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 raw data of the experimental sample were determined.

During the course of this experimental study

Being relatively new to the field, electromechanical actuators in aerospace applications lack the knowledge base compared to ones accumulated for the other actuator types, especially when it comes to fault detection and characterization. Lack of health monitoring data from fielded systems and prohibitive costs of carrying out real flight tests push for the need of building system models and designing affordable but realistic experimental setups. This paper presents our approach to accomplish a comprehensive test environment equipped with fault injection and data collection capabilities. Efforts also include development of multiple models for EMA operations, both in nominal and fault conditions that can be used along with measurement data to generate effective diagnostic and prognostic estimates. A detailed description has been provided about how various failure modes are inserted in the test environment and corresponding data is collected to verify the physics based models under these failure modes that have been developed in parallel. A design of experiment study has been included to outline the details of experimental data collection. Furthermore, some ideas about how experimental results can be extended to real flight environments through actual flight tests and using real flight data have been presented. Finally, the roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators is discussed.*

While art is omnipresent in human history, the neural mechanisms of how we perceive, value and differentiate art has only begun to be explored. Functional magnetic resonance imaging (fMRI) studies suggested that art acts as secondary reward, involving brain activity in the ventral striatum and prefrontal cortices similar to primary rewards such as food. However, potential similarities or unique characteristics of art-related neuroscience (or neuroesthetics) remain elusive, also because of a lack of adequate experimental tools: the available collections of art stimuli often lack standard image definitions and normative ratings. Therefore, we here provide a large set of well-characterized, novel art images for use as visual stimuli in psychological and neuroimaging research. The stimuli were created using a deep learning algorithm that applied different styles of popular paintings (based on artists such as Klimt or Hundertwasser) on ordinary animal, plant and object images which were drawn from established visual stimuli databases. The novel stimuli represent mundane items with artistic properties with proposed reduced dimensionality and complexity compared to paintings. In total, 2,332 novel stimuli are available open access as “art.pics” database at https://osf.io/BTWNQ/ with standard image characteristics that are comparable to other common visual stimuli material in terms of size, variable color distribution, complexity, intensity and valence, measured by image software analysis and by ratings derived from a human experimental validation study [n = 1,296 (684f), age 30.2 ± 8.8 y.o.]. The experimental validation study further showed that the art.pics elicit a broad and significantly different variation in subjective value ratings (i.e., liking and wanting) as well as in recognizability, arousal and valence across different art styles and categories. Researchers are encouraged to study the perception, processing and valuation of art images based on the art.pics database which also enables real reward remuneration of the rated stimuli (as art prints) and a direct comparison to other rewards from e.g., food or money.Key Messages: We provide an open access, validated and large set of novel stimuli (n = 2,332) of standardized art images including normative rating data to be used for experimental research. Reward remuneration in experimental settings can be easily implemented for the art.pics by e.g., handing out the stimuli to the participants (as print on premium paper or in a digital format), as done in the presented validation task. Experimental validation showed that the art.pics’ images elicit a broad and significantly different variation in subjective value ratings (i.e., liking, wanting) across different art styles and categories, while size, color and complexity characteristics remained comparable to other visual stimuli databases.

The HIRENASD data produced by analyzing the experimental data is repeated on this website, for those who can not download the information in the zip format found on the primary Experimental Data page, or who wish to examine the plots of the data online.

A new, relational database to be used for disease gene discovery, gene annotation and reporting, and searching for genes for future studies in model organisms. It incorporates 5 layers of information about the genes residing in it- the expression information from a gene (as reported in Unigene), the cytological location of the gene (if available), the ortholog of each gene in the available species within the database, the divergence information between species for each gene, and functional information as reported by OMIM and the Enzyme Commission (EC) reference number of genes. Tables have also been created to help record polymorphism data and functional information about specific changes within or between species, such as measured by Granthams distance (1) or model organism studies.

This database is linked to the article entitled "Water clusters in interaction with corannulene in a rare gas matrix: structures, stability and IR spectra" by Leboucher et al. submitted to "Photochem" on March 1st 2022.

Theoretical results can be found in the following directories: - Geoms which contains the DFTB/FF optimized structures reported in Figures 2 to 4 of the manuscript (the last column of the files must not be taken into account) - IR_harm which contains the IR harmonic data for these structures (first column: wavenumbers in cm-1, second column: intensities in km/mol) - Spect_10K which contains the dynamics spectra as reported in Figures 5 to 7

Experimental results can be found in the directory Experimental, with spectra in two columns (first column: wavenumber in cm-1, second column: absorbance). Data have been corrected for atmospheric water vapor.

