Emory Chan

Multi‐Ion Doping in Low‐Phonon‐Energy Nd3+ Based Double Perovskite Unlocks Multimodal Anti‐Counterfeiting and High‐Performance Optical Thermometry Multi-ion engineering in low-phonon Nd-based double perovskites enables excitation-programmable multicolor UC/DS emission and record-sensitivity multi-channel optical thermometry for advanced anti-co...

Multi‐Ion Doping in Low‐Phonon‐Energy Nd3+ Based Double Perovskite Unlocks Multimodal Anti‐Counterfeiting and High‐Performance Optical Thermometry - Xin - Advanced Functional Materials - Wiley Online Library advanced.onlinelibrary.wiley.com/doi/10.1002/...

Honored to have our work on #photonAvalanchingNanoparticles with @askripka.bsky.social be selected as one of @berkeleylab.lbl.gov's top stories of 2025. Read the original article here: doi.org/10.1038/s415...

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs - Nature Computational Science Graph neural networks built on physically motivated representations enable gradient-based optimization of complex upconverting nanoparticle heterostructures, revealing photophysical design rules and a...

Out in @natcomputsci.nature.com: A roadmap for inverse design of #nanomaterials heterostructures via HT data gen -> representation dev -> heteroGNN training -> gradient-based global opt! w/ @emorychannano.bsky.social @ewcspottesmith.bsky.social
www.nature.com/articles/s43...
Free link rdcu.be/eTH72

For a more digestible summary of our recent @natcomputsci.nature.com article, here's the research brief that @samblau.bsky.social and I wrote... complete with a #BehindThePaper tidbit that thankfully has less drama than a VH1 Behind the Music episode (free link: rdcu.be/eUVIw)

We're still looking for motivated postdoc candidates for this exciting opportunity. See below and please repost!

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs Nature Computational Science - Graph neural networks built on physically motivated representations enable gradient-based optimization of complex upconverting nanoparticle heterostructures,...

Free online access to the @natcomputsci.nature.com paper: rdcu.be/eTH72

Downloadable PDF from chemRxiv (in our original full-length format): chemrxiv.org/engage/chemr...

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs Nature Computational Science - Graph neural networks built on physically motivated representations enable gradient-based optimization of complex upconverting nanoparticle heterostructures,...

Free online access to the @natcomputsci.nature.com paper: rdcu.be/eTH72

Downloadable PDF from chemRxiv (we prefer this format, but some of the figure captions were cleaned up in press):
chemrxiv.org/engage/chemr...

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs Nature Computational Science - Graph neural networks built on physically motivated representations enable gradient-based optimization of complex upconverting nanoparticle heterostructures,...

Free online access to the @natcomputsci.nature.com paper: rdcu.be/eTH72

Downloadable PDF from chemRxiv (we prefer this format, but some of the figure captions were cleaned up in press):
chemrxiv.org/engage/chemr...

Our manuscript on deep learning of upconverting nanoparticle heterostructures w/ @samblau.bsky.social is finally out in @natcomputsci.nature.com!

See 🧵for links to free access via Readcube and chemrxiv.

@berkeleylab.lbl.gov @molecularfoundry.lbl.gov @mitcheme.bsky.social

Sub-10 nm upconversion nanocrystals for long-term single-particle tracking - Nature Communications This study presents ultrasmall, bright lanthanide-doped upconversion nanoparticles that overcome surface quenching, enabling high spatiotemporal resolution tracking of membrane proteins with exception...

Congrats to @molecularfoundry.lbl.gov users Yunxiang Zhang and Qian Liu for their latest work in @natcomms.nature.com: "Sub-10 nm upconversion nanocrystals for long-term single-particle tracking." doi.org/10.1038/s414.... w/ Chan group postdoc Xiaojing Xia on on the kinetic Monte Carlo #KMC #UCNPs

Love building microscopes? Looking for a #postdoc? Come work w/ me, Ed Barnard, Jim Schuck, Bruce Cohen & others @berkeleylab.lbl.gov developing a #photonAvalanching microscope for bio & environmental sensing! Description below: #jobs #nonlinear #optics #photonics

drive.google.com/file/d/1Qcof...

