Search Results - "CSD Python API"

Temperature validation using the CSD Python API

Authors: Amy A. Sarjeant Seth B. Wiggin Dean Johnston

Source: Acta Crystallographica Section A Foundations and Advances. 74:a398-a398

Subject Terms: 01 natural sciences, 0104 chemical sciences

Access URL: http://journals.iucr.org/a/issues/2018/a1/00/a56947/a56947.pdf
http://journals.iucr.org/a/issues/2018/a1/00/a56947/a56947.pdf
https://journals.iucr.org/a/issues/2018/a1/00/a56947/a56947.pdf

Using the CSD Python API for interactive analytics and data mining of the Cambridge Structural Database

Authors: Paul C. Sanschagrin

Source: Acta Crystallographica Section A Foundations and Advances. 73:a67-a67

Subject Terms: 02 engineering and technology, 0210 nano-technology, 01 natural sciences, 0104 chemical sciences

Access URL: http://journals.iucr.org/a/issues/2017/a1/00/a54716/a54716.pdf
https://journals.iucr.org/a/issues/2017/a1/00/a54716/a54716.pdf

Harnessing the power of the Cambridge Structural Database in your own way: the CSD Python API

Authors: Seth B. Wiggin Andrew G. P. Maloney Paul C. Sanschagrin

Source: Acta Crystallographica Section A Foundations and Advances. 72:s165-s165

Subject Terms: 01 natural sciences, 0104 chemical sciences

Access URL: http://journals.iucr.org/a/issues/2016/a1/00/a54246/a54246.pdf
https://journals.iucr.org/a/issues/2016/a1/00/a54246/a54246.pdf

What has scripting ever done for us? The CSD Python application programming interface (API).

Authors: Sykes, Richard A. Johnson, Natalie T. Kingsbury, Christopher J. et al.

Source: Journal of Applied Crystallography. Aug2024, Vol. 57 Issue 4, p1235-1250. 16p.

Subject Terms: *DRUG discovery, *DATABASES, *DRUG development, *PYTHON programming language, *SERVER farms (Computer network management)

A to Z of polymorphs related by proton transfer.

Authors: Woods-Ryan, Amy Doherty, Cheryl L. Cruz-Cabeza, Aurora J.

Source: CrystEngComm; 5/21/2023, Vol. 25 Issue 19, p2845-2858, 14p

Subject Terms: PHARMACY databases, PROTONS, ZWITTERIONS, DATABASES, CRYSTAL structure, DATA mining, INTRAMOLECULAR proton transfer reactions, MASS transfer

Automated oxidation‐state assignment for metal sites in coordination complexes in the Cambridge Structural Database.

Authors: Reeves, Matthew G. Wood, Peter A. Parsons, Simon

Source: Acta Crystallographica Section B: Structural Science, Crystal Engineering & Materials; Dec2019, Vol. 75 Issue 6, p1096-1105, 10p

Subject Terms: OXIDATION states, DATABASES, METALS, COORDINATE covalent bond, METALS testing

Interpretation of the crystal structures of transition metal compounds and complexes

Authors: Reeves, Matthew George Parsons, Simon Brechin, Euan

Contributors: Reeves, Matthew George Parsons, Simon Brechin, Euan

Subject Terms: Cambridge Structural Database, transition metal structures, automated computational methods, calculation of intermolecular interaction energies

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.828927

A survey of thermal expansion coefficients for organic molecular crystals in the Cambridge Structural Database.

Authors: Bond, Andrew D.

Source: Acta Crystallographica Section B: Structural Science, Crystal Engineering & Materials; Jun2021, Vol. 77 Issue 3, p357-364, 8p

Subject Terms: MOLECULAR crystals, THERMAL expansion, GAUSSIAN distribution, STANDARD deviations, UNIT cell, LOW temperatures, MISSING data (Statistics), SKEWNESS (Probability theory)

Organic solvates in the Cambridge Structural Database.

Authors: Werner, Jen E. Swift, Jennifer A.

Source: CrystEngComm; 2/21/2021, Vol. 23 Issue 7, p1555-1565, 11p

Subject Terms: DATABASES, APPLICATION program interfaces, PYTHON programming language, TIME measurements, SOLVENTS

Virtual screening of n-type organic semiconductors using exhaustive band structure calculations.

