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We provide refined experimental property data across thermo-physicochemical, thermodynamic, transport, and pharmaceutical properties, which serves as an important benchmark to cross-verify predictions and improve robustness. Below is the list of available refined experimental data View Refined Experimental Data List V

The experimental data was collected to validate the reliability of our QSQN technology. Due to frequent measuring errors in the raw experimental data, we implemented a systematic refinement process involving basic analysis, statistical filtering, and similarity analysis. For more details, see our refinement example using the normal boiling point as a case study.

We provide thermo-physicochemical, thermodynamic, transport, and pharmaceutical property data for over 1 billion compounds as listed below. View Property Data List V

The property data listed above is produced using our proprietary QSQN and QN technology, backed by 41 patents, and has been validated to demonstrate proven reliability. The compounds, composed of C, H, N, O, S, F, Cl, Br, I, Si, P, and/or As, span a wide range of structures and compositions.

We offer comprehensive molecular structures and identifiers for over 1 billion compounds as listed below. View List

The optimized 3D structures are produced using a high-quality quantum chemical computation process. We perform conformer analysis to select the lowest energy structure, followed by geometry optimization with the DFT-B3LYP functional and 6-31G basis set. All optimized structures are verified to ensure the absence of imaginary frequencies.

We provide comprehensive spectroscopic data for over 4 million compounds, with each and every compound featuring key information for molecular identification and analysis. The following spectroscopic data is available:

• Infrared (IR) Spectroscopy:

  Detailed vibrational frequencies and intensities essential for identifying functional groups and molecular structures. IR spectroscopy data is available in JDX (JCAMP Chemical Spectroscopic Data Exchange Format) as well, ensuring easy integration into various analysis tools and workflows.

• Nuclear Magnetic Resonance (NMR) Spectroscopy:

  ¹H, ¹³C, ¹⁵N, ¹⁷O, and ³²S NMR data, providing insights into molecular environments, bonding interactions, and chemical connectivity.

• Vibrational Circular Dichroism (VCD) Spectroscopy:

  Provides chiral-sensitive data that enhances molecular structure determination, particularly useful for studying the stereochemistry of organic compounds.

These datasets are derived from high-quality quantum chemical computations as outlined in our proprietary QSQN technology.

We provide an extensive collection of quantum chemical data for over 4 million compounds, critical for developing AI models in areas like molecular design, drug discovery, and material science. The data listed below represents only a subset of the complete data (Download full data list).

Quantum Chemical Computation Data

• Vibrational Frequency Data:

  Provides key insights into molecular vibrations, essential for understanding molecular dynamics.

• Total Energy:

  Critical for determining the stability and potential reactivity of a molecule.

• Molecular Orbital Energies (HOMO, LUMO):

  Important indicators of a molecule's ability to donate or accept electrons, useful for predicting chemical reactivity.

• Mulliken Charges, Cartesian Coordinates, and Force Constants:

  Important computational outputs used for electronic structure analysis and geometric optimization.

Quantum Chemical Descriptors (3-Dimensional Molecular Descriptors)

• HOMO-LUMO Energy Gap:

  A widely used metric for predicting molecular stability and chemical reactivity.

• Nucleophilic and Electrophilic Reactivity Indices:

  Critical for understanding how a molecule interacts with other species in nucleophilic (electron-donating) and electrophilic (electron-accepting) reactions.

• Atomic Charges and Molecular Dipole:

  Key indicators of charge distribution within the molecule, influencing how it interacts in chemical and biological environments.

Electrostatic Descriptors (3-Dimensional Molecular Descriptors)

Electrostatic properties are crucial for understanding a molecule’s behavior in different environments, such as solvent interactions:

• Max and Min Partial Charges:

  Provide insight into the distribution of charge across a molecule, helping predict areas of electron density.

• Polarity Parameter:

  Measures the overall polarity of a molecule, which is important for predicting solubility and molecular interactions.

• Surface Area Metrics:

  Includes Total Molecular Surface Area, Partial Positive and Negative Surface Areas, and Charge-Weighted Surface Areas—essential for understanding molecular interactions like binding affinity.

Quantum Chemical Computation Result File

• FCHK File:

  A file that contains comprehensive quantum chemical computation results, providing a complete dataset for each molecule that can be further analyzed or integrated into AI models.

Molecular descriptors mathematically represent the properties of molecules and play a crucial role in improving the performance of AI models, enabling AI systems to more accurately understand and predict the structural, chemical, and geometrical characteristics of molecules in fields such as chemical research, material science, and drug design

We offer over 3,000 2-dimensional molecular descriptors for more than 1 billion compounds, organized into 20 distinct categories, providing detailed insights into molecular behavior for AI-driven research. Below are the descriptor categories and the corresponding number of available descriptors. View Category List V

Each descriptor category provides a unique perspective on the molecular structure and properties. For a detailed list of descriptors within each category, a separate file is available for download (Download full data list).

We understand that each customer’s data needs are unique. We therefore offer the flexibility to choose only the specific data you need from our 30+ billion datasets, ensuring a fully customized solution tailored to your exact requirements.

Simply contact us at contact@cc-dps.com and let us know the type of data and compounds you need, the quantity of data points or compounds, and your preferred format for receiving the data (e.g., as a file, integrated database, API, or other specific formats). Once we receive your inquiry, we will provide you with a tailored quote based on your specific requirements.

Feel free to reach out to us anytime—we’re here to help you get the data you need for your AI development.