The 2016 Bradley-Mason prize for open chemistry.

Peter Murray-Rust and I are delighted to announce that the 2016 award of the Bradley-Mason prize for open chemistry goes to Jan Szopinski (UG) and Clyde Fare (PG).

Jan’s open chemistry derives from a final year project looking at why atom charges derived from quantum chemical calculation of the electronic density represent chemical information well, but the electrostatic potential (ESP) generated from these charges is very poor and conversely charges derived from the computed electrostatic potential are incommensurate with chemical information (such as the electronegativity of atoms). He has developed a Python program called ‘repESP’ in which ‘compromise’ charges are generated which attempt to reconcile the physical world-view (fitting the ESP) with chemical insight provided by NPA (Natural Population Analysis). Jan was the main driver to making his code open source, “opening his supervisor’s eyes” to the various flavours of open source licences. To ensure that all subsequent improvements to the program remain available to anyone, the source code has been released under a ‘copyleft’ licence (GPL v3) and is maintained by Jan on GitHub, where Jan looks forward to helping new users and collaborating with contributors.

Clyde has made various contributions to opensource chemistry over the period of his PhD, with the focus mainly on utilities to improve quantum chemical research and the enhancement of a popular machine learning library with a method that has been successful in chemometrics, creation of an opensource channel for teaching chemists programming and data analysis and creation of a tool to help encourage open sourcing software development. Cclib is the most popular library for parsing quantum chemical data from output files and Clyde has contributed patches for the Atomic simulation environment which enables control of quantum chemical codes from a unified python interface. He was responsible for the construction of a computational chemistry electronic notebook published to github and which is now under active development by others as well. This aims to encapsulate computation chemical research projects, both for the sake of reproducibility and for the sake of organising and keeping track of quantum chemical research. Alongside this platform he created an enhanced Gaussian calculator for the Atomic Simulation Environment that enables automatic construction of ONIOM input files, also now under active development. He also made contributions to scikit learn, the most popular python machine learning framework, implementing a kernel for Kernel Ridge Regression that has become the most successful kernel for regression over molecular properties. He was part of the team that won the 2014 sustainable software conference prize for creation of the opensource healthchecker software as part of Sustain. He has argued for opensource as a platform for teaching resources and created the Imperial Chemistry github user account, which is now run by the department. Materials for the Imperial Chemistry Data Analysis and Programming workshops implemented as Python Notebooks are now available through this account and continue under active development.

Criteria for the award will include judging the submission on its immediate accessibility via public web sites, what is visible and re-usable in this way and of evidence of either community formation/engagement or re-use of materials by people other than the proposer.

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