Minggao Feng

How is your wasabi？

Accelerating discovery in natural science laboratories with AI and robotics: Perspectives and challenges Experts from academia and industry offer perspectives on the future direction of autonomous science and knowledge discovery.

www.science.org/doi/10.1126/...

Just about ready for our first workshop on mol-cspy: our source software for crystal structure prediction
gitlab.com/mol-cspy/mol...
A massive thank you to the research team in getting material together for this.
#compchemsky #chemsky

Image of speaker at conference in front of projected slide showing computer simulation results on molecular crystals.

Thank you to the organisers of the "from molecules to materials" meeting in Bologna for inviting me to give a keynote talk.
Among other things, I spoke about @aichemyhub.bsky.social-funded large-scale crystal structure prediction and transferable ML potentials: doi.org/10.1039/D4FD...
#compchemsky

User interface of the CrystalNets web app

Architecture of the CrystalNets web app, showing client-side and server-side tasks.

“CrystalNets: a web app for topology determination of crystalline structures” — our latest preprint on @chemrxiv.org doi.org/10.26434/che...

An Adapted Similarity Kernel and Generalised Convex Hull for Molecular Crystal Structure Prediction We adapted an existing approach to identifying stabilisable crystal structures from prediction sets - the Generalised Convex Hull (GCH) - to improve its application to molecular crystal structures. Th...

I'm very pleased to say my first preprint, with @graemeday.bsky.social and @micheleceriotti.bsky.social is now online!

This is the main work of my PhD, adapting a similarity kernel to be more suited for exploring molecular CSP landscapes

#compchemsky #chemsky #compchem

doi.org/10.26434/che...

#chemistswhocook

First time I tried making steamed buns, it seems quite successful😄

Graph showing the connections between crystal structures as a function of increasing energy. Each connection is represented as a node connecting lines from initial starting structures.

If you're at the 25th European crystallographic meeting in Poznan, I'll recommend MS43 – "Simulating and predicting structure" at 14:00 on Wed.

Pedro Juan Royo from our group will be presenting on our methods for mapping the interconnectivity of predicted crystal structures.
#CompChemSky #ChemSky

They happened to be looking for the next 007

The robot chemists helping scientists in a university chemistry lab Instead of scientists in white coats, it is robots that move between the benches in a University of Liverpool cheminstry laboratory.

@apnews.com apnews.com/video/the-ro...

SDLs raise some new safety questions - here we introduce Chemist Eye, a distributed safety monitoring system designed to enhance situational awareness in SDLs. 👏 for Francisco Munguia-Galeano, who tested it for accident recognition by lying repeatedly on the lab floor. www.arxiv.org/pdf/2508.05148

Congrats!

‘CrystalGPT’ set to enhance how chemists design crystals in silico Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data

Understanding and predicting crystals’ properties is a key element of materials design, and a new transformer-based model can do it quickly and accurately. #ChemSky

Excited to share that our latest work on organic crystal transformer (MCRT) has been featured in Chemistry World! 🎉 This model accelerates organic materials discovery by predicting properties with unprecedented accuracy. Check out the article and our paper for more details!

Check out this new @chemistryworld.com story from Kirsty McRoberts based on recent work by @graemeday.bsky.social, Xenophon Evangelopoulos, and @aicooper.bsky.social published in Chemical Science!

Read the original article for free here:

doi.org/10.1039/D5SC...

#ChemSky #CompChemSky

‘CrystalGPT’ set to enhance how chemists design crystals in silico Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data

@chemistryworld.com article on our recent @chemicalscience.rsc.org paper. #compchemsly #chemsky

'CrystalGPT’ set to enhance how chemists design crystals in silico
www.chemistryworld.com/news/crystal...

‘CrystalGPT’ set to enhance how chemists design crystals in silico Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data

Nice work @graemeday.bsky.social and @aicooper.bsky.social - you made it easy for me to comment on! Cool stuff 😎
www.chemistryworld.com/news/crystal...
@chemistryworld.com

Ah chili sauce, looks actually 👍. I love making this too, but Chinese style.🌶️

What was the final pruduct?

Just out, "Selective CO2 Adsorption in Ultrahydrophobic Molecular Pyrene Frameworks by Computational Design" pubs.acs.org/doi/10.1021/.... Sam Harding was the student who led this. MeTBAP-α is one of the most hydrophobic porous solids reported, and this came out of a priori computational design 🚫💧

Now published in @chemicalscience.rsc.org and highlighted as a #ChemSciPicks. Great work by @ffmmgg.bsky.social. Collab with @aicooper.bsky.social

A Universal Foundation Model for Transfer Learning in Molecular Crystals

#compchemsky #chemsky
@unisouthampton.bsky.social @liverpooluni.bsky.social

This week's #ChemSciPicks comes from @graemeday.bsky.social (University of Southampton), @ffmmgg.bsky.social‬, Chengxi Zhao‬, Xenphon Evangelopoulos, and @aicooper.bsky.social‬ (University of Liverpool).

Read the full paper here: doi.org/10.1039/D5SC...

#ChemSky

Have a look through our most popular 2024 papers in Chemical Science in Physical, Computational & Theoretical Chem. #chemsky #compchemsky

and it's all Open Access.

A promotional slide for the Chemical Science themed collection on most popular work in the area of physical, theoretical and computational chemistry from 2024

Our #ChemSciMostPopular collection for work in Physical, Computational & Theoretical Chemistry is now available online!

The collection, like all papers published in the journal, is entirely free to read:
pubs.rsc.org/en/jour...

Check out some of these 🔥HOT🔥 articles:

Automatic Discovery and Optimal Generation of Amorphous High-Entropy Electrocatalysts Amorphous materials are ubiquitous in nature and are widely used for many industrial applications, including catalysis, energy storage, and environmental science. However, significant challenges remain in designing and optimizing amorphous high-entropy materials because of the lack of well-defined structure–activity relationships. Here, we use synthesis systems to discover and optimize amorphous high-entropy oxyhydroxide electrocatalysts within the entire design space for the alkaline oxygen evolution reaction. Amorphous high-entropy electrocatalysts are derived from ultrathin 2D coordination polymers composed of six nonprecious metal elements that were selected from top 16 candidate metal elements involved in oxygen evolution reaction (OER)-related literature searching, which can then be transformed in situ into amorphous oxyhydroxides. Leveraging machine learning (ML) techniques, we establish a composition–activity relationship and thereby identify an optimal composition group by traversing the entire design space (over 1,900,000 compositions). Our ML-model is validated by using 100 compositions in the high-activity region and 588 compositions in the low-activity region, which results in excellent recall values of nearly 100%. The predicted optimal amorphous high-entropy electrocatalyst demonstrates an ultralow overpotential of 159 mV at a current density of 10 mA cm–2 for the alkaline OER in a 1 M KOH while exhibiting ultralong durability 10,218 h under a practical current density of 1 A cm–2 in a 6 M KOH. Our work provides a general strategy for the automatic discovery and optimization of amorphous high-entropy oxyhydroxide electrocatalysts and could significantly impact the development of other amorphous high-entropy materials.

New paper from Jun Jiang and colleagues - "Automatic Discovery and Optimal Generation of Amorphous High-
Entropy Electrocatalysts" using a mobile robotic chemist @jacs.acspublications.org #robots #chemsky pubs.acs.org/doi/10.1021/...

Brilliantly Red: The Structure of Carmine Carmine is a red pigment made from dried cochineal, a scale insect that has been a source of brilliant scarlet reds in clothing and art for more than two millennia, with records dating back to 700 BC....

Carmine is a red pigment used since antiquity to color textiles, in paintings by Rembrandt and Van Gogh, and today as a food coloring agent (E120).

Very excited that @esvenssongrape.bsky.social finally reveals the crystal structure of carmine by #3DED!

pubs.acs.org/doi/10.1021/...

💡Big ideas need big backing…
Something major is coming — our Large Funding Call is almost here, with up to £1M in grants up for grabs! 💰🚀

Think bold. Think transformative.
Details landing soon. Stay close. 👀

#FundingOpportunity #ResearchFunding #Innovation #BigIdeasBigImpact #AIchemyHub

There is a lot in this paper beyond just an updated set of MOF structures. For example, we introduce a new version of MOFid that should be more useful for ML and data analytics. Check it out.

🚨 Brand new postdoctoral researcher position in my group at Princeton! Please apply or share with anyone interested in computational materials science and being an electron whisperer! puwebp.princeton.edu/AcadHire/app....