY22-24 with the participation of 214 unique institutions and around 700 participants. The PVPMC website was redesigned, and its reliability was improved; it receives over 50,000 visitors/year from 202 unique countries.

14 SOLAR ENERGY↗
DOE OSTI2021

Valuing wind as a distributed energy resource: A literature review

As more distributed energy resources are deployed on electric grid systems across the world, it is important to identify, characterize, and quantify the value elements of different types of distributed energy resources so that policymakers, developers, and utilities can make informed energy deployment decisions. This paper focuses on the value of wind energy as a distributed energy resource (i.e., “distributed wind”). Because of a lack of distributed wind-specific valuation studies, in this review we document the current state of distributed energy resource valuation, analyze a wide array of distributed energy resource valuation metastudies, and identify several value elements for which we recommend developing more robust and standardized calculation methodologies for their potential inclusion in distributed wind valuation. These value elements are ancillary services and locational, resilience, reliability, and resource diversity benefits. Furthermore, this work lays the foundation for a future comprehensive framework for distributed wind valuation studies.

17 WIND ENERGY↗
DOE OSTI2024

Two-dimensional perovskite templates for durable, efficient formamidinium perovskite solar cells

We present a design strategy for fabricating ultrastable phase-pure films of formamidinium lead iodide (FAPbI 3 ) by lattice templating using specific two-dimensional (2D) perovskites with FA as the cage cation. When a pure FAPbI 3 precursor solution is brought in contact with the 2D perovskite, the black phase forms preferentially at 100°C, much lower than the standard FAPbI 3 annealing temperature of 150°C. X-ray diffraction and optical spectroscopy suggest that the resulting FAPbI 3 film compresses slightly to acquire the (011) interplanar distances of the 2D perovskite seed. The 2D-templated bulk FAPbI 3 films exhibited an efficiency of 24.1% in a p-i-n architecture with 0.5–square centimeter active area and an exceptional durability, retaining 97% of their initial efficiency after 1000 hours under 85°C and maximum power point tracking.

14 SOLAR ENERGY↗