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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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NASA NTRS2001

Guidelines for the Selection of Near-Earth Thermal Environment Parameters for Spacecraft Design

Thermal analysis and design of Earth orbiting systems requires specification of three environmental thermal parameters: the direct solar irradiance, Earth's local albedo, and outgoing longwave radiance (OLR). In the early 1990s data sets from the Earth Radiation Budget Experiment were analyzed on behalf of the Space Station Program to provide an accurate description of these parameters as a function of averaging time along the orbital path. This information, documented in SSP 30425 and, in more generic form in NASA/TM-4527, enabled the specification of the proper thermal parameters for systems of various thermal response time constants. However, working with the engineering community and SSP-30425 and TM-4527 products over a number of years revealed difficulties in interpretation and application of this material. For this reason it was decided to develop this guidelines document to help resolve these issues of practical application. In the process, the data were extensively reprocessed and a new computer code, the Simple Thermal Environment Model (STEM) was developed to simplify the process of selecting the parameters for input into extreme hot and cold thermal analyses and design specifications. In the process, greatly improved values for the cold case OLR values for high inclination orbits were derived. Thermal parameters for satellites in low, medium, and high inclination low-Earth orbit and with various system thermal time constraints are recommended for analysis of extreme hot and cold conditions. Practical information as to the interpretation and application of the information and an introduction to the STEM are included. Complete documentation for STEM is found in the user's manual, in preparation.

Anderson, B. J.↗
DOE OSTI2023

QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data and scripts associated with a manuscript investigating dissolved organic matter and microbial community linkages across seven globally distributed rivers

This data package is associated with the publication “Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers” submitted to Science of the Total Environment. This data package includes the data necessary to replicate the analyses presented within the manuscript to investigate dissolved organic matter (DOM) development across broad spatial distances and within divergent biomes. Specifically, we included the Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data, geochemistry data, annotated metagenomic data, and results from ecological null modeling analyses in this data package. Additionally, we included the scripts necessary to generate the figures from the manuscript. Complete metagenomic data associated with this data package can be found at the National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. This dataset consists of (1) four folders; (2) a file-level metadata (flmd) file; (3) a data dictionary (dd) file; (4) a factor sheet describing samples; and (5) a readme. The FTICR Data folder contains (1) the processed Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data; (2) a transformation-weighted characteristics dendrogram generated from the FTICR-MS data; and (3) the script used to generate all FTICR-MS related figures. The Geochemical Data folder contains (1) the single geochemistry data file and (2) the R script responsible for generating associated figures. The Metagenomic Data folder contains (1) annotation information across different levels; (2) carbohydrate active enzyme (CAZyme) information from the dbCAN database (Yin et al., 2012); (3) phylogenetic tree data (FASTAs, alignments, and tree file); and (4) the scripts necessary to analyze all of these data and generate figures. The Null Modeling Data folder contains (1) data generated during null modeling for each river and all rivers combined and (2) the R scripts necessary to process the data. All files are .csv, .pdf, .tsv, .tre, .faa, .afa, .tree, or .R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling

This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mineralogy of floodplain sediments from Meanders C, O, and Z in the East River Watershed, CO, USA

This dataset includes bulk X-ray diffraction data from floodplain sediments collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of biogeochemical cycling and other river corridor processes on riverine export of solutes. Sediment cores were collected from Meander C, Meander O, and Meander Z in July 2016 to September 2017 to depths of approximately 40-95 cm. Sample metadata including locations, depths, and sample dates are included in a csv file ("sample_list_and_locations.csv"). The file "diffraction_data.csv" contains raw diffraction data, and mineral quantification is in the file "mineral_abundance.csv". This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Facilitating Implementation of High-Volume Fly Ash Use in Pre-cast Concrete Construction to Increase Beneficial Utilization

The main goal of this project was to increase the beneficial use of fly ash as a supplementary cementitious material for precast concrete applications. A major focus was to develop balanced concrete mix design strategies which collectively satisfy the follow objectives: 1) increase fly ash beneficial use by at least 15% in the precast concrete industry, 2) maintain or exceed stringent structural property requirements (e.g., compressive strength at initial prestress, modulus of rupture, etc.), 3) exhibit little or no additional cost relative to conventional mixtures, and 4) mitigate detrimental environmental consequences inadvertently caused by increased beneficial use. Outcomes from this project include recommendations for design guidelines and code provisions for sustainable concrete mix designs, facilitating diversion and harvesting of large quantities of fly ash from landfills or impoundments, and multiple frameworks for incorporating discarded fly ash materials (i.e., landfilled or ponded fly ash after separating the impurities) in concrete construction.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

SPRUCE Photosynthesis and Respiration of Picea mariana and Larix laricina in SPRUCE Experimental Plots, 2019

This dataset contains physiological, morphological, and chemical measurements of the two dominant coniferous species, Picea mariana and Larix laricina, in August 2019 (2019-08-20 to 2019-08-22) at the SPRUCE (Spruce and Peatland Responses under Changing Environments) experiment site in the Marcell Experimental Forest in northern Minnesota, USA. These observations help to assess the effects of whole ecosystem scale warming and elevated carbon dioxide (CO2) concentrations on peatland ecosystems. Measurements include light-saturated photosynthesis and foliar dark respiration measurements under standard conditions and growth conditions involving varying temperatures and atmospheric CO2 concentrations, as well as leaf morphology measurements (leaf mass per unit leaf area) and nitrogen content based on mass and leaf area. Net photosynthesis and dark respiration measurements were taken using portable photosynthesis systems (LI6400XT, LI6800, LI-COR Biosciences, USA). This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE Root Production Assessed with Manual Minirhizotrons Resolved to Plant Functional Type, 2015-2021

This dataset contains raw root length and diameter for individual roots and estimated root population production measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements started at the beginning of whole ecosystem warming manipulations in 2015 through 2021 (2015-05-26 to 2021-09-01). Root morphology and estimated production were quantified throughout the peat profile with manual minirhizotrons deployed within SPRUCE plots. Images were processed using commercial software to quantify the length and diameter of individual roots. Roots were visually assigned to a plant functional type (PFT) of either (ericaceous) shrub, herb (sedges and Maianthemum trifolium), or tree (Larix laricina, Picea mariana) based on expert opinion. The biomass of individual roots was estimated using PFT-specific allometric equations (Iversen et al., 2018). Production per day was estimated as the length of new roots produced between imaging sessions, divided by the number of days between imaging sessions. These values were placed on a m2 aboveground area basis and scaled to a standard depth of 1m (roots are not evenly distributed with depth, do not interpret value as being on a m3 basis). Maximum and average (weighted by production length) depth of each PFT were also estimated within each minirhizotron tube. Annual production was interpolated as the average of four methods to scale these data (see Weber et al, 2026). Standing crop of roots was estimated for each tube as the maximum visible amount (both length and mass) of roots of that PFT for that year. These data expand the ability of researchers to accurately estimate the belowground dynamics of peatland vegetation, as well as the role that fine roots may play in impacting the fluxes of carbon within peatlands. This dataset contains three data files in comma-separate values (*.csv) format. This dataset contains one data file in comma-separate values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring: Supporting Data

This dataset was used to assess the performance of a compression algorithm for Soil Deformation and Temperature Monitoring data. The development of this technology is presented in the article named time division duplex (TDD) "TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring" and published in Springer's Journal on Signal Processing Systems. [Time Division Duplex (TDD); Long Range (LoRa)]Field experiment data includes: 1) soil temperature measurements, 2) snow temperature data, 3) soil temperature and deformation data. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 15 minutes. Lists included for probe, datalogger, and packaging components. The two temperature data sets were acquired at a site at the East River Watershed, Colorado, while the temperature/deformation data were collected at the Teller Road (mile 27) site near Nome, Alaska. The package includes 8 comma-separated files (.csv) and one .pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2021

Leaf gas exchange measurements on Carex aquatilis Wahlenb. following a single season warming treatment. Data were collected in 2021 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2017

Leaf gas exchange measurements on Petasites frigidus (L.) Fr. following a single season warming treatment. Data were collected in 2017 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5-25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017-2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Hydrogen-oxygen catalytic ignition and thruster investigation. Volume 1: Catalytic ignition and low pressure thruster evaluations

An experimental and analytical program was conducted to evaluate catalytic igniter operational limits, igniter scaling criteria, and delivered performance of cooled, flightweight gaseous hydrogen-oxygen reaction control thrusters. Specific goals were to: (1) establish operating life and environmental effects for both Shell 405-ABSG and Engelhard MFSA catalysts, (2) provide generalized igniter design guidelines for high response without flashback, and (3) to determine overall performance of thrusters at chamber pressures of 15 and 300 psia (103 and 2068 kN/sq m) and thrust levels of 30 and 1500 lbf, respectively. The experimental results have demonstrated the feasibility of reliable, high response catalytic ignition and the effectiveness of ducted chamber cooling for a high performance flightweight thruster. This volume presents the results of the catalytic igniter and low pressure thruster evaluations are presented.

Johnson, R. J.↗
NASA NTRS1993

The interaction of high voltage systems with the environments of the Moon and Mars

High voltage systems designed for use on the lunar and Martian surfaces or in orbit will interact with environmental components such as electrically charged dust, low pressure atmospheres, ionospheric plasmas and neutrals, and chemically reactive species. As the Space Exploration Initiative (SEI) advances from the realm of feasibility study to that of conceptual design, guidelines will be required to ensure that these effects are properly accounted for. A first step in providing such guidelines is the prioritization of interactions for each of the space or surface environments that will be encountered. For those issues that are identified as high priority, the state of environmental knowledge, emphasizing essential data, must be determined. This report describes possible means of obtaining such information, including ground tests, modeling and analysis, and flight experiments. The development of computational tools which will enable engineers to simulate and thereby quantify the interactions will be especially considered. Our analysis is drawn from various study and workshop activities undertaken within the last two years.

Hillard, G. Barry↗
DOE OSTI2022

Design and Implementation of Smart Buildings: A Review of Current Research Trend

The building sector is one of the largest contributors to the world’s total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people’s daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields.

renewable system integration↗
DOE OSTI2023

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external temperature reference source (ETRS) for temperature compensation. The combination of an IRT and an ETRS forms a screening thermograph (ST). We investigated the effects of viewing angle (θ, 0–75°), ETRS set temperature (T ETRS , 30–40 °C), ambient temperature (T atm , 18–32 °C), relative humidity (RH, 15–80%), and working distance (d, 0.4–2.8 m). We discovered that STs exhibited higher accuracy compared to IRTs alone. Across the tested ranges of T atm and RH, both IRTs exhibited absolute measurement errors of less than 0.97 °C, while both STs maintained absolute measurement errors of less than 0.12 °C. The optimal T ETRS for EBT detection was 36–37 °C. When θ was below 30°, the two STs underestimated calibration source (CS) temperature (T CS ) of less than 0.05 °C. The computer simulations showed absolute temperature differences of up to 0.28 °C and 0.04 °C between estimated and theoretical temperatures for IRTs and STs, respectively, considering d of 0.2–3.0 m, T atm of 15–35 °C, and RH of 5–95%. The results highlight the importance of precise calibration and environmental control for reliable temperature readings and suggest proper ranges for these factors, aiming to enhance current standard documents and best practice guidelines. These insights enhance our understanding of IRT performance and their sensitivity to various factors, thereby facilitating the development of best practices for accurate EBT measurement.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

An expert-driven literature review of “negative” chemicals for developmental neurotoxicity (DNT) in vitro assay evaluation

To date, approximately 200 chemicals have been tested in US Environmental Protection Agency (EPA) or Organization for Economic Co-operation and Development (OECD) developmental neurotoxicity (DNT) guideline studies, leaving thousands of chemicals without traditional animal information on DNT hazard potential. To address this data gap, a battery of in vitro DNT new approach methodologies (NAMs) has been proposed. Evaluation of the performance of this battery will increase the confidence in its use to determine DNT chemical hazards. One approach to evaluate DNT NAM performance is to use a set of chemicals to evaluate sensitivity and specificity. Since a list of chemicals with potential evidence of in vivo DNT has been established, this study aims to develop a curated list of “negative” chemicals for inclusion in a “DNT NAM evaluation set”. A workflow, including a literature search followed by an expert-driven literature review, was used to systematically screen 39 chemicals for lack of DNT effect. Expert panel members evaluated the scientific robustness of relevant studies to inform chemical categorizations. Following review, the panel discussed each chemical and made categorical determinations of “Favorable”, “Not Favorable”, or “Indeterminate” reflecting acceptance, lack of suitability, or uncertainty given specific limitations and considerations, respectively. Further, the panel determined that 10, 22, and 7 chemicals met the criteria for “Favorable”, “Not Favorable”, and “Indeterminate”, for use as negatives in a DNT NAM evaluation set. Ultimately, this approach not only supports DNT NAM performance evaluation but also highlights challenges in identifying large numbers of negative DNT chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A molecular view of peptoid-induced acceleration of calcite growth

The extensive deposits of calcium carbonate (CaCO 3 ) generated by marine organisms constitute the largest and oldest carbon dioxide (CO 2 ) reservoir. These organisms utilize macromolecules like peptides and proteins to facilitate the nucleation and growth of carbonate minerals, serving as an effective method for CO 2 sequestration. However, the precise mechanisms behind this process remain elusive. In this study, we report the use of sequence-defined peptoids, a class of peptidomimetics, to achieve the accelerated calcite step growth kinetics with the molecular level mechanistic understanding. By designing peptoids with hydrophilic and hydrophobic blocks, we systematically investigated the acceleration in step growth rate of calcite crystals using in situ atomic force microscopy (AFM), varying peptoid sequences and concentrations, CaCO 3 supersaturations, and the ratio of Ca 2+ / HCO 3 − . Mechanistic studies using NMR, three-dimensional fast force mapping (3D FFM), and isothermal titration calorimetry (ITC) were conducted to reveal the interactions of peptoids with Ca 2+ and HCO 3 − ions in solution, as well as the effect of peptoids on solvation and energetics of calcite crystal surface. Our results indicate the multiple roles of peptoid in facilitating HCO 3 − deprotonation, Ca 2+ desolvation, and the disruption of interfacial hydration layers of the calcite surface, which collectively contribute to a peptoid-induced acceleration of calcite growth. These findings provide guidelines for future design of sequence-specific biomimetic polymers as crystallization promoters, offering potential applications in environmental remediation (such as CO 2 sequestration), biomedical engineering, and energy storage where fast crystallization is preferred.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