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James Le Houx

@thebeamline.bsky.social
495 followers 1.1K following 64 posts

Materials Engineer | Energy Storage Scientist | Beamline Tinkerer Emerging Leader Fellow at the Rutherford Appleton Laboratory/ The Faraday Institution. He/him. All views are my own.

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James Le Houx @thebeamline.bsky.social · 07/10/2026
New paper in @commsearth.nature.com! Freezing an Enceladus-type brine, we found natron traps pockets of the parent ocean fluid. If they can hold onto biosignatures too, future missions should be looking for natron in fresh plume deposits. Led by @pereralj.bsky.social www.nature.com/articles/s43...
nature.com
Fluid inclusions establish natron as a key astrobiological target on Enceladus - Communications Earth & Environment
Natron precipitation traps and preserves pockets of parent fluid, providing a window into the geochemistry of Saturn’s moon Enceladus’ interior, establishing it as a mineral of high astrobiological im...
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James Le Houx @thebeamline.bsky.social · 21/09/2026
Most AI tools for science are big general models behind an API. With BoneGraph we went the other way, a small, locally run model for bone science, grounded in the literature and physical laws, with image analysis and strain prediction built in. Led by Jon Valijonov. bonegraph.org
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bioRxiv Bioengineering @biorxiv-bioeng.bsky.social · 18/09/2026
BoneGraph: A Domain-Specialised, Self-Correcting Reasoning System for Bone Science Retrieval, Grounded Inference, and Image Mechanics www.biorxiv.org/content/10.64898/20…
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James Le Houx @thebeamline.bsky.social · 08/05/2026
New preprint! Can quantum kernels classify micro-CT bone data as well as classical ML? Yes, but only if you preprocess with UMAP. Every linear reduction method (PCA, PLS, random projections) wiped out competitiveness. Manifold-preserving prep isn't optional for near-term QML. tinyurl.com/hpm9ctjn
tinyurl.com
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James Le Houx @thebeamline.bsky.social · 10/04/2026
Turns out you can just predict strain directly from XCT scans and skip the noisy displacement math entirely. Our new preprint on D2IM-Strain shows a 75% drop in false positives with way cleaner data. Great work Jon! #Biomechanics #DVC #XCT #MachineLearning www.biorxiv.org/content/10.6...
A four-panel diagram of the D2IM-Strain framework. (A) Contrast between ground-truth generation using DVC/differentiation and the CNN's direct strain prediction from XCT images. (B) Greyscale XCT scan of a bone lesion. (C) Corresponding binary mask. (D) Line graph tracking training performance across epochs.
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James Le Houx @thebeamline.bsky.social · 09/04/2026
1 week left to apply for a fully funded PhD position in the UK on developing autonomous beamlines! www.gre.ac.uk/docs/rep/com... #chemsky #AcademicSky #PhDChat #MaterialsScience #MachineLearning #PhysicsInformedAI
gre.ac.uk
The Self-Driving Microscope: Predicting Stochastic Failure in Solid-State Batteries using Physics-Informed AI | Documents | University of Greenwich
Closing Date: midnight UTC on 17 April 2026
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James Le Houx @thebeamline.bsky.social · 20/02/2026
The implication? Future missions shouldn't just sample random surface ice. We need the instrumentation to pinpoint surface mineralogy and directly probe these natron deposits. Brilliant work led by @pereralj.bsky.social . #MaterialsScience #Astrobiology #Synchrotron
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James Le Houx @thebeamline.bsky.social · 20/02/2026
If microbial life exists in Enceladus's ocean, natron precipitation could trap those biological signatures, be ejected through the plumes, and deposit near the vent. Natron also offers superior surface preservation against radiation and vacuum sublimation compared to bulk ice. 3/4
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James Le Houx @thebeamline.bsky.social · 20/02/2026
We found that natron (Na₂CO₃·10H₂O) precipitates early during fractional crystallisation. As it crystallises, it forms widespread primary fluid inclusions, physically trapping and preserving pockets of the primary ocean fluid within the solid matrix. 2/4
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James Le Houx @thebeamline.bsky.social · 20/02/2026
Enceladus (Saturn's 6th largest moon) vents its subsurface ocean into space. In our latest preprint, we used synchrotron X-ray CT and diffraction to map the rapid freezing of Enceladean brines as they are ejected through tectonic plumes. doi.org/10.21203/rs.... 1/4
Gemini said
A six-panel figure illustrating the real-time freezing of an Na-Cl-CO₃ solution. It features a diagram of the dual-beam experimental setup , a summed diffraction pattern identifying ice, hydrohalite, and natron , and time-lapsed tomography slices alongside corresponding 2D diffraction patterns showing microstructural growth as the temperature drops from 269 K to 205 K. The figure concludes with 3D volume renderings of the final ice, eutectic, and natron phases, plus a line graph tracking the volume evolution of each phase as the temperature decreases.