Chan Group @ Molecular Foundry - openings The Chan group welcomes inquiries for motivated, creative, and independent researchers at all levels (postdoctoral fellow, graduate students, undergraduates, and visitors), even in the absence of post...

We have a postdoc opening w/ @samblau.bsky.social
on the autonomous synthesis of colloidal upconverting nanoparticles.

If you're looking for an exciting postdoc combining #robotics, #nanochemistry, #machinelearning, #UCNPs & simulations, see the link below!

combinano.lbl.gov/openings

⚡ Level up your research skills! Our 2.5-day Summer School will teach you closed-loop experiment design, data visualization, and robotic synthesis using cutting-edge platforms. Open to all students & postdocs! Register today: bit.ly/3Z5Uf8m #FutureOfScience #Automation

Room-temperature multiferroicity in sliding van der Waals semiconductors with sub-0.3 V switching - Nature Communications The authors observe out-of-plane ferroelectric polarization induced by interlayer sliding in a multiferroic van der Waals semiconductor. The switching voltage scales down to 0.3 V at room temperature,...

Congrats to @molecularfoundry.lbl.gov users Rui Chen and Jie Yao on their publication in @natcomms.nature.com!
doi.org/10.1038/s414...

2 #S25MRS talks down, 1 proposal submitted (internally). Time to take an ebike ride around Seattle before my flight!It's so nice here... great choice, MRS.

Check out my 2 talks at #S25MRS this week in Seattle!

@mphendricks.bsky.social, Michael Campos & the rest of Jon Owen's lab were some of the greatest WANDA users of all time. They took LBNL by storm with boxes of distilled solvents and custom precursors.

They showed that robots are pointless if the other parts of your workflow are not reproducible.

WANDA misses you! We look forward to training all the future Skripka lab students on WANDA!

Reproducible, High-Throughput Synthesis of Colloidal Nanocrystals for Optimization in Multidimensional Parameter Space While colloidal nanocrystals hold tremendous potential for both enhancing fundamental understanding of materials scaling and enabling advanced technologies, progress in both realms can be inhibited by...

I can't believe it's been 15 years since this paper came out! We introduced a nanocrystal-synthesizing robot called WANDA to the world! Now robots & ML are all the rage, but WANDA was a pioneer & is still going strong. @deliamilliron.bsky.social @molecularfoundry.lbl.gov
pubs.acs.org/doi/full/10....

New article online: Intrinsic optical bistability of photon avalanching nanocrystals.

go.nature.com/3DSOmUC

Up-conversion nanoparticles measure medium-sized forces in hard-to-reach places Squeezing the tiny crystals can dramatically change their photophysics.

pubs.aip.org/physicstoday...

glad you found it useful! I would be happy to chat about future Foundry user proposals whenever you have a potential project in mind.

That's it! For more information on submitting a @molecularfoundry.lbl.gov, follow the post below!

bsky.app/profile/mole...

#10) If your proposal is on the bubble for a bin, you have a better chance of sneaking in if your proposal has: low staff effort, large benefit to @molecularfoundry.lbl.gov, or is a project that a staff member is really excited to work on.

#9) Although you get a score for your proposal, you are really only competing with other proposals in your "bin." Basically this correlates to a specific instrument or staff member's available time. The bin is filled up with the top-ranked proposals until it's full.

#8) Each of the 7 @molecularfoundry.lbl.gov facilities reviews proposals a little differently, so make sure to talk to Staff in the lead facility to understand what their review boards want to see in a proposal.

#7) Use attractive figures that crystallize your proposed work. Reviewers read a ton of these proposals, so graphics will help you stand out and break up big blocks of text.

#6) Make sure to list all the equipment that you need -- you won't be able to add high demand tools like TEM, robots, later. You may need separate proposals for those. Don't pile on random capabilities for fun... The buffet strategy is a red flag for a proposal.

#5) Show how you will contribute to the @molecularfoundry.lbl.gov community! That's what makes us great! Helping to develop new workflows/capabilities, training users, participating in committees -- those all reduce staff effort <-- major brownie points.

#4) Show how your project is feasible! Cite specific processes/reactions, walk reviewers through the important steps, e.g., synthesis, characterization, data analysis. Show preliminary data. Don't say you're going to use water in a glovebox. Show that you've done your homework!