The CSD in Electronics Research

This blog is based on the work by Seyedmojtaba Seyedraoufi and co-workers, who searched the Cambridge Structural Database (CSD) to identify new potential proton-transfer ferroelectric materials and then predicted their coercive fields. 

Seyedmojtaba Seyedraoufi is a PhD student in computational material science and informatics from the Material Theory Group at the Norwegian University of Life Sciences. He recently presented the webinar “The CSD in Electronics Research. Predicting Coercive Fields in Organic Proton-Transfer Ferroelectrics” at the CCDC, which you can watch here on demand. His approach integrates database mining, machine learning, and quantum mechanical calculations, primarily at the DFT/vdW-DF level. Read the full article (the data and images on the blog are based on a revised version of the work).

Introduction

Ferroelectric materials are characterised by a spontaneous electric polarization that can be reversed in response to an external electric field (a coercive electric field). Owing to their interesting properties, these materials have a wide range of applications in industry: examples of materials in which they are used are capacitors, non-linear optics, ferroelectric RAM for computers and RFID cards.

Ferroelectrics can be inorganic or organic compounds: while the first require high-temperature processing and often contain toxic heavy elements, organic molecular ferroelectrics typically require low-temperature fabrication processes, do not contain heavy elements and can be made into flexible devices. 

Organic proton-transfer ferroelectrics (OPTFes) are a sub-group of organic molecular ferroelectrics that exhibit low coercive fields and fast ferroelectric switching. They include tautomeric materials and acid-base salts. In these materials, the polarization reversal is attributed to the proton-transfer along the hydrogen bond between one molecule and the next in the crystal lattice. 

In this work, the scientists systematically screened the CSD and identified eight potential OPTFes which had been deposited in the CSD but had not previously been investigated for ferroelectric properties. The team then calculated the spontaneous polarization and proton-transfer barriers for these compounds using density functional theory. 

Method

Reported in Figure 1 is the workflow that the team used to search the CSD. Starting with the over 1.2 million crystal structures present in the database when the work was carried out, the scientists incorporated only those with polar space groups (a requirement for ferroelectricity) and organic non-polymeric structures with less than 1000 atoms, in the screening. Further filters were then applied to consider only the structures with 3D coordinates, no disorder and an R-factor ≤ 0.075, reducing the dataset to 68,767 crystal structures. The filters were implemented using the CSD Python API. 

The next step was to apply a filter to exclude the compounds that did not exhibit a pseudo inversion centre (pseudosymmetry) when hydrogen atoms were removed. Pseudosymmetry refers to the concept where a structure can be viewed as a higher symmetry structure that has undergone minor distortions. This is particularly important for OPTFes because it is known that protons are typically responsible for breaking the symmetry in these materials. The next filter was then used to identify structures where the position of the transferrable hydrogen atoms resulted in breaking of inversion symmetry (Figure 1b), resulting in a dataset containing 2771 remaining structures. 

Finally, the remaining structures were inspected for clear proton-transfer pathways, resulting in 34 candidate compounds (Figure 1c). Of these, 22 were previously identified OPTFes and 8 were highlighted as possible new OPTFes. 

Reported in Figure 2 are the eight new potential OPTFes derived from this screening. Two of them are neutral tautomers, while six are ionic. Notably, the latter are salts, which may benefit from elevated melting points compared to typical OPTFes. This method may open the way for exciting new possibilities for tuneable properties based on ionic materials.

After identifying candidate structures, spontaneous polarizations and proton-transfer barriers were calculated, the critical parameters for ferroelectricity. Density functional theory (DFT) methods were used to calculate these properties. 

Conclusions

In this work, scientists reported the workflow used to screen the CSD for new OPTFes candidates. On top of 22 compounds already reported in the literature, the team also identified eight new potential OPTFes. In contrast to the previously reported tautomeric structures, six of these OPTFes candidates are salts, giving rise to the possibility of designing and tuning higher operational temperature devices.  

These promising results provide inspiration for new routes to OPTFes, and highlight the value of mining the vast amount of curated crystal structure data in the CSD for the discovery of new functional materials. 

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