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基于探针结构预测和机器学习发现低导热氧化物

Discovery of a Low Thermal Conductivity Oxide Guided by Probe Structure Prediction and Machine Learning.

作者信息

Collins Christopher M, Daniels Luke M, Gibson Quinn, Gaultois Michael W, Moran Michael, Feetham Richard, Pitcher Michael J, Dyer Matthew S, Delacotte Charlene, Zanella Marco, Murray Claire A, Glodan Gyorgyi, Pérez Olivier, Pelloquin Denis, Manning Troy D, Alaria Jonathan, Darling George R, Claridge John B, Rosseinsky Matthew J

机构信息

Department of Chemistry, University of Liverpool, Crown Street, Liverpool, L69 7ZD, UK.

Leverhulme Research Centre for Functional Materials Design, The Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.

出版信息

Angew Chem Int Ed Engl. 2021 Jul 19;60(30):16457-16465. doi: 10.1002/anie.202102073. Epub 2021 Jun 17.

Abstract

We report the aperiodic titanate Ba Y Ti O with a room-temperature thermal conductivity that equals the lowest reported for an oxide. The structure is characterised by discontinuous occupancy modulation of each of the sites and can be considered as a quasicrystal. The resulting localisation of lattice vibrations suppresses phonon transport of heat. This new lead material for low-thermal-conductivity oxides is metastable and located within a quaternary phase field that has been previously explored. Its isolation thus requires a precisely defined synthetic protocol. The necessary narrowing of the search space for experimental investigation was achieved by evaluation of titanate crystal chemistry, prediction of unexplored structural motifs that would favour synthetically accessible new compositions, and assessment of their properties with machine-learning models.

摘要

我们报道了一种非周期性钛酸盐BaYTiO,其室温热导率等于已报道的氧化物中的最低值。该结构的特征是每个位点的占有率调制不连续,可被视为一种准晶体。由此产生的晶格振动局域化抑制了热的声子传输。这种新型的低导热率氧化物铅材料是亚稳态的,位于先前已探索的四元相区内。因此,其分离需要精确确定的合成方案。通过评估钛酸盐晶体化学、预测有利于合成可及新组成的未探索结构基序以及用机器学习模型评估其性质,实现了实验研究搜索空间的必要缩小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9567/8362121/b5ea2de82398/ANIE-60-16457-g001.jpg

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