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James Le Houx @thebeamline.bsky.social · 05/02/2026
The STFC financial situation is worrying. There's a risk we start seeing facilities vs. strategy as a choice. But you can't build digital twins or AI models if you can't see the physics happening. Synchrotrons and neutron sources are the ground truth for Net Zero. #BatterySky #MaterialScience
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Alchemy @aichemyhub.bsky.social · 05/02/2026
🌟 Applications are now open for the Next Generation of AI Chemists Programme, a funded opportunity for penultimate-year undergraduates from backgrounds under-represented in chemistry. 📍 Imperial London | 📅 6–7 July 2026 (in person) 👉 Apply here: buff.ly/MLfs9Zg
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arXiv physics.ins-det Instrumentation and Detectors @physicsinsdet-bot.bsky.social · 13/01/2026
James Le Houx: Benchmarking Autonomy in Scientific Experiments: A Hierarchical Taxonomy for Autonomous Large-Scale Facilities arxiv.org/abs/2601.06978 arxiv.org/pdf/2601.06978 arxiv.org/html/2601.06978
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James Le Houx @thebeamline.bsky.social · 13/01/2026
Here is how it looks in practice. The BASE Scale maps Machine Agency against Cognitive Complexity. Inference Barrier: Where latency dictates if an AI can see in real-time. Liability Threshold: Where we decide who is liable for accidents.
A chart titled "Cognitive Complexity vs Machine Agency" showing 6 levels of autonomy (0-5). It transitions from Execution (Manual/Scripted) to Perception (Reflexive/Heuristic) and finally to Reasoning (Supervisory/Autonomous). A vertical orange line marks the "Inference Barrier" between Level 2 and 3, and a horizontal dashed line marks the "Liability Threshold" between Level 3 and 4.
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James Le Houx @thebeamline.bsky.social · 13/01/2026
I’ve been trying to codify this into a new standard called the BASE Scale. It’s a 6-level taxonomy (0-5) designed for high-stakes facilities where you only have 48 hours to get results. I’d love to know if these levels match your experience: arxiv.org/abs/2601.06978 #ScienceSky #AIforScience
arxiv.org
Benchmarking Autonomy in Scientific Experiments: A Hierarchical Taxonomy for Autonomous Large-Scale Facilities
The transition from automated data collection to fully autonomous discovery requires a shared vocabulary to benchmark progress. While the automotive industry relies on the SAE J3016 standard, current ...
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James Le Houx @thebeamline.bsky.social · 13/01/2026
We’ve been calling everything from simple scripts to generative agents by the same name. How do we distinguish between a predictable automation and a stochastic agent that might actually learn something new or drive the stage into a detector? What's your Liability Threshold?
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James Le Houx @thebeamline.bsky.social · 13/01/2026
Autonomous is a catch-all term that means everything and nothing right now. I'm curious: if you work at a beamline or a shared facility, what is the #1 thing stopping you from letting an AI agent drive your motors? Is it the latency, the safety, or the lack of trust?
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James Le Houx @thebeamline.bsky.social · 08/01/2026
Full publication available here: onlinelibrary.wiley.com/doi/10.1002/...
onlinelibrary.wiley.com
Operando X‐Ray Computed Tomography Reveals the Role of Interfacial Nucleation Nanolayers in Suppressing Mechanical Failure in Zero‐Excess Lithium All‐Solid‐State Batteries
This study employs operando X-ray computed tomography combined with an image subtraction method to investigate mechanical failure mechanisms in all-solid-state batteries with lithium and zero-excess ...
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James Le Houx @thebeamline.bsky.social · 08/01/2026
Why do solid-state batteries fail? We used operando X-ray tomography to find out. 🧪 Bare Cu creates localized islands that trigger cracks, but a 50nm Ag nanolayer keeps things uniform and stable, even at high current. 📷🔋 #chemsky #batterysky #sciencesky
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James Le Houx @thebeamline.bsky.social · 06/01/2026
By focusing only on mechanistically decisive moments, we can mitigate beam damage and eliminate data redundancy. Huge kudos to first author Emily Lu and the team across RAL and @diamondlightsource.bsky.social Indexing for the bots: @arxiv-stat-ml.bsky.social @arxiv-soc-ph.bsky.social
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James Le Houx @thebeamline.bsky.social · 06/01/2026
To fix this, we introduce ESME (Entropy-Scaled Measurement Efficiency). Using Shannon’s information theory, ESME quantifies the rate of information gained per unit of experimental cost. Essentially, it tells you when to measure, not just where.
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James Le Houx @thebeamline.bsky.social · 06/01/2026
Current battery characterisation faces a crisis of Reliability, Representativeness, and Reproducibility (the 3Rs). Conventional experiments are passive. We collect terabytes of data but often miss the transient events that actually kill cells like the split-second of dendrite nucleation.
