Theoretical/Computational Chemist @EmoryChem Assistant Professor
Atlanta, GA
- Tweets 433
- Following 1,537
- Followers 2,674
- Likes 1,664
Pinned Tweet
🤩🤩🤩
Issue 9 is here!
Our front cover this week features Fang Liu et al 🤩
'Chatbot-assisted quantum chemistry for explicitly solvated molecules'
🔗 doi.org/10.1039/D4SC08677E
#ChemSciCovers
@FangLiu_Emory @EmoryChem @emorycollege
1
23
3,587
Coming up Monday afternoon at ACS Fall 2026: machine learning potentials and data-driven models for molecular and materials simulations.
📅 Monday, August 24
⏰ 2:00–6:00 PM
📍 McCormick Place Convention Center, Room W180
#ACSFall2026
1
378
Join us at #ACSFall2026 in Chicago for “Machine Learning Meets Electronic Structure Theory”—three days at the frontier of quantum chemistry, materials and AI.
📅 Aug 24–26
📍 McCormick Place, Room W180
👥 Organized by Yeongsu Cho & Fang Liu
#MachineLearning #QuantumChemistry
2
2
15
1,153
Full program (access with ACS login):
(1) Aug 24 AM: lnkd.in/ekkRZcb5
(2) Aug 24 PM: lnkd.in/excVU43x
(3) Aug 25 AM: lnkd.in/eJn9EUtS
(4) Aug 25 PM: lnkd.in/eEwt26eg
(5) Aug 26 AM: lnkd.in/etZjCb69
(6) Aug 26 PM: lnkd.in/eXiect2H
71
We gratefully acknowledge the support of APL Computational Physics (@AIP_Publishing) and Electronic Structure (@IOPPublishing). Thank you for helping bring our community together at #ACSFall2026!
86
Now in @JCIM_JCTC, Fangning & Patrick benchmark 5 different tuning schemes for long-range-separated functionals in the polarizable continuum model using experimental 937 solution-phase absorption spectra — offering data-driven recommendations. pubs.acs.org/doi/10.1021/acs…
1
13
888
Barista mode activated !🍹 Crafted 10 drinks (iced coffee☕️, matcha latte🍵, and mango sago🥭)for the group + first-year grad students exploring research groups. Research talk never tasted so good!
12
680
Now published in JCE we built a preconfigured JupyterHub image for #ChemistryEducation — Instructors can now easily build a coding website for their classes: browser-based coding + automatic grading and feedback via nbgrader.
🔗 doi.org/10.1021/acs.jchemed.…
1
11
464
Now in Digital Discovery, @_Xu_Chen_ introduces the ACES-GNN framework, designed to simultaneously improve predictive accuracy and interpretability by integrating explanation supervision for activity cliffs (ACs) into GNN training. pubs.rsc.org/en/content/arti…
1
22
1,182
(Reposting due to wrong link posted in previous post) Our recent work about utilizing domain adversarial neural network trained on simulated data to analyze experimental spectra is now featured in the cover image of Newton, volume 1, issue 3! cell.com/newton/fulltext/S29…
1
2
4
540
Instead, we trained the model based on simulated spectra and apply the model to detect phase transition in experimental spectra. However, this won’t directly work, because of the difference in experimental and simulated spectra. To tackle the problem, we used domain adaptation,
1
1
293
Prof. Mingda Li @mit_nse just published a preview in Newton to introduce our recent paper in Newton (doi.org/10.1016/j.newton.202…) about using domain adversarial neural networks (DANN) to detect phase transition in superconducting material.
cell.com/newton/fulltext/S29…
2
14
908
Huge congratulations to @ArielGGale on successfully defending her PhD dissertation! So proud of this milestone and excited for what’s next!
24
1,512
Now published in Newton, Xu developed a domain-adversarial framework that fuses abundant simulation data with scarce experimental data to detect thermodynamic phase transitions from photoemission spectroscopy. doi.org/10.1016/j.newton.202…
1
10
725
Data scarcity often limits ML applications in experimental science. We tackle this with a domain-adversarial framework that fuses abundant simulation data with scarce experimental data to detect thermodynamic phase transitions from photoemission spectroscopy. 🧵1/6
1
2
13
1,717
The work is published today on Newton: linkinghub.elsevier.com/retr… 🧵5/6
1
339
A detailed story about this work is also available on Emory News: click.inspire.emory.edu/?qs=… 🧵6/6
1
325