Shunda Chen
@shunda-chen.bsky.social
A scientist exploring the fearful symmetry and amazing ordering on a small blue planet full of life, chaos, diversity, and entropy. Let there be light.
Here is the link to the paper titled "Identification of short-range ordering motifs in semiconductors": www.science.org/doi/10.1126/...
September 26, 2025 at 6:24 AM
Here is the link to the paper titled "Identification of short-range ordering motifs in semiconductors": www.science.org/doi/10.1126/...
A new paper published in Science: Short-range order in semiconductors has been directly confirmed, offering a new way to engineer electronic properties for advanced microelectronics & quantum devices. www.science.org/doi/10.1126/... @science.org @berkeleylab.lbl.gov @gwu1821.bsky.social #EFRC
Identification of short-range ordering motifs in semiconductors
Chemical short-range ordering is expected to be a key factor for tuning the electronic structure of semiconductors. However, experimental evidence of short-range ordering is still lacking due to the c...
www.science.org
September 26, 2025 at 6:20 AM
A new paper published in Science: Short-range order in semiconductors has been directly confirmed, offering a new way to engineer electronic properties for advanced microelectronics & quantum devices. www.science.org/doi/10.1126/... @science.org @berkeleylab.lbl.gov @gwu1821.bsky.social #EFRC
Water is the most anomalous liquid and extremely hard to model. We made a breakthrough with a machine-learning framework (NEP-MB-pol) that captures water’s quantum nature and simultaneously predicts its structural, thermodynamic, and transport properties. www.nature.com/articles/s41...
NEP-MB-pol: a unified machine-learned framework for fast and accurate prediction of water’s thermodynamic and transport properties - npj Computational Materials
npj Computational Materials - NEP-MB-pol: a unified machine-learned framework for fast and accurate prediction of water’s thermodynamic and transport properties
www.nature.com
August 28, 2025 at 4:21 AM
Water is the most anomalous liquid and extremely hard to model. We made a breakthrough with a machine-learning framework (NEP-MB-pol) that captures water’s quantum nature and simultaneously predicts its structural, thermodynamic, and transport properties. www.nature.com/articles/s41...
Reposted by Shunda Chen
Thank you @physicsworld.bsky.social for covering our work on homogeneous nucleation of graphite and diamond from molten carbon. Did I show you this? physicsworld.com/a/graphite-h...
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Graphite 'hijacks' the journey from molten carbon to diamond – Physics World
Machine-learning-based molecular simulations reveal unexpected crystallization pathway
physicsworld.com
August 16, 2025 at 11:36 PM
Thank you @physicsworld.bsky.social for covering our work on homogeneous nucleation of graphite and diamond from molten carbon. Did I show you this? physicsworld.com/a/graphite-h...
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Our recent study used machine-learning MD simulations to uncover carbon’s surprising crystallization behavior, shedding light on puzzling experimental results and the hidden complexity of how carbon forms graphite or diamond.
🔗 www.nature.com/articles/s41...
#NEP #GPUMD #AI #MachineLearning #Diamond
🔗 www.nature.com/articles/s41...
#NEP #GPUMD #AI #MachineLearning #Diamond
Metastability and Ostwald step rule in the crystallisation of diamond and graphite from molten carbon - Nature Communications
Molecular simulations reveal how diamond and graphite crystallize from molten carbon. Following Ostwald’s step rule, the liquid’s low density drives metastable graphite formation even within the diamo...
www.nature.com
July 29, 2025 at 4:24 AM
Our recent study used machine-learning MD simulations to uncover carbon’s surprising crystallization behavior, shedding light on puzzling experimental results and the hidden complexity of how carbon forms graphite or diamond.
🔗 www.nature.com/articles/s41...
#NEP #GPUMD #AI #MachineLearning #Diamond
🔗 www.nature.com/articles/s41...
#NEP #GPUMD #AI #MachineLearning #Diamond
Our paper "Enabling Type I Lattice-Matched Heterostructures in SiGeSn Alloys Through Engineering Composition and Short-Range Order: A First-Principles Perspective" is selected for the front cover of IEEE Journal of Selected Topics in Quantum Electronics!
doi.org/10.1109/JSTQ...
doi.org/10.1109/JSTQ...
April 11, 2025 at 12:47 AM
Our paper "Enabling Type I Lattice-Matched Heterostructures in SiGeSn Alloys Through Engineering Composition and Short-Range Order: A First-Principles Perspective" is selected for the front cover of IEEE Journal of Selected Topics in Quantum Electronics!
doi.org/10.1109/JSTQ...
doi.org/10.1109/JSTQ...
Excited to share our latest work on Semiconductor-Compatible Topological Digital Alloys, just published in Materials Today! Get 50 days of free access here: authors.elsevier.com/c/1ktXH4tRoW...
April 4, 2025 at 9:13 PM
Excited to share our latest work on Semiconductor-Compatible Topological Digital Alloys, just published in Materials Today! Get 50 days of free access here: authors.elsevier.com/c/1ktXH4tRoW...
Our GPU-accelerated NEP-PIMD approach offers an accessible, accurate, and scalable way to capture nuclear quantum effects in diverse materials. 🚀 Now published in J. Chem. Phys. 162, 064109 (2025) doi.org/10.1063/5.02... #NEP #GPUMD #PIMD #RPMD #TRPMD #MachineLearning #AI
Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
Path-integral molecular dynamics (PIMD) simulations are crucial for accurately capturing nuclear quantum effects in materials. However, their computational inte
doi.org
February 12, 2025 at 11:54 PM
Our GPU-accelerated NEP-PIMD approach offers an accessible, accurate, and scalable way to capture nuclear quantum effects in diverse materials. 🚀 Now published in J. Chem. Phys. 162, 064109 (2025) doi.org/10.1063/5.02... #NEP #GPUMD #PIMD #RPMD #TRPMD #MachineLearning #AI
Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy on desktop gaming GPUs! 💻 Enabled by Neuroevolution Potential (NEP) in GPUMD. Published in J. Appl. Phys. 137, 014305 (2025) doi.org/10.1063/5.02... #MachineLearning #NEP #GPUMD #graphene #AI
Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy enabled by neuroevolution potential on desktop GPUs
First-principles molecular dynamics simulations of heat transport in systems with large-scale structural features are challenging due to their high computationa
doi.org
January 22, 2025 at 4:28 AM
Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy on desktop gaming GPUs! 💻 Enabled by Neuroevolution Potential (NEP) in GPUMD. Published in J. Appl. Phys. 137, 014305 (2025) doi.org/10.1063/5.02... #MachineLearning #NEP #GPUMD #graphene #AI
Reposted by Shunda Chen
Dylan's first research paper outlines a workflow to calculate vibrational properties, thermal conductivity, and elastic moduli at finite temperature with #MachineLearning potentials. #open-access in J.Appl.Phys. @aip.bsky.social
Collaboration with @flokno.bsky.social doi.org/10.1063/5.02...
Collaboration with @flokno.bsky.social doi.org/10.1063/5.02...
Elastic moduli and thermal conductivity of quantum materials at finite temperature
We describe a theoretical and computational approach to calculate the vibrational, elastic, and thermal properties of materials from the low-temperature quantum
pubs.aip.org
December 12, 2024 at 1:39 AM
Dylan's first research paper outlines a workflow to calculate vibrational properties, thermal conductivity, and elastic moduli at finite temperature with #MachineLearning potentials. #open-access in J.Appl.Phys. @aip.bsky.social
Collaboration with @flokno.bsky.social doi.org/10.1063/5.02...
Collaboration with @flokno.bsky.social doi.org/10.1063/5.02...
Reposted by Shunda Chen
🌟 Exciting news! We're now on Bluesky! Follow us and join the conversation with #F24MRS. Stay connected with the latest updates and insights from the materials community!
December 1, 2024 at 7:32 PM
🌟 Exciting news! We're now on Bluesky! Follow us and join the conversation with #F24MRS. Stay connected with the latest updates and insights from the materials community!
Reposted by Shunda Chen
Hello, it's me.
I'm in California dreaming about who I used to be.
When I was younger and free.
I'm in California dreaming about who I used to be.
When I was younger and free.
November 14, 2024 at 6:33 PM
Hello, it's me.
I'm in California dreaming about who I used to be.
When I was younger and free.
I'm in California dreaming about who I used to be.
When I was younger and free.
Reposted by Shunda Chen
🚨 Hello #machinelearning #compchem friends. After many months of careful coding, checking, optimization and renaming all classes, we are happy to announce torch-pme - a fast and flexible library to incorporate long-range physics into atomistic ML models.
December 5, 2024 at 11:28 AM
🚨 Hello #machinelearning #compchem friends. After many months of careful coding, checking, optimization and renaming all classes, we are happy to announce torch-pme - a fast and flexible library to incorporate long-range physics into atomistic ML models.
Reposted by Shunda Chen
Welcome to all the newcomers to #ChemSky 🧪
I don't post much, but you'll get a dose of #compchem and materials discovery, a bit of #machinelearning (with skepticism) and some sprinkling of #Pittsburgh (including @pitt.bsky.social and @pittchem.bsky.social)
Enjoy some recent @avogadro.cc renders
I don't post much, but you'll get a dose of #compchem and materials discovery, a bit of #machinelearning (with skepticism) and some sprinkling of #Pittsburgh (including @pitt.bsky.social and @pittchem.bsky.social)
Enjoy some recent @avogadro.cc renders
November 15, 2024 at 9:09 PM
Welcome to all the newcomers to #ChemSky 🧪
I don't post much, but you'll get a dose of #compchem and materials discovery, a bit of #machinelearning (with skepticism) and some sprinkling of #Pittsburgh (including @pitt.bsky.social and @pittchem.bsky.social)
Enjoy some recent @avogadro.cc renders
I don't post much, but you'll get a dose of #compchem and materials discovery, a bit of #machinelearning (with skepticism) and some sprinkling of #Pittsburgh (including @pitt.bsky.social and @pittchem.bsky.social)
Enjoy some recent @avogadro.cc renders
Reposted by Shunda Chen
As my first post on @bsky.app, I'm happy to announce the publication of a paper describing the new (very fast!) GPU version of our RASPA simulation code, gRASPA. Congratulations to Zhao Li and the team!
November 20, 2024 at 9:55 PM
As my first post on @bsky.app, I'm happy to announce the publication of a paper describing the new (very fast!) GPU version of our RASPA simulation code, gRASPA. Congratulations to Zhao Li and the team!
Reposted by Shunda Chen
Hello! I'm posting this both here and on the X-rated site, let's see where it gets more re-posts 😇. We are looking for a research software engineer to help us develop (even) better code for #compchem #atomicscale #machinelearning. Check out the specs and apply!
www.epfl.ch/labs/cosmo/i...
www.epfl.ch/labs/cosmo/i...
Jobs
-
www.epfl.ch
December 3, 2024 at 11:56 AM
Hello! I'm posting this both here and on the X-rated site, let's see where it gets more re-posts 😇. We are looking for a research software engineer to help us develop (even) better code for #compchem #atomicscale #machinelearning. Check out the specs and apply!
www.epfl.ch/labs/cosmo/i...
www.epfl.ch/labs/cosmo/i...
🎉 Exciting news! Our unified neuroevolution potential (UNEP-v1) is now published in Nature Communications!
Read it here 🔗 nature.com/articles/s41...
#AI #MachineLearning #MaterialsScience #MD #GPU
Read it here 🔗 nature.com/articles/s41...
#AI #MachineLearning #MaterialsScience #MD #GPU
General-purpose machine-learned potential for 16 elemental metals and their alloys - Nature Communications
Machine-learned potentials are accurate but often lack broad applicability. Here, authors develop a general-purpose neuroevolution potential for 16 metals and their alloys, achieving efficient and acc...
nature.com
December 9, 2024 at 1:52 AM
🎉 Exciting news! Our unified neuroevolution potential (UNEP-v1) is now published in Nature Communications!
Read it here 🔗 nature.com/articles/s41...
#AI #MachineLearning #MaterialsScience #MD #GPU
Read it here 🔗 nature.com/articles/s41...
#AI #MachineLearning #MaterialsScience #MD #GPU