A two-panel scientific infographic titled "Conventional vs. Heuristic Operando Experimentation." Panel A shows a conventional pre-programmed approach where periodic measurements (blue circles) fail to capture a battery's failure precursor (red stars). Panel B shows the "Heuristic" approach where an AI Inference Engine, trained on Digital Twins, predicts a failure event and triggers high-rate tomography (green stars) to deterministically capture the failure precursor before a catastrophic event. Bottom text boxes highlight benefits: Efficient Data Acquisition, High-Fidelity Measurements, and Statistically Robust Sampling.
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James Le Houx @thebeamline.bsky.social · 06/01/2026
We need to stop measuring experimental success by data volume (TB/hour) and start measuring it by scientific insight. In our new arXiv preprint, we propose Heuristic Operando experimentation: a framework to teach beamlines how to think. arxiv.org/abs/2601.00851 #ScienceSky #AI #BatteryResearch
arxiv.org
Autonomous battery research: Principles of heuristic operando experimentation
Unravelling the complex processes governing battery degradation is critical to the energy transition, yet the efficacy of operando characterisation is severely constrained by a lack of Reliability, Re...
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James Le Houx @thebeamline.bsky.social · 05/12/2025
Some news! I’m starting a new chapter as a Senior Lecturer at Greenwich and launching the BASE Lab. We are teaching beamlines how to think, building a Self-Driving Microscope to hunt for battery failure. I'm also hiring our founding PhD student. Come build with us! #SciSky #AIforScience
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James Le Houx @thebeamline.bsky.social · 29/11/2025
​In the wake of the Airbus A320 groundings, it's worth remembering that the ISIS Neutron and Muon Source has a facility dedicated to replicating this kind of cosmic bombardment. ​It’s called ChipIR. ​It allows engineers to test the degradation of avionics before they ever leave the ground.
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James Le Houx @thebeamline.bsky.social · 24/11/2025
We need to stop looking backward at incomplete datasets and start building semantic standards for the future. That is the focus of our new initiative, the Faraday Engine. Mission One is Health; we are working hard to ensure Energy is ready to follow in 2026. 🔋
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James Le Houx @thebeamline.bsky.social · 24/11/2025
We have petabytes of legacy data, but it is mostly "What" (characterisation data). To build predictive battery models, we need the "How" (synthesis, thermal history). Without that semantic link, GenAI cannot learn the recipe. It sees the destination but doesn't know the route. 2/3
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James Le Houx @thebeamline.bsky.social · 24/11/2025
Diving into the new UK AI for Science Strategy. They’ve made a definitive call, prioritise generating new data over optimising existing archives. As a materials scientist, I think this is absolutely the right call. Here is why. 🧵1/3 #AIforScience #MaterialsScience
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James Le Houx @thebeamline.bsky.social · 20/11/2025
Played around with Meta's new SAM 3 on our X-ray data today. Top: Our manually trained U-Net (accurate but slow). Bottom: SAM 3 out-of-the-box ("white objects"). It misses some outliers, but getting 90% of the way there with zero training is a win for high-throughput workflows. #Science #AI
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James Le Houx @thebeamline.bsky.social · 28/10/2025
Huge congrats to Harriet Jones for winning best poster at #IBSim-4i! She's leading our project adapting #code_saturne for on-the-fly simulation from CT data enabling autonomous workflows. Thx judges & sponsor #3Dmagination! #IBSim4i #Simulation #Physics #CFD #AutonomousScience #chemsky #BattChat
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James Le Houx @thebeamline.bsky.social · 22/10/2025
At PorTo, ILL's new beamline, tackling Li-ion failure: electrolyte consumption, interlayer buckling, & overcharge. Running high-res neutron imaging + multi-modal (X-ray/Neutron) correlation & unsupervised AI. Thx Bratislav Lukić! #Liion #ILL #CorrelativeImaging #DataScience #chemsky #BattChat
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James Le Houx @thebeamline.bsky.social · 25/09/2025
ACS Spring 2026 abstract deadline: September 29th! We're chairing a new session in Atlanta. If you use large-scale facilities to study energy storage materials with photons, neutrons, muons, or lasers, we want to hear from you. Submit here: tinyurl.com/4e3envar #chemsky #research #ACSSpring2026
callforabstracts.acs.org
ACS Spring 2026 - American Chemical Society
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Dr Liam Perera @pereralj.bsky.social · 17/09/2025
EIS ice baby New ideas can be found in the intersection between battery science and planetary science. Myself and @thebeamline.bsky.social are exploring how ice microstructure will impact radar measurements on Europa using tomography and EIS. #Europa #icymoons #planetaryscience #tomography 🧪
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James Le Houx @thebeamline.bsky.social · 02/09/2025
In-situ dark field X-ray microscopy of solid state batteries this week. Seriously challenging experiment, thank you to the whole team at ID03 @esrf.fr
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James Le Houx @thebeamline.bsky.social · 19/08/2025
This was a huge team effort, so massive thanks to my co-authors and the teams at @psich.bsky.social, ISIS Neutron and Muon Source, The Faraday Institