This repository has properties for different groups of material. The main idea is to provide accesible properties for comparison.

Materials Project is an open database of computed materials properties aiming to accelerate materials science research. The resources in this OpenData dataset contain the raw, parsed, and build data products.

NIST has accumulated a valuable and comprehensive collection of thermal conductivity data from measurements performed with a 200-mm square guarded-hot-plate apparatus. The guarded-hot-plate test method is arguably the most accurate and popular method for determination of thermal transmission properties of flat, homogeneous specimens under steady state conditions. Several organizations, including ASTM and ISO, have standardized the method. Version 1.0 of the database includes data for over 2000 measurements, covering several categories of materials including concrete, fiberboard, plastics, thermal insulation, and rubber. The data cover a temperature range corresponding to most building applications; however, the majority of the measurements were conducted at 24° C (75° F). Web version 1.0

This database contains cryogenic material property data.

This is a companion repository for a paper published in Scientific Data with the title and authors given above, whose abstract is below:There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

A complete copy of the Materials Project database as of 10/18/2018. Mp_all files contain structure data for each material while mp_nostruct does not.Available as Monty Encoder encoded JSON and as CSV. Recommended access method for these particular files is with the matminer Python package using the datasets module. Access to the current Materials Project is recommended through their API (good), pymatgen (better), or matminer (best).Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.Dataset discussed in:A. Jain*, S.P. Ong*, G. Hautier, W. Chen, W.D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K.A. Persson (*=equal contributions) The Materials Project: A materials genome approach to accelerating materials innovation APL Materials, 2013, 1(1), 011002.Dataset sourced from:https://materialsproject.org/Citations for specific material properties available here:https://materialsproject.org/citing

The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-throughput experiments at the National Renewable Energy Laboratory (NREL).

The document contains the comprehensive ‘one-stop’ material properties database developed by the GEOLAB consortium for the typical soils and constitutive models used in the GEOLAB facilities. The said database was developed to support the use and re-use of the quality experimental data from the GEOLAB Transnational Access projects.

An in-house developed finite-difference time-domain (FDTD) code has been used to simulate certain patterned defects as found in the semiconductor industry. Intrinsic to FDTD is the establishment of a simulation domain, a 3-D matrix of some arbitrary size (X, Y, Z) comprised of smaller cells (in our case, cubic with side length x), with each cell indexed to a material (including the vacuum) to form the geometry. Although the specific text files used as inputs to the in-house FDTD engine are provided, such files are likely incompatible with external FDTD solutions for the replication of our results. Therefore, entire 3-D matrices for our simulations have been reduced to single-vector, readable ASCII data files indexing the geometry and materials of the system, accompanied by text files that supply the optical constants used in the simulation as well as cross-sectional images that allow verification by others of their reconstruction of the 3-D matrix from the supplied 1-D ASCII data files.

V2DB: A two-dimensional (2D) materials database, created by the Autonomous Energy Materials Discovery [AMD] research group, consists of 316,505 likely to be stable materials with AI predicted key properties (energy, electronic, and magnetic).

Yamdb (Yet Another Materials Database/YAMl materials DataBase) is a Python library providing thermophysical properties of liquid metals and molten salts in an easily accessible manner. Mathematical relations describing material properties - usually determined by experiment - are taken from the literature and implemented in Python. The coefficients of these equations are stored separately in YAML files.

The database includes mechanical data for structure-properties relationships and mechanical modeling of elastic impact protection foams from a variety of imaging (micro-computed tomography, digital image correlation) and force-sensing instruments (dynamic mechanical analysis, universal test system) under a wide range of experimental conditions and modes. The data repository includes directories for: dynamic mechanical analysis raw data, results, and analysis tools; intermediate rate (servo-hydraulic UTS based) raw data including 2D digital image correlation (DIC) images, results, and analysis tools; quasi-static rate (electro-mechanical UTS based) raw data including 2D digital image correlation (DIC), results, and analysis tools; micro-computed tomography data including raw volume images, filtered images, binarized images, other results, and analysis tools; and, instrumented drop tower data including backface force, high speed video, and results and analyzed data, Fourier Transform Infrared (FTIR) spectra, and differential scanning calorimetry (DSC) data.For more information see the readme and data documentation in each respective directory. A paper describing data collection, analysis, and database documentation is available here: https://doi.org/10.1038/s41597-023-02092-4. A repository containing example usage code is available at: https://github.com/materials-data-facility/foam_db. File formats for data include .txt, .xls, .tri, .tprc, .rcp, .py, .m, .csv, .mat, .vtk, .spa, .exp, .stl, and .tif.

The vastness of materials space, particularly that which is concerned with metal–organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties.

