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Electron density learning of non-covalent systems
Chemists continuously harvest the power of non-covalent interactions to control phenomena in both the micro- and macroscopic worlds. From the quantum chemical perspective, the... -
Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Co...
This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible... -
I’m alone but not lonely. U-shaped pattern of perceived loneliness during the...
In the past months, many countries have adopted varying degrees of lockdown restrictions to control the spread of the COVID-19 virus. According to the existing literature, some... -
Local kernel regression and neural network approaches to the conformational l...
The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of... -
Learning the energy curvature versus particle number in approximate density f...
The average energy curvature as a function of the particle number is a molecule-specific quantity, which measures the deviation of a given functional from the exact conditions... -
Simulating the ghost: quantum dynamics of the solvated electron
The nature of the bulk hydrated electron has been a challenge for both experiment and theory due to its short lifetime and high reactivity, and the need for a high-level of... -
Revised MD17 dataset
The original MD17 dataset (http://quantum-machine.org/datasets/#md-datasets) [Chemiela et al. Sci. Adv. 3(5), e1603015, 2017] contains numerical noise. Thus, any numbers... -
Learning the exciton properties of azo-dyes
The ab initio determination of the character and properties of electronic excited states (ES) is the cornerstone of modern theoretical photochemistry. Yet, traditional ES... -
Maximum volume simplex method for automatic selection and classification of a...
Fingerprint distances, which measure the similarity of atomic environments, are commonly calculated from atomic environment fingerprint vectors. In this work, we present the... -
Dataset of predicted daily nutrient concentrations for NO3-N and TP for 150 m...
The main component of this data publication is a dataset of predicted daily nutrient concentrations for NO3-N and TP for 150 monitoring stations along 60 German rivers (main... -
The rule of four: anomalous stoichiometries of inorganic compounds
Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle,... -
The rule of four: anomalous stoichiometries of inorganic compounds
Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle,... -
Data underpinning "Generalization Capabilities of Machine Learning-based PDM ...
"graph_data.xlsx" is an excel spreadsheet containing the graph data. There are two sheets, "Nonlinearities" which contains the data in Fig 2a, and "Dispersion" containing the... -
Date Estimation in the Wild Dataset
This dataset has no description
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3D µCT images of specimens of carbon fiber reinforced polyamide 6 plaque, fib...
This dataset includes 3D µCT images of nine different specimen of 10 mm \times 10 mm of a carbon fiber reinforced polyamide 6 plaque produced in the long fiber reinforced... -
Ball Screw Drive Surface Defect Dataset for Classification
The dataset contains of 21835 150x150 Pixel RGB images of the surface of Ball Screw Drives. 11075 of these images are images without surface defects whereas the rest shows... -
Dataset for the Segmentation of Industrial Burner Flames
The published dataset contains images and masks related to the research article with the title "Segmentation of Industrial Burner Flames: A Comparative Study from Traditional... -
Domain-Shift-Dataset of Defects on Metallic Surfaces (MSD-Shift)
The dataset maps two different surfaces (domains) from mechanical engineering (Surfaces of Ball Screw Drives (BSD); Surface of Metallic Semi-finished Products (SEV)). The... -
Evolution of Surface Defects on Ball Screw Drive Spindles for intelligent Pro...
The dataset shows the development of 82 surface defects (pits) over the operating time of Ball Screw Drives. The name of the images is structured as follows:...