Authors: Okada, Tomoharu Fujiwara, Wataru Katagiri, Hiroshi et al.

Source: Science and Technology of Advanced Materials: Methods; Dec2025, Vol. 5 Issue 1, p1-7, 7p

Graph neural networks for predicting metal-ligand coordination of transition metal complexes.

Authors: Toney, Jacob W. St. Michel, Roland G. Garrison, Aaron G. et al.

Source: Proceedings of the National Academy of Sciences of the United States of America; 10/14/2025, Vol. 122 Issue 41, p1-12, 59p

Subject Terms: GRAPH neural networks, TRANSITION metal complexes, DATABASES, MOLECULAR models, VIRTUAL high-throughput screening (Drug development), METAL complexes, DENSITY functional theory

Predicting mechanical properties of crystalline materials through topological analysis.

Authors: Bryant, M. J. Maloney, A. G. P. Sykes, R. A.

Source: CrystEngComm; 5/21/2018, Vol. 20 Issue 19, p2698-2704, 7p

Subject Terms: MECHANICAL behavior of materials, CRYSTAL structure, HYDROGEN bonding

A survey of thermal expansion coefficients for organic molecular crystals in the Cambridge Structural Database.

Authors: Bond, Andrew D

Source: essn: 2052-5206; nlmid: 101609037

Index Terms: Cambridge Structural Database, Thermal Expansion, Molecular Crystals, Python Api, Article

URL: https://www.repository.cam.ac.uk/handle/1810/325482

Structure of (E)-4-amino-5-{[(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)imino]methyl}-1-methyl-2-phenyl-2,3-dihydro-1H-pyrazol-3-one: aerial oxidation of 4-aminoantipyrine in dimethylformamide.

Authors: Kumaravel, R. Stoeckli-Evans, Helen Subashini, A. et al.

Source: Acta Crystallographica Section E: Crystallographic Communications; May2025, Vol. 81 Issue 5, p438-443, 12p

Subject Terms: HYDROGEN bonding, CRYSTAL structure, DIMETHYLFORMAMIDE, DIMERS, PYRAZOLES

Hotspots API: A Python Package for the Detection of Small Molecule Binding Hotspots and Application to Structure-Based Drug Design.

Authors: Curran, Peter R Radoux, Chris J Smilova, Mihaela D et al.

Index Terms: Databases, Factual, Drug Design, Molecular Docking Simulation, Proteins, Software, Article

URL: https://www.repository.cam.ac.uk/handle/1810/304045

Predictive crystallography at scale: mapping, validating, and learning from 1000 crystal energy landscapes.

Authors: Taylor, Christopher R. Butler, Patrick W. V. Day, Graeme M.

Source: Faraday Discussions; 2025, Issue 256, p434-458, 25p

Comprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classifications.

Authors: Liu, Yutong Dong, Yawen Wu, Hua

Source: Journal of Materials Chemistry A; 1/28/2025, Vol. 13 Issue 4, p2403-2440, 38p

MrPIXEL: automated execution of Pixel calculations via the Mercury interface.

Authors: Reeves, Matthew G. Wood, Peter A. Parsons, Simon

Source: Journal of Applied Crystallography. Aug2020, Vol. 53 Issue 4, p1154-1162. 9p.

Subject Terms: *PIXELS, *INTERMOLECULAR interactions, *MERCURY (Element), *NUCLEAR density, *ELECTRON density

The interplay between hydrogen bonds and stacking/T-type interactions in molecular cocrystals.

Authors: Cruz-Cabeza, Aurora J. Spackman, Peter R. Hall, Amy V.

Source: Communications Chemistry; 12/2/2024, Vol. 7 Issue 1, p1-9, 9p

Subject Terms: HYDROGEN bonding interactions, STACKING interactions, CHEMICAL bonds, HYDROGEN bonding, MOLECULAR interactions

Statistical analysis of interatomic transfer integrals for exploring high-mobility organic semiconductors.

Authors: Ozawa, Koki Okada, Tomoharu Matsui, Hiroyuki

Source: Science & Technology of Advanced Materials; Dec2024, Vol. 25 Issue 1, p1-6, 6p

Subject Terms: MOLECULAR orbitals, DENSITY functional theory, CONTENT analysis, DATABASES, THIOUREA, ORGANIC semiconductors