In the directory Gas-phase are reported the results of gas-phase calculations at the DFT (M062X/d95v(dip) and DFTB levels performed for benchmark purpose. - in DFT_opt are reported DFT optimized structures, similar to DFTB optimized structures - in IR-spect, harmonic DFT and DFTB spectra - the En_GP.pdf file reports energetic data for these systems.

This database summarizes 165 experimental test data on beam-to-column connections for composite special moment frames (C-SMFs).

river map

experimental data from the MFA algorithm

This resource contains the experimental data that was included in tecplot input files but in matlab files. dba1_cp has all the results is dimensioned (7,2) first dimension is 1-7 for each span station 2nd dimension is 1 for upper surface, 2 for lower surface. dba1_cp(ispan,isurf).x are the x/c locations at span station (ispan) and upper(isurf=1) or lower(isurf=2) dba1_cp(ispan,isurf).y are the eta locations at span station (ispan) and upper(isurf=1) or lower(isurf=2) dba1_cp(ispan,isurf).cp are the pressures at span station (ispan) and upper(isurf=1) or lower(isurf=2) Unsteady CP is dimensioned with 4 columns 1st column, real 2nd column, imaginary 3rd column, magnitude 4th column, phase, deg M,Re and other pertinent variables are included as variables and also included in casedata.M, etc

This dataset contains experimental data for aerodynamics and acoustics of configuration B1, which was defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise). The measurements were taken in the Low-Speed, Low-Turbulence Tunnel (LTT) at Delft University of Technology, using a Distributed Electric Propulsion (DEP) configuration model that consists of three propellers installed side-by-side on the leading edge of a wing.

We present the full database of the article "Explainable Supervised Machine Learning Model to Predict Solvation Free Energy".

This is the database used for a ML model, containing a variety of solvent-solute pairs with known experimental solvation free energy ΔGsolv values. Data entries were collected from two separate databases. The FreeSolv library, with 642 experimental aqueous ΔGsolv determinations and the Solv@TUM database with 5597 entries for non-aqueous solvents. Both databases were selected given their wide-scale of solute/solvents pairs, amassing 6239 experimental values across light and heavy-atom solutes with a diverse solvent structure and with small value uncertainties.

Experimental ΔGsolv values range from -14 to 4 kcal mol-1 and each solute/solvent pair is represented by their chemical family, SMILES string and InChlKey. We generated 213 chemical descriptors for every solvent and solute in each entry using RDKit software, version 2022.09.4, running on top of Python 3.9. Descriptors were calculated from the “MolFromSmiles” function in “RDKIT.Chem” as descriptors with non-numerical values were removed. The descriptors encode significant chemical information and are used to present physicochemical characteristics of compounds, building a relationship between structure and ΔGsolv.

Through Machine Learning regression algorithms, our models were able to make ΔGsolv predictions with high accuracy, based on the information encoded in each chemical feature.

This database contains the results of 146 experimental evacuation drills. Several configurations are proposed: from a single room to a multi-compartment configuration. For each test, a unique file contains all the evacuation times in seconds from the drill start when people go through the doorways. These raw data will be handled by future users to calibrate or validate their own evacuation models.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

This data set is a collection of data sets and model checkpoint in the iPXRDnet.

Model checkpoint file(model.zip):
hmof-130T_Hydrogen: Model of adsorption prediction for H2 in the hMOF-130T database obtained by training
hmof-130T_CarbonDioxide: Model of adsorption prediction for CO2 in the hMOF-130T database obtained by training
hmof-130T_Nitrogen: Model of adsorption prediction for N2 in the hMOF-130T database obtained by training
hmof-130T_Methane: Model of adsorption prediction for CH4 in the hMOF-130T database obtained by training
hmof-300T: Adsorption prediction model in the hMOF-300T database obtained by training
Gas_Se: Separation selectivity prediction model obtained by training
Gas_SD: Self-diffusion coefficients prediction model obtained by training
MOD: Bulk modulus and shear modulus prediction model obtained by training
exAPMOF-1bar-ALM+PXRD: Experimental adsorption at 1 bar model of Anion-pillared MOFs obtained by training with PXRD and material ligands
exAPMOF-1bar-ALM: Experimental adsorption at 1 bar model of Anion-pillared MOFs obtained by training with material ligands only
exAPMOF-1bar-PXRD: Experimental adsorption at 1 bar model of Anion-pillared MOFs obtained by training with PXRD only
exAPMOF-ISO:Experimental adsorption isotherm model of Anion-pillared MOFs obtained by training
exAPMOF-1bar-NOacvPXRD: Experimental adsorption at 1 bar model of Anion-pillared MOFs obtained by training with PXRD data before activation only
exAPMOF-1bar-acvPXRD: Experimental adsorption at 1 bar model of Anion-pillared MOFs obtained by training with PXRD data after activation only

Checkpoint file for model without co-learning strategy(model-No-co-learning.zip):
hmof-130T_Hydrogen: Model of adsorption prediction for H2 in the hMOF-130T database obtained by training
hmof-130T_CarbonDioxide: Model of adsorption prediction for CO2 in the hMOF-130T database obtained by training
hmof-130T_Nitrogen: Model of adsorption prediction for N2 in the hMOF-130T database obtained by training
hmof-130T_Methane: Model of adsorption prediction for CH4 in the hMOF-130T database obtained by training
hmof-130T-str: Structural characteristics prediction model in the hMOF-130T database obtained by training
hMOF-130T-GradCAM: Model for GradCAM in the hMOF-130T database obtained by training
hmof-300T: Adsorption prediction model in the hMOF-300T database obtained by training
hmof-300T-str: Structural characteristics prediction model in the hMOF-300T database obtained by training
Gas_Se: Separation selectivity prediction model obtained by training
Gas_SD: Self-diffusion coefficients prediction model obtained by training
MOD: Bulk modulus and shear modulus prediction model obtained by training

Data sets file (data.zip):
hmof-xrd+str+ad :PXRD and gas adsorption and structural feature of hmof-300T database
hMOF-130T_ad_list_mof :Gas adsorption data of hmof-130T database
hMOF-130T_GAS_DICT :Gas descriptors data of hmof-130T database
hMOF-130T_STR_DICT :Structural feature data of hmof-130T database
hMOF-130T_PXRD_DICT :PXRD data of hmof-130T database
MOD_data :Bulk modulus and shear modulus data of Moghadam's MOFs
MOD_PXRD_dict : PXRD data of Moghadam's MOFs
GAS_SD-data : self-diffusion coefficients data in CoREMOF database
SE-CO2,N2_data:Separation selectivity ,PXRD and structural feature of CO2/N2 selectivity database
Sa_sp:Data set partitioning results of CO2/N2 selectivity database
gas_dict : gas descriptors data used in the self-diffusion coefficients database
PXRD_DICT : PXRD data after activation of MOFs in Anion-pillared MOFs' experimental database
xrd_noacv : PXRD data before activation of MOFs in Anion-pillared MOFs' experimental database
Smiles_ads : Smiles data of gas in Anion-pillared MOFs' experimental database
all_exAPMOF-1bar : Anion-pillared MOFs' experimental adsorption data under 298K and 1 bar.
all_exAPMOF-1bar-NOacv : Experimental adsorption data for anion-pillared MOFs with PXRD before activation under 298K and 1 bar.
exAPMOF_DICT : Anion-pillared MOFs' Smiles data of MOFs' ligands and descriptors of metal centers in the experimental database
all_exAPMOF-iso : Key library of MOF and gas combinations in Anion-pillared MOFs' experimental isotherm database.
exAPMOF_ISOdata: Anion-pillared MOFs' experimental adsorption isotherm data under 298K.

New Data sets file (data_new.zip):

Files starting with ‘4gas_’: Files are named in the form of ‘4gas_Gas_Pressure’, recording the adsorption amounts of 20,000 randomly selected structures from the hMOF-130T database at different pressures at 298K.
all_adinfo_list_robustness: Gas adsorption data file used for study of model robustness .
hmof-130T_Xnm: PXRD data of structures in the hmof-130T database at different crystal sizes.
hMOF-130T_ad_list_mof: Corrected Gas adsorption data of hmof-130T database . There are problems with the data in the data.zip file.
X_PXRD,AD: Adsorption amount and PXRD data of ionic MOFs (iMOFs), zeolitic imidazolate frameworks (ZIF) and Uio-66 series from experimental literature. Among them, the Uio-66 series uses CO2 as the gas, and other files contain adsorption data of different gases.

In this dataset, the spectral data of the compounds synthesized and characterized are contained together with the experimental procedures.

This experimental database aimed to study the behavior of the air-water two-phase flow through thin orifice plates in a horizontal orientation. Two orifices with different area contraction ratios were tested. The database contains the raw pressure and dual impedance probe data in a fully instrumented test section. The test grid encompasses single- and two-phase flow. The superficial velocities of liquid varied from 0.20 m/s to 0.70 m/s, and gas varied from 0 m/s to 0.80 m/s.

This database was established to oversee documents issued in support of fishery research activities including experimental fishing permits (EFP), letters of acknowledgement (LOA), temporary possession permits (TPP), exempted educational activity authorizations (EEAA), and scientific research permits (SRP) . Specifically, the primary objectives are: 1. Oversee research document applications; 2....