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A High-Throughput Computational Search for New Transparent Conducting Oxides

Final Report Summary - HTFORTCOS (A High-Throughput Computational Search for New Transparent Conducting Oxides)

Transparent conducting oxides (TCO) show the rare combination of high electronic conductivity (10-3 to 10-4 Ohm.cm) and transparency in the visible range. TCO materials are critical in many industrial applications. Their importance in energy related applications (e.g. in low-emissivity windows and thin-film photovoltaics) make them of special interest for “green technologies”. On the longer term, the development of new TCOs could also enable entirely new technologies such as transparent electronics.
While there is a great need for finding new TCOs, the purely experimental search can be very time consuming as the chemical space to explore is very large and, one would have to synthesize and characterize each possible new materials candidate. Fortunately, researcher have nowadays access to a very powerful tool called ab initio computations. The ab initio techniques rely on the basic laws of physics to compute properties of materials (sometimes even before they have even been synthesized). An emerging approach is to use these ab initio techniques on a very large scale to perform so-called high-throughput computations. The idea is very simple yet powerful. By computing properties for thousands of different materials we can right away select the most promising ones and guide experiments towards them. Luckily, many of the properties of importance for TCOs can be nowadays computationally assessed (e.g. transparency, carrier mobilities and concentrations). This project aims at performing the first high-throughput computational search for new TCOs.
There are two kinds of TCOs: the n-type (with electrons as carriers) and the p-type (with the absence of electrons, or holes, as carriers). While the n-type TCOs are largely commercialized and show good performances the few known p-type TCOs show very poor quality. Unfortunately, the lack of a good p-type TCO impedes the development of many critical future technologies (e.g. transparent electronics or better solar cells). Our high-throughput infrastructure has already identified several novel potential p-type TCOs that had never been considered as TCO before. From a database of more than 4,000 known oxides only a handful satisfied the criteria to be a good p-type TCO. This illustrates how powerful high-throughput computational can be in solving the “needle in a haystack” problem of new materials discovery. This approach saves an enormous amount of time. Experimentalists can now use our results to focus on those promising chemistries identified through computing. In fact, preliminary experimental results on a novel p-type TCO identified through our approach : Ba2BiTaO6 have already been obtained. Our work goes even further. Not only have we identified the most promising oxides but the generated data has been used to discover the design rules to make very high conductivity p-type TCOs. For instance, materials containing a certain type of chemical element (tin 2+) are especially prone to form very good p-type TCOs. Those new chemical recipe will certainly give a new impulse to the quest for high performance p-type TCOs.
Our high-throughput infrastructure has also been used to study if any novel n-type TCO could be found. There, we found that the ones already commercialized (ZnO, In2O3, …) are already optimal in terms of effective mass. However, we identified a few interesting new n-type TCOs that could be of interest for certain niche applications. We also found through data mining the chemistry leading to the highest mobility n-type TCO.

Last but not least, this work developped a series of tools and frameworks to perform automatic computations of properties of interest for TCOs (band gaps, effective masses,…) using a series of ab initio techniques (density functional theory but also GW). This is of interest to many applications beyond TCO including solar absorber in photovoltaics and thermoelectric materials. We are actively currently pursuing the search for novel thermoelectric materials using high-throughput computing.