Jiaxing Qu

UIUC PhD candidate| Computational material science | Thermoelectrics, Material Design

[Jiaxing Qu @JiaxingQu]

Our framework enables:
1. recommendations of highly relevant candidates for a query material.
2. exploration of under-studied space for potential thermoelectrics.
3/3.

[Jiaxing Qu @JiaxingQu]

Really excited to present our new work for material discovery: we leveraged language representations to design a framework that can recommend, rank, and explore functional materials: https://t.co/OMImyjQrjx

Joint work with @RichardYuxuan
#materialsscience #MachineLearning
1/3

[Jiaxing Qu @JiaxingQu]

Contextual knowledge encoded in language representations renders information about material properties and structures.

Example: thermoelectrics potential.
2/3

[Prashun Gorai @prashungorai]

Computational Design of Thermoelectric Alloys Through Optimization of Transport and Dopability. Accepted in @MaterHoriz. We lay the groundwork for a computational framework to optimize transport, and doping. @JiaxingQu at the helm! #compchem #alloy
https://t.co/ANo8x57t6U

[Jain Research Papers @jainpapers]

AMSET is a new theoretical method + code to calculate electronic properties of materials from first principles. Mobility, Seebeck, electronic thermal conductivity (w/lifetimes) at ~1/500th the computing cost of DFPT+Wannier.

@alexganose et al., Nat Comm
https://t.co/lR5u9ANOjB

[Jiaxing Qu @JiaxingQu]

Highlight: Band-engineering strategies on new n-type dopable Zintls!

[Prashun Gorai @prashungorai]

In our new @ChemMater paper led by @JiaxingQu, we report the discovery and band engineering of new Zintl phases A2CdP2 (A = Sr, Ba, Eu). Excellent collab with Svilen Bobev's team @UDelaware. Preprint on @ChemRxiv. #compchem @ACSPublications

https://t.co/5wUbLfbLSH

[Jiaxing Qu @JiaxingQu]

My first paper in PhD published on Journal of Material Chemistry A, with @prashungorai 😆

[Prashun Gorai @prashungorai]

Now accepted in @JMaterChem A. This is the first of many exciting results from @JiaxingQu's ongoing work on discovery and doping of Zintl phases. Congratulations, @JiaxingQu! #compchem @RoySocChem

https://t.co/lpa1Ya5lMb

[ChemRxiv @ChemRxiv]

A Combined DFT/Machine Learning Framework for Materials Discovery: Application to Spinels and Assessment of Search Completeness and Efficiency by Joshua A. Schiller & co-workers

https://t.co/uvL5jYtPZW

[Jain Research Papers @jainpapers]

"Matbench" collects 12 problems for testing new machine learning algorithms to predict inorganic structure/composition -> property relationships. Data suggests conventional ML good for small data, graph NNs better for large data.

Dunn et al, npj Comp Mat
https://t.co/AGyK6Y8l9j

[Snyder Lab @SnyderGroupNU]

Just out in the latest edition of @J_A_C_S!

@JamesMale27 and collaborators at @AIST_EN get into the details to explain why excess Na doping makes such good p-type PbTe #thermoelectrics, even without complicated band engineering or microstructure.

https://t.co/12zfvGHV3U

[Jiaxing Qu @JiaxingQu]

Excited to get first paper! Really appreciate your guidance on this work @prashungorai

[Prashun Gorai @prashungorai]

Happy to share my student @JiaxingQu's work on discovery of new n-type Zintl phases. Small steps towards realizing doping by design. #compchem

This is @JiaxingQu's first first-author paper - always special as a grad student.

Preprint now on @ChemRxiv: https://t.co/JujrAfuoGn

[Prashun Gorai @prashungorai]

This week we had @alexganose from @jainpapers introduce our team to matminer and automatminer for #machinelearning in materials science. Here's to our continued collaboration in #thermoelectrics!

[Jiaxing Qu @JiaxingQu]

@prashungorai Oh feel so hungry when look at this before sleep..

[Prashun Gorai @prashungorai]

Virtual Conference on Thermoelectrics #VCT2020. The response so far has been very positive!

By popular demand, we have extended the deadline for nominations to May 15, 2020 (May 22 for Asia).

https://t.co/dmYj0ZKggP