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DOE OSTI2026

Data and scripts associated with a manuscript modeling microbial regulation of priming effects

This data package is associated with the publication “Modeling Microbial Regulatory Feedback in Organic Matter Decomposition Identifies Copiotrophic Traits as Key Drivers of Positive Priming” published as a preprint on BioRXiv by Ahamed et al. (2026); https://doi.org/10.1101/2024.08.11.607483. The package contains MATLAB scripts and saved simulation outputs used to implement a cybernetic model of microbial regulation during complex organic matter (OM) decomposition governing priming effects. It includes models of (i) single microbial functional groups (copiotrophic or oligotrophic degraders) and (ii) binary consortia composed of degraders and non-degraders with contrasting or common growth traits. Simulation results were generated using Monte Carlo analyses, with randomized key model parameters across a range of environmental mixing fractions of complex and labile OM. The dataset was created to provide a transparent and reusable computational framework for systematically exploring how microbial growth traits, metabolic regulation, and community composition influence OM decomposition dynamics and priming effects. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes the variable definitions. This package includes: (1) annotated MATLAB code implementing the system of ordinary differential equations and cybernetic control laws; (2) saved output files containing data (e.g., biomass, substrates, enzyme levels, priming metrics); and (3) scripts for processing saved outputs and regenerating figures. Specifically, the data package contains three main MATLAB scripts: runPrimingModel.m, runPlotData.m, and runPlotSuppFigS1.m, along with this readme and supporting documentation. Users should begin with runPrimingModel.m, which contains the annotated code implementing the system of ordinary differential equations and cybernetic control laws. This script runs the Monte Carlo simulations of microbial OM decomposition and allows users to modify microbial trait definitions, adjust parameter distributions, or define new community configurations. Simulation outputs are automatically saved as .mat files in the folder named SavedData, which stores all pre-generated results included in this package. The second script, runPlotData.m, reads files from the SavedData folder and processes them to regenerate the figures presented in the manuscript. The third script, runPlotSuppFigS1.m, specifically generates Figure S1 in the Supplementary Material of the manuscript. The package also includes the aforementioned files in non-proprietary .txt format. If users intend to use them, they should first save the files in their respective .m or .mat formats prior to execution in MATLAB.

Biomass concentration↗
DOE OSTI2021

A Systematic Interpretation of Subsurface Proppant Concentration from Drilling Mud Returns: Case Study from Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin

The aim of this study is generation and validation of a proppant log using analysis of drilling mud returns for child wells. Proppant log provides qualitative as well as quantitative insights into spatial distribution of proppant sand particles from prior stimulation of parent wells. While the basic methodology was developed and formalized during analysis of material collected from through fracture cores at Hydraulic Fracturing Test Site in Midland Basin (HFTS – 1), the test wells at HFTS – 2 in the neighboring Delaware Basin allowed the opportunity to validate the workflow on actual mud return samples from subsurface. As a child well is being drilled, periodic mud return samples are collected at the rig site and preserved for analysis. The workflow involves systematic cleaning of the samples including various steps such as washing, drying and segregation of samples into relevant size fractions of interest (< Mesh 20) based on specifications of pumped sand during stimulation of the parent well. Clean samples are imaged using high resolution transparency scanning. Scan images are then systematically analyzed for particles of interest using computer vision techniques. Sample counts are further validated using elemental analysis of smaller sub-samples at various depths of interest. This step is necessary to isolate proppant versus other naturally occurring minerals such as sulphates and carbonates which show similar optical properties. We successfully correlated proppant distribution against the existing parent well and validated propped versus relatively un-propped zones for a child well at the test site. The advantage of testing the proppant log concept at the HFTS – 2 site is the plethora of additional diagnostic data that is available to validate our primary observations. We can correlate spatial proppant distribution against variability in stimulation response based on independent observations such as image logs, microseismic attributes as well as DAS response, all of which tend to corroborate one another. One of our significant successes was being able to describe varying degrees of impact of the parent well along the lateral length of a stimulated child well. Our workflow represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling child wells. This provides unique opportunities to better understand the current state of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R003/2477415/urtec-2021-5189-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5189 2 reservoir being targeted including zones which are likely more drained relative to others and how the planned completion of the child well can be improved. Lastly, this log can be useful is validating optimal well spacing in relatively new fields under development.

58 GEOSCIENCES↗
DOE OSTI2026

Do solar panels contain PFAS?

The presence and potential leaching of PFAS (Per- and Polyfluoroalkyl Substances) from solar panels are increasingly mentioned in news articles, raising public concerns. Such concerns may slow the adoption of photovoltaic (PV) technology, despite its central role in the renewable energy sector. The limited transparency from manufacturers about fluorinated materials used in PV modules, along with the scarcity of publicly available testing data, contributes to uncertainty and speculation. This perspective aims to clarify the current state of PFAS presence in solar PV. Although certain fluoropolymers are used in PV manufacturing, the scientific consensus on their toxicity indicates they should not be classified as PFAS. Portraying fluoropolymers as toxic PFAS unnecessarily amplifies concerns and unfairly undermines the perceived environmental sustainability of PV technology.

environmental impact↗
DOE OSTI2023

Electrochemical Synthesis of Monodisperse Platinum-Cobalt Nanocrystals

The synthesis of platinum-cobalt nanocrystals (NCs) using colloidal solvothermal techniques is well understood. However, for monodisperse NCs to form, high temperatures and environmentally detrimental solvents are needed. We report a room temperature, aqueous method of platinum-cobalt NC synthesis using electrochemical reduction as the driving force for nucleation and growth. It is found that colloidal NCs will form in both the presence and absence of surfactant. Additionally, we report a monodisperse electrochemical deposition of NCs utilising a transparent conducting oxide electrode. The methods developed here will allow for a synthetic method to produce nanocatalysts with minimal environmental impact and should be readily applicable to other NC systems, including single- and multi-component alloys.

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

Wire-arc Additive Manufacturing Benchmark

This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.

Bachus, Nicholas [UC Davis, Davis, CA]↗
DOE OSTI2026

Lifetime extension of legacy CEBAF LLRF hardware

A significant portion of the Low-Level Radio Frequency (LLRF) hardware in Jefferson Lab’s CEBAF is from the original construction of the facility using 1980’s CAMAC technology. Of the fifty-three zones in CEBAF, thirty-six of them are legacy hardware. The age of the legacy system has led to difficulties in maintaining the hardware due to parts going obsolete without suitable drop in replacements. Continued operation of the legacy system is required as the installation of LLRF 3.0 systems is costly and cannot be completed in a short period of time with the available resources. The most pressing failure in the legacy system was a failing buffer card, which is responsible for communication between the EPICs network and individual RF control modules. A new buffer card was designed as a transparent, drop in, replacement so that upgrades are simply a matter of swapping the existing legacy hardware. This buffer card upgrades a single point failure component and promises to extend the operable lifetime of CEBAF’s legacy systems.

Accelerator Physics↗
DOE OSTI2026

ORCHID: Orchestrated Retrieval-Augmented Classification of High-Risk Property with Intelligent Decision-Making

High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must track evolving rules designated by various export control policies to make transparent and auditable decisions. Traditional expert-only workflows are time-consuming, backlog-prone, and struggle to keep pace with shifting regulatory boundaries. We propose ORCHID, a modular agentic framework for HRP classification that pairs retrieval-augmented generation (RAG) with human oversight to produce policy based outputs that can be audited. Small cooperating agents—retrieval, description refiner, classifier, validator, and feedback logger—coordinate via agent-to-agent messaging and invoke tools through the Model Context Protocol (MCP) for model-agnostic on-premise operation. The interface follows an "Item to Evidence to Decision" loop with step-by-step reasoning, on-policy citations, and append-only audit bundles (run-cards, prompts, evidence). In preliminary tests on real HRP cases, ORCHID improves accuracy and traceability over a non-agentic baseline while deferring uncertain items to Subject Matter Experts (SMEs). The demonstration shows single item submission, grounded citations, SME feedback capture, and exportable audit artifacts—illustrating a practical path to trustworthy LLM assistance in sensitive DOE compliance workflows.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2026

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗
DOE OSTI2024

gcamfaostat: An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling

The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat (v1.0) and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. One of the important features of the package is the possibility to construct the FAO Food Balance Sheets at the disaggregated commodity level (with over 500 commodities), which provides a comprehensive and detailed data input for a variety of analytical and modeling applications. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗
DOE OSTI2021

Seaborgite, LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), the First Uranyl Mineral Containing Lithium

Abstract Seaborgite (IMA2019-087), LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), is a new mineral species from the Blue Lizard mine, Red Canyon, San Juan County, Utah, U.S.A. It is a secondary phase found on gypsum in association with copiapite, ferrinatrite, ivsite, metavoltine, and römerite. Seaborgite occurs in sprays of light-yellow, long flattened prisms or blades, up to about 0.2 mm in length. Crystals are elongated on [100], flattened on {010}, and exhibit the forms {100}, {010}, {001}, and {101}. The mineral is transparent with vitreous luster and very pale-yellow streak. It exhibits bright lime-green fluorescence under a 405 nm laser. The Mohs hardness is ~2½. The mineral has brittle tenacity, curved or conchoidal fracture, and one good cleavage on {100}. The measured density is 2.97(2) g/cm3. The mineral is immediately soluble in H2O at room temperature. The mineral is optically biaxial (–), α = 1.505(2), β = 1.522(2), γ = 1.536(2) (white light); 2Vmeas = 85(1)°; moderate r < ν dispersion; orientation X ^ a ≈ 10°; pleochroic X colorless, Y and Z light green-yellow; X < Y ≈ Z. EPMA and LA-ICP-MS analyses of seaborgite undermeasured its Li, K, and Na. The empirical formula using Li, Na, and K based on the structure refinement is Li1.00Na5.81K2.19(UO2)(SO4)5(SO3OH)(H2O). Seaborgite is triclinic, P1, a = 5.4511(4), b = 14.4870(12), c = 15.8735(15) Å, α = 76.295(5), β = 81.439(6), γ = 85.511(6)°, V = 1203.07(18) Å3, and Z = 2. The structure (R1 = 0.0377 for 1935 I = 2σI) contains [(UO2)2(SO4)8]4– uranyl-sulfate clusters that are linked into a band by bridging LiO4 tetrahedra. The bands are linked through peripheral SO4 tetrahedra forming a thick heteropolyhedral layer. Channels within the layers contain a K site, while an additional K site, six Na sites, and an SO3OH group occupy the space between the heteropolyhedral layers.

Geochemistry & Geophysics↗
DOE OSTI2024

Bobfinchite, Na[(UO2)8O3(OH)11]·10H2O, a new Na-bearing member of the schoepite family

Abstract The new mineral bobfinchite (IMA2020-082), Na[(UO2)8O3(OH)11]·10H2O, was found in the Burro mine, Slick Rock district, San Miguel County, Colorado, U.S.A., where it occurs as an oxidation product of uraninite on asphaltite matrix in intimate association with gypsum, natrozippeite, metaschoepite, and uranopilite. Bobfinchite crystals are transparent to translucent, yellow, lozenge-shaped disks up to 0.3 mm wide. Crystals are flattened on [100] and exhibit the forms {100}, {011}, {021}, {021}, and {011}. Bobfinchite has a pale-yellow streak and emits very dim yellow fluorescence under 365 nm ultraviolet illumination. The crystals are brittle with very good {100} cleavage and irregular, stepped fracture. The Mohs hardness is ca. 2 based on scratch tests. The calculated density is 5.044 g/cm3 based on the empirical formula and 5.036 g/cm3 for the ideal formula. Bobfinchite is optically biaxial (–), with α = 1.690(5), β = 1.7205(5), and γ = 1.730(5) (white light). The measured 2V, estimated from the interference figure, is 55(5)° and the calculated value is 59.1°. Dispersion is moderate, r > v; orientation: X = a, Y = b, Z = c; pleochroism: X nearly colorless, Y yellow, Z yellow; X < Y ≈Z. Electron microprobe analysis provided the empirical formula (Na0.99Pb0.02)[(UO2)7.99O3(OH)11]·10H2O. The five strongest X-ray powder diffraction lines are [dobs in Å(I)(hkl)]: 7.34(100)(200), 3.59(50)(024), 3.23(60)(224), 3.18(36)(240), and 2.01(23)(624,551,208,640,346). Bobfinchite is orthorhombic, Pbcn, a = 14.6249(9), b = 14.0389(10), c = 16.6923(10) Å, V = 3427.2(4) Å3, and Z = 4. The structure of bobfinchite (R1 = 0.0330 for 3770 I > 4σI) is built from uranyl oxide-hydroxide sheets that adopt the fourmarierite topology, with interlayer Na+ and H2O groups. Both the sheet and interlayer topology mimic those observed in natural and synthetic Na-metaschoepites studied previously, and as seen in other uranyl oxide hydrate minerals, charge balance is achieved at specific sites in the sheet through the substitution O2– ↔ (OH)–.

Geochemistry & Geophysics↗
DOE OSTI2025

Screening analysis of enhanced weathering of igneous rocks and industrial waste materials

Enhanced weathering (EW) is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. This manuscript reports on a screening level techno-economic analysis of EW. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The modeled EW process encompasses material purchase, comminution, transport, distribution of material on farmland, and measurement, reporting and verification of CO2 removal. Detailed sensitivities are performed to highlight promising scenarios for application. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured (less than $100 per total tonnes of CO2 captured from the atmosphere). NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

Leptinsky, Sarah [NETL Site Support Contractor, Na↗
DOE OSTI2022

Mean string field theory: Landau-Ginzburg theory for 1-form symmetries

By analogy with the Landau-Ginzburg theory of ordinary zero-form symmetries, we introduce and develop a Landau-Ginzburg theory of one-form global symmetries, which we call mean string field theory. The basic dynamical variable is a string field – defined on the space of closed loops – that can be used to describe the creation, annihilation, and condensation of effective strings. Like its zero-form cousin, the mean string field theory provides a useful picture of the phase diagram of broken and unbroken phases. We provide a transparent derivation of the area law for charged line operators in the unbroken phase and describe the dynamics of gapless Goldstone modes in the broken phase. The framework also provides a theory of topological defects of the broken phase and a description of the phase transition that should be valid above an upper critical dimension, which we discuss. We also discuss general consequences of emergent one-form symmetries at zero and finite temperature.

Iqbal, Nabil↗
DOE OSTI2020

Getting to Neutral: Options for Negative Carbon Emissions in California

This report is an assessment of negative emissions pathways - ones that physically remove CO 2 from the atmosphere - that can help California achieve carbon neutrality by 2045, or sooner. It integrates original research findings with current published research on three main pillars of negative emissions: natural and working lands, carbon capture from biomass conversion to fuels, and direct air capture. The focus and scope of this report is unique: it only addresses practices and technologies for removing carbon dioxide from the air. It also encompasses the entire breadth of strategies, from land management to the latest technological options, and it evaluates the cost of every step of the solution, from waste biomass collection to carbon dioxide transport and geologic storage. The methods are intended to be transparent; details of the calculations and underlying data are included in the report body and appendices. This study intentionally avoids any discussion of policies and does not include current incentives; it provides a range of options, tradeoffs and costs that can be used to inform future policies. The key finding of this report is that carbon neutrality is achievable.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

5G Enabled Energy Innovation: Advanced Wireless Networks for Science (Workshop Report)

