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DOE OSTI2024

Data associated with the manuscript “Radiative impact of record-breaking wildfires from integrated ground-based data” collected in Richland, Washington in September 2020

This data package is associated with the publication “Radiative impact of record-breaking wildfires from integrated ground-based data” submitted to Nature Scientific Reports (Kassianov et al., 2024). Data from ground-based measurements of shortwave and spectrally resolved irradiance and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges were assessed to quantify the radiative impact of the September 2020 wildfires that occurred in the Western United States. Data were collected in September 2020 by several ground-based instruments at the Atmospheric Measurements Laboratory (AML) located in Richland, Washington (46.3451, -119.2792). These data include (1) Aerosol Optical Depth (AOD); (2) spectrally resolved and shortwave (SW) irradiances; (3) backscatter profiles; (4) total sky images; and (5) near-surface ambient air temperatures.The data package consists of five sub-directories: (1) “AML_Ceilometer_”; (2)” AML_CSPHOT_”; (3) “AML_MFRSR_irradiances_”; (4) “AML_SW_irradiances_and_Temp_”; (5) “AML_TSI_images_”; and 6 files stored at the directory level, including the readme, file-level metadata file, and data dictionary. The file-level metadata file (the file ending in “_flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (the file ending in “_dd.csv”) describes each tabular column header’s unit, definition, and structure. Below are descriptions of each sub-directory:“AML_Ceilometer_” includes ceilometer data collected at the AML. These files contain the corresponding narratives of data. Details related to the ceilometer data can be found in Morris (2016). “AML_CSPHOT_” includes ascii files with high-temporal resolution (about 10-15 min) AML CSPHOT data and their daily-averaged counterparts. These two files contain the corresponding narratives of data. Details related to the CSPHOT data can be found in Gregory (2011). “AML_MFRSR_irradiances_” includes ascii files with the AML MFRSR-measured diffuse, normal, and total spectrally resolved irradiance. Details related to the MFRSR data can be found in Hodges and Michalsky (2016) and Koontz et al. (2013). “AML_SW_irradiances_+_Temp_” includes near-surface ambient air temperature and SW irradiances, namely direct normal, diffuse hemispherical, and total hemispheric (global), measured at the AML. These files also incorporate the corresponding narratives of data. Details related to the SW irradiances can be found in Andreas et al. (2018). “AML_TSI_images_” includes Total Sky Images (TSIs) collected at the AML. Details related to the TSI data can be found in Morris (2005).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Multi-omics data resource: Data package 22 (Pck022)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines. The data package consists of isolated pancreatic islets from adult male C57BL6/J mice treated with IL-1β, IFNγ or IL-1β + IFNγ for 6 h and submitted for scRNA-seq. This study focused on understanding the heterogeneity of the cytokine-mediated response. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE156175 Publication: 10.26508/lsa.202000949

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2021

Chemical Kinetics of the Autoxidation of Poly(ethylenimine) in CO 2 Sorbents

The oxidative degradation rates of a CO 2 sorbent composed of a mesoporous alumina impregnated with poly- (ethylenimine) (PEI) are measured under systematically varied conditions and a reaction rate law is created. Good agreement is shown between the rate of oxidation obtained via in situ calorimetric heat measurement during oxidative degradation reactions and the loss of CO 2 capture performance presented as amine efficiency (mol CO 2 /mol amine). PEI mass loss and elemental composition are tracked over the course of the reaction and used in conjunction with the oxidation rate measurements to shed insight into the oxidation reaction(s). These data, in combination with measurements of the heat of reaction, suggest a common reaction set across the range of temperatures, oxygen concentrations, and sorbent compositions tested. The data are consistent with the basic autoxidation scheme (BAS), the accepted mechanism of autoxidation of aliphatic polymers. We propose a lumped kinetic model to describe the oxidation reaction set and estimate an activation energy of 105 kJ/mol and an oxygen reaction order of 0.5–0.7 from the data accordingly. Furthermore, these parameters can be incorporated into process cycle models to estimate the material lifetime, a critical uncertainty in the deployment of DAC technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

A primer on artificial intelligence in plant digital phenomics: embarking on the data to insights journey

Artificial intelligence (AI) has emerged as a fundamental component of global agricultural research that is poised to impact on many aspects of plant science. In digital phenomics, AI is capable of learning intricate structure and patterns in large datasets. We provide a perspective and primer on AI applications to phenome research. We propose a novel human-centric explainable AI (X-AI) system architecture consisting of data architecture, technology infrastructure, and AI architecture design. We clarify the difference between post hoc models and 'interpretable by design' models. We include guidance for effectively using an interpretable by design model in phenomic analysis. We also provide directions to sources of tools and resources for making data analytics increasingly accessible. In conclusion, this primer is accompanied by an interactive online tutorial.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

A Measurement of the CMB E-mode Angular Power Spectrum at Subdegree Scales from 670 Square Degrees of POLARBEAR Data

In this work, we report a measurement of the E-mode polarization power spectrum of the cosmic microwave background (CMB) using 150 GHz data taken from 2014 July to 2016 December with the POLARBEAR experiment. We reach an effective polarization map noise level of 32 μK-arcmin across an observation area of 670 square degrees. We measure the EE power spectrum over the angular multipole range 500 ≤ ℓ < 3000, tracing the third to seventh acoustic peaks with high sensitivity. The statistical uncertainty on E-mode bandpowers is ~2.3 μK 2 at ℓ ~ 1000, with a systematic uncertainty of 0.5 mK 2 . Furthermore, the data are consistent with the standard ΛCDM cosmological model with a probability-to-exceed of 0.38. We combine recent CMB E-mode measurements and make inferences about cosmological parameters in ΛCDM as well as in extensions to ΛCDM. Adding the ground-based CMB polarization measurements to the Planck data set reduces the uncertainty on the Hubble constant by a factor of 1.2 to H0 = 67.20 ±0.57 km s -1 Mpc -1 . When allowing the number of relativistic species (Neff ) to vary, we find N eff = 2.94 ±0.16, which is in good agreement with the standard value of 3.046. Instead allowing the primordial helium abundance (Y He ) to vary, the data favor Y He = 0.248 ±0.012. This is very close to the expectation of 0.2467 from big bang nucleosynthesis. When varying both Y He and N eff , we find N eff = 2.70 ±0.26 and Y He = 0.262 ±0.015.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Feedback on Forty-year Long Clean-up Operations of a Contaminated Soil for Environmental Purpose - 20026

One of the CEA facilities in France is the place of miscellaneous mapping and clean-up operations since the 1980's. The final purpose of the conducted work deals with the environmental remediation of the building. In France, the absence of a regulatory framework for the management of sites polluted by radioactive substances, especially as the lack of release thresholds, has led to develop different approaches of soil radiological characterization. The geostatistical approach is part of them. Preliminary investigations are an unavoidable step prior to clearance and remediation. First, historical analysis enables to define site perimeters to investigate as well as to precisely locate expected contaminated parts. For radioactive pollutants, the media (water, soil, air) and transfer routes participate in the definition of the investigation perimeter and thus also need to be identified through a geological study. At the same time, functional analysis leads to choose the best measurement means which could provide useful information when combined with visual inspection. An equipment well adapted to easy-to-measure radionuclides as gamma emitters, such as gamma probe or on-site gamma spectrometry, is usually selected as a non-destructive assay. Coupled with spatial positions, processed on-site radiological data can be mapped. Data processing consists in mapping and kriging before a geostatistical analysis in order to identify the zones of interest to be targeted. Selected zones are not only linked to high level count rates but also to low level ones so that a pollution-free reference is known in the area. This data processing also enables to categorize waste types according to their origin and contamination levels. An expected volume of different waste then follows as well as the waste characterization equipments. In-depth investigations, e.g. core drillings and samplings, naturally ensue to aim at remediation optimization through the assessment of environmental impact. After clean-up operations, non-destructive assays as well as destructive samplings enable to check the effective clearance. Following this methodology in the present remediation work, results of the first non-destructive assay campaign highlighted a long-lived transuranic radionuclides contamination in the concrete flagstone. Successive non-destructive assays were then performed in the defined zones of interest. Count rates measured with a surface probe were first mapped. The best localization of destructive assays, i.e. core drillings at a 1 meter depth, came from this surface mapping followed by a geostatistical analysis. The concrete flagstone was totally removed. Then, the depth of soil to remove under the flagstone was optimized from the results of radiological activities measured in core drillings samples. A new surface mapping was then drawn after this partial soil excavation. The sand and demolition rubble samples, homogeneously constituted from the flagstone fragments, were analyzed by gamma spectrometry. Meanwhile, waste drums and other containers were also measured by gamma spectrometry and passive neutron measurement devices. All these results have brought miscellaneous pieces of information. In this context, major issues appear in terms of physical constraints such as the premises tininess as well as of soil sampling techniques and in terms of measurement performances assessment and the representativeness of homogeneous samples. The choice of radiological soil and waste characterization devices is described in the light of enhanced performances by keeping in mind radiation protection requirements and a willing to always optimize waste categories (very low level waste) and volume. The improvement of the characterization methods appears through this forty-year long work while sharing the feedback of encountered difficulties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Water heating energy use reductions from EPA WaterSense lavatory plumbing fittings

Hot water savings from water-efficient lavatory fittings lead to reductions in water heating energy consumption, and ultimately to decreases in carbon emissions. This paper characterizes existing and proposed approaches used to estimate hot water savings and carbon emissions reductions stemming from the U.S. Environmental Protection Agency's WaterSense program. Also described are refinements that improve the accuracy of residential hot water use percentage estimates of lavatory fittings. The authors conclude that (1) hot water percentages for showers and faucets calculated using up-to-date, publicly available national data are consistent with those found by regional studies and household-level models of water use; (2) the accuracy of heating energy savings estimates attributable to WaterSense-labeled lavatory products, as well as associated emissions reductions, can be refined by modifying the existing energy factor/uniform energy factor (EF/UEF)-based estimation approach with available data. The refined approach accounts for more nuanced conditions than the EF/UED-based approach but depends on data not always available; and (3) the approaches described and intermediate outputs can be generalized for other water conservation programs or estimating purposes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Cloud Shortwave Optical Properties

The data set consists of calibrated zenith shortwave spectral radiances (400-950 nm and 940-1665 nm) and cloud optical depth (COD) retrievals every 2 seconds. The field of view is 0.5 degree. Retrievals of cloud droplet effective radius and thermodynamic phase are currently experimental and done offline. Effective radius and phase are not in this data set.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Structural Investigation of Six Quinary Sulfides Synthesized via the Flux-Assisted Boron-Chalcogen Mixture (BCM) Method: Eu 2+ Containing Members of the RE 3 MTQ 7 (M and T = Transition or Main Group Metals, Q = Chalcogens) Family

For this work, a series of six quinary rare-earth sulfides Ce 4+ 1.85 Eu 2+ 1.15 Na 0.30 SiS 7 , Ce 4+ 1.91 Eu 2+ 1.09 K 0.18 SiS 7 , Ce 4+ 1.96 Eu 2+ 1.04 Rb 0.08 SiS 7 , Ce 4+ 1.98 Eu 2+ 1.02 Cs 0.05 SiS 7 , Ce 4+ 1.97 Eu 2+ 1.03 Ag 0.06 SiS 7 , and Ce 4+ 1.50 Eu 2+ 1.50 CuSiS 7 were obtained in an alkali iodide flux using the boron-chalcogen mixture (BCM) method. Single crystal X-ray diffraction was used to determine the structures of the high quality single crystals that were grown; their elemental compositions were confirmed by energy-dispersive spectroscopy (EDS). The compounds crystallize in the hexagonal crystal system in the noncentrosymmetric space group P63. The crystal structure consists of a three-dimensional network composed of mixed cerium and europium bicapped trigonal prisms, isolated SiS4 tetrahedra, and monovalent metals (Na, K, Rb, Cs, Ag, and Cu) located in cavities created by linked Ce/EuS 8 polyhedra. The structures are charge-balanced when Ce and Eu are in their +4 and +2 oxidation states, respectively. The effective magnetic moment of Ce 1.50 4+ Eu 1.50 2+ CuSiS 7 determined from the temperature dependence of the magnetic susceptibility data is consistent with the presence of Ce 4+ and Eu 2+ . Clear correlations between the alkali ion site occupancy, the ionic radius of the alkali cations, and the average bond length of Ce 4+ /Eu 2+ –S, were established. UV–vis diffuse reflectance data were collected for Ce 1.50 4+ Eu 1.50 2+ CuSiS 7 and a band gap of 1.9(1) eV was established.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Multi-omics data resource: Data package 23 (Pck023)

The data package consists of isolated pancreatic islets from adult male C57BL6/J mice treated with IL-1β + IFNγ, IL-1β + IFNγ + NMMA, or NMMA alone for 18 h and submitted for scRNA-seq. This study focused on the cell-type-specific effects of nitric oxide signaling in islets and characterized the heterogeneity of responses. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE183010 Publication: 10.1093/function/zqab063

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2023

Data assimilation in operator algebras

We develop an algebraic framework for sequential data assimilation of partially observed dynamical systems. In this framework, Bayesian data assimilation is embedded in a nonabelian operator algebra, which provides a representation of observables by multiplication operators and probability densities by density operators (quantum states). In the algebraic approach, the forecast step of data assimilation is represented by a quantum operation induced by the Koopman operator of the dynamical system. Moreover, the analysis step is described by a quantum effect, which generalizes the Bayesian observational update rule. Projecting this formulation to finite-dimensional matrix algebras leads to computational schemes that are i) automatically positivity-preserving and ii) amenable to consistent data-driven approximation using kernel methods for machine learning. Moreover, these methods are natural candidates for implementation on quantum computers. Applications to the Lorenz 96 multiscale system and the El Niño Southern Oscillation in a climate model show promising results in terms of forecast skill and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Biogeochemistry of Pond B (Savannah River Site, South Carolina, USA): Water column and Sediments

Pond B at Savannah River Site (SRS, South Carolina) is a monomictic reservoir that received SRS R reactor cooling water from 1961–1964. Previous studies conducted between the 1980s–1990s on the water column and sediments of Pond B measured trace amounts of Pu (33 MBq 238Pu and 430 MBq 239,240Pu), 241Am, and 137Cs. Since then, the pond has been relatively isolated and the radionuclide concentrations have not been monitored over time. Herein, about 30 years after the last publication on Pond B, we are re-evaluating the geochemistry and radionuclide distribution within Pond B at five locations along a horizontal transect from the inlet to outlet. In addition, we are conducting the first analysis of the microbial community composition. This data package consists of water column measurements (1) using a multi-probe sonde, (2) plutonium isotopes and total concentrations, (3) total organic/inorganic carbon concentrations, (4) trace metals and major ions concentrations, and (6) microbial community composition. Sediment measurements include (1) plutonium isotopes and total concentrations and (2) microbial community composition.For sediment core and porewater, please see other Pond B data package (ess-dive-60d2352a4495472-20200615T203925174).The data in this package will be submitted for peer review in 2023.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: I. Fully vibrationally-resolved electronic excitation of H 2 $X^1Σ^+_g)$

Here, we present a comprehensive set of vibrationally-resolved cross sections for electron-impact electronic excitation of molecular hydrogen suitable for implementation in collisional-radiative models. The adiabatic-nuclei molecular convergent close-coupling method is used to calculate cross sections for excitation of all bound vibrational levels and dissociative excitation of the B 1 Σ u + , C 1 Π u , E F 1 Σ g + , B ′ 1 Σ u + , G K 1 Σ g + , I 1 Π g , J 1 Δ g , D 1 Π u , H 1 Σ g + , b 3 Σ u + , c 3 Π u , a 3 Σ g + , e 3 Σ u + , d 3 Π u , h 3 Σ g + , g 3 Σ g + , i 3 Π g , and j 3 Δ g electronic states from all –14 bound vibrational levels of the ground electronic ($\text{X}$ $^1&#x3A3^+_g$) state. The data set consists of cross sections from threshold to 500 eV for over 5000 transitions, representing all possible electronic and vibrational transitions between the state and the –3 singlet and triplet states (where refers to the united-atoms-limit principle quantum number). The cross sections are presented in graphical form and provided as both numerical values and analytic fit functions in supplementary data files.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Trace Metal Uptake and Mercury Methylation by Sediments from a Stream in Tennessee

The formation and transport of methylmercury (MeHg), a neurotoxin, in aquatic environments is a global concern for human health as MeHg can bioaccumulate and biomagnify to high concentrations in aquatic food webs. MeHg is formed by conversion from inorganic mercury through microbial mediated methylation. Sulfate-reducing bacteria have been identified as the primary organisms responsible for MeHg production. Pure-culture studies suggest that low availability of cobalt and copper may inhibit mercury methylation, but whether such limitations occur in the environment is unclear. To explore the possible interaction between trace metal availability and mercury methylation, sediments from the East Fork Poplar Creek in Oak Ridge, Tennessee were sampled and then incubated in the presence and absence of added dissolved cobalt and copper. Three types of data are provided in this package. The first reports the uptake of dissolved cobalt and copper by these stream sediments on short time scales (24 hours) in the form of final dissolved and adsorbed concentrations. The second data component consists of a time series of dissolved concentrations and pH values for stream sediments incubated with artificial stream water containing different addition levels of dissolved cobalt or copper. The dissolved concentrations reported include total iron, manganese, sulfur, phosphorus, nickel, zinc and cobalt, dissolved concentrations of sulfate and orthophosphate, and the amount of cobalt or copper adsorbed by the sediment. The third data component reports data at 0 and 72 hours of incubation time for stream sediments to which cobalt was added. These data include concentrations of methylmercury with isotope labeling to enable determination of methylation and demethylation rates as well as dissolved concentrations of sulfate, phosphate, chloride, iron, cobalt, and organic carbon. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower-case mu to indicate the micro prefix on units. A Table of Contents file (Data_package_TableofContents.txt) provides an index for the data contained in the individual files.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Voltammetric Measurement of Rates and Energetics for Surface Methoxylation of Si(100) in Methanol with Dissolved Electron Acceptors Using Si Ultramicroelectrodes

The steady-state voltammetric responses of n-type Si(100) semiconductor ultramicroelectrodes (SUMEs) immersed in air- and water-free methanolic electrolytes have been measured. The response characteristics of these SUMEs in the absence of illumination were modeled and understood through a framework that describes the distribution of the applied potential across the semiconductor/electrolyte contact using four discrete regions: the semiconductor space charge, surface, Helmholtz, and diffuse layers. The latter region was described by the full Gouy–Chapman model. This framework afforded insight on how relevant parameters such as the semiconductor band edge potentials, the reorganization energies for charge transfer, the standard potential of redox species in solution, the density and energy of surface state populations, and the presence of an insulating (tunneling) layer individually and collectively dictate the observable current–potential responses. With this information, the methoxylation of Si surfaces was evaluated by analysis of the change in voltammetric responses during the course of prolonged immersion in methanol. Here, the electrochemical data were consistent with a surface methoxylation mechanism that depended on the standard potential of redox species dissolved in solution. Estimates of the enthalpies of adsorption as well as the potential-dependent rate constant for surface methoxylation were obtained. Collectively, these measurements supported the contention that the rates of Si surface reactions can be systematically tuned by exposure to dissolved outer-sphere electron acceptors. Moreover, the data represent the quantitative utility of voltammetry with SUMEs for the measurement of semiconductor/liquid contacts.

14 SOLAR ENERGY↗

DOE OSTI2022

Multi-Variable Parametric Analysis of Prototype Building Energy Performance Using Current and Future Weather Scenarios For Data-Driven Market Transformation Support

This project aimed to develop a public building simulation data set that may be used to inform building code development and guidelines for building innovation. The data set consists of several common building types and many representative locations across the United States. A parametric design of building properties was developed to create a range of building energy models that represent common building design decisions with a particular focus on fenestration options. The US Department of Energy prototype building energy models were altered according to a parametric building design and simulated using both current weather data and future weather estimates derived from global climate models. The resulting data set allows for pertinent exploration of building design parameters, including fenestration, within different environments across the United States in the broader context of climate change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