In this work, MOF bulk properties are evaluated and compared using several force fields on several well-studied MOFs, including IRMOF-1 (MOF-5), IRMOF-10, HKUST-1, and UiO-66. It is found that, surprisingly, UFF and DREIDING provide good values for the bulk modulus and linear thermal expansion coefficients for these materials, excluding those that they are not parametrized for. Force fields developed specifically for MOFs including UFF4MOF, BTW-FF, and the DWES force field are also found to provide accurate values for these materials’ properties. While we find that each force field offers a moderately good picture of these properties, noticeable deviations can be observed when looking at properties sensitive to framework vibrational modes. This observation is more pronounced upon the introduction of framework charges.

Dataset accompanying the publication 'M. Cermak, N. Perez, and M. Bahrami, 'Material properties and structure of natural graphite sheet', Science and Technology of Advanced Materials, 2020'.

The dataset contains the raw data related to the measurements of material properties, implementation of data processing in Matlab and Microsoft Excel, and microscope images of the material structure.

The Network for Evaluating Structural Components (NESC) coordinated extensive materials testing and fracture analyses performed by a group of twenty European organizations. The NESC-IV project addressed the transferability of fracture toughness data from laboratory specimens to applications that assess the integrity of reactor pressure vessels subjected to upset and normal loading transients. The coordinated experimental and analytical program drew from major elements of the biaxial features testing program conducted by the Heavy Section Steel Technology Program at the Oak Ridge National Laboratory. In this context, the JRC performed impact and tensile tests in the temperature range -90 to 80ºC on type A533B ferritic steel.

MADB is a bibliographic database on physico-chemical properties of selected Minor Actinide compounds and alloys. The materials and properties are selected based on their importance in the advanced nuclear fuel cycle options. This list is updated up to 2008.

The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the material properties are registered on a three-dimensional grid with a spacing of 25 meters between nodes. The material properties are listed an Excel file. Figures show planar slices in three sets: horizontal slices in a planes normal to the vertical Z axis (Z normal), vertical slices in planes perpendicular to the dominant strike of the fault system (X normal), and vertical slices in planes parallel to the dominant strike of the fault system (Y normal). The results agree on the following points. The material is unconsolidated and/or fractured, especially in the shallow layers. The structural trends follow the fault system in strike and dip. The geodetic measurements favor the hypothesis of thermal contraction. Temporal changes in pressure, subsidence rate, and seismic amplitude are associated with changes in pumping rates during the four stages of the deployment in 2016. The modeled hydraulic conductivity is high in fault damage zones. All the observations are consistent with the conceptual model: highly permeable conduits along faults channel fluids from shallow aquifers to the deep geothermal reservoir tapped by the production wells.

This compilation of outgassing data of materials intended for spacecraft use were obtained at the Goddard Space Flight Center (GSFC), utilizing equipment developed at Stanford Research Institue (SRI) under contract to the Jet Propulsion Laboratory (JPL). SRI personnel developed an apparatus for determining the mass loss in vacuum and for collecting the outgassed products. Their report (Reference 1), which contained data from June 1964 to August 1967, served well as a foundation for selecting spacecraft materials with low outgassing properties. The apparatus was also constructed at GSFC and, based on the SRI data and GSFC data, a GSFC report (Reference 2) was published. That report included data for those materials meeting two criteria: a maximum total mass loss (TML) of 1.0 percent and maximum collected volatile condensable material (CVCM) of 0.10 percent. After a series of tests and verification of procedures, an American Society for Testing and Materials (ASTM) Standard Test Method was developed, based upon this apparatus. The method, 'Total Mass Loss (TML) and Collected Volatile Condensable Materials (CVCM) from Outgassing in a Vacuum Environment,' is identified as E 595-77/84/90. The data developed through the years have been reported in References 3, 4, 5, 6, 7, 8, and 9 as a means of assisting in selecting materials for space flight use.

This dataset consists of

1) Excel sheets with material properties for a) a collection of historic building materials and b) insulation materials suited for internal insulation. Material properties were collected from all RIBuild partner countries. The main purpose was to locate data set not included in the DELPHIN database that contained the needed data for DELPHIN simulations.

2) Excel sheets with material properties for specific historic building materials used in Italy and Switzerland. As these materials were supposed to be included in hygrothermal simulations with DELPHIN performed in RIBuild, a full material characterization was required as described in RIBuild deliverable D2.1 and in the DELPHIN specifications. Material characterization was performed at RTU.

Requirements concerning input need for DELPHIN simulations are described in RIBuild deliverable D2.1.

Overview of data files to be found in 'RIBuild data WP2 Mat Prop' as part of this dataset.