Rapidly expanding, new telecommunications infrastructure based on 5G technologies will disrupt and transform how we design, build, operate, and optimize scientific infrastructure and the experiments and services enabled by that infrastructure, from continental-scale sensor networks to centralized scientific user facilities, from intelligent Internet of Things devices to supercomputers. Concurrently, 5G will introduce, or exacerbate, challenges related to protecting infrastructure and associated scientific data as well as to fully leveraging opportunities related to expanded infrastructure scale and complexity. The U.S. Department of Energy (DOE) Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. Along with field experiments and remote observatories, every aspect of DOE’s scientific enterprise will be affected by 5G, which amounts to a complete renovation of the underpinnings of the nation’s information infrastructure. In this report we explore the scientific opportunities and new research challenges associated with 5G, ranging from scalability to heterogeneity to cybersecurity. The rapid commercial deployment of 5G opens the opportunity to rethink and reinvent DOE’s scientific infrastructure and experimentation, from intelligent sensor networks at unprecedented scales to a digital continuum of cyberinfrastructure spanning low-power sensors, high-performance computing embedded within and at the edge of the network, and DOE’s large-scale user instrument and computing facilities. New programming paradigms, workflow and data frameworks, and AI-based system design, operation, and autonomous adaptation and optimization will be necessary in order to exploit these new opportunities. Field deployments and centralized scientific instruments can also be revolutionized, moving (without traditional performance penalties) from wired to wireless connectivity for data and control systems, improving flexibility, and opening new sensing modalities, including the use of the 5G electromagnetic spectrum itself as an environmental probe. For DOE science, in contrast to commercial 5G applications and settings, devices will be deployed in extreme environments such as cryogenically cooled instrument control systems and in remote settings with harsh conditions, requiring the design of new materials for RF communication and edge processing to operate in these regimes. Concurrently, 5G infrastructure comprises both hardware and sophisticated software systems - currently closed and proprietary. The cybersecurity challenges to 5G-empowered reinvention mirror the complexity and variety of new 5G features, from virtualization to private network slices to ubiquitous access. Research is also needed in order to accelerate the development of secure and open 5G software infrastructure, reducing reliance on hardware and software produced outside the United States and providing the transparency and rigorous evaluation and testing afforded through open software. Twelve broad research thrusts are laid out in four chapters, with a companion fifth chapter (and three additional research thrusts) underscoring the needs and opportunities for an aggressive testbed program co-designed by networking experts and scientists involved in the 15 research thrusts. The urgency of undertaking this research is fueled by a global, accelerating deployment of new telecommunications infrastructure that is designed for entertainment and commercial applications - barely scratching the surface of what 5G can do to extend U.S. leadership in scientific discovery.

42 ENGINEERING↗
DOE OSTI2020

Wide Band-Gap Perovskites for Tandem Photovoltaics

This research was aimed at development of a mechanically-stacked, perovskite Multi-Junction Solar Cell in which (1) at least one Junction is made of metal-halide perovskite and (2) the Junctions are manufactured in parallel and then stacked to create the final module. This technology presented significant advanced manufacturing challenges and opportunities in getting to scale, including materials scale-up and the development of novel roll-to-roll processing and encapsulation methods. Research conducted was also applicable to a monolithically-integrated perovskite Multi-Junction Solar Cell, in which the two or more Junctions are integrated and electrically connected. The project explored the following technical opportunities in conjunction with the Cyclotron Road mentored entrepreneurial research experience: Fabrication of inorganic heterojunction layers on both sides of a perovskite semiconductor, and modification of interfaces; developed transparent electrode layers on both sides of a perovskite semiconductor; and developed a prototype and optimized perovskite Junction Solar Cell.

14 SOLAR ENERGY↗
DOE OSTI2020

Beryllium (Be) Handbook

Beryllium (Be), atomic number 4, is a silver gray metal of low density (1.85g/cm 3 ), moderately high melting point (1289°C), and quite good stability in the atmosphere. Favorable mechanical properties, particularly specific stiffness (elastic modulus/density), have resulted in a number of weight-critical structural applications. Other notable properties of beryllium include good dimensional stability, high specific heat and extremely high transparency to X-radiation. The nuclear properties of beryllium include a high neutron scattering cross section (6 barns for thermal neutrons) and a low neutron absorption cross section (0.009 barns for thermal neutrons) making it a good choice for a neutron reflector. The (n, 2n) reaction in beryllium also makes it suitable for a neutron multiplier.

36 MATERIALS SCIENCE↗