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Issue 10, 2021

A data-driven perspective on the colours of metal–organic frameworks

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Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a material based on its structure is challenging. In this work, we leverage subjective and categorical human assignments of colours to build a model that can predict the colour of compounds on a continuous scale. In the process of developing the model, we also uncover inadequacies in current reporting mechanisms. For example, we show that the majority of colour assignments are subject to perceptive spread that would not comply with common printing standards. To remedy this, we suggest and implement an alternative way of reporting colour—and chemical data in general. All data is captured in an objective, and standardised, form in an electronic lab notebook and subsequently automatically exported to a repository in open formats, from where it can be interactively explored by other researchers. We envision this to be key for a data-driven approach to chemical research.

Graphical abstract: A data-driven perspective on the colours of metal–organic frameworks

Supplementary files

Article information

24 Sep 2020
19 Dec 2020
First published
28 Dec 2020

This article is Open Access
All publication charges for this article have been paid for by the Royal Society of Chemistry

Chem. Sci., 2021,12, 3587-3598
Article type
Edge Article

A data-driven perspective on the colours of metal–organic frameworks

K. M. Jablonka, S. M. Moosavi, M. Asgari, C. Ireland, L. Patiny and B. Smit, Chem. Sci., 2021, 12, 3587 DOI: 10.1039/D0SC05337F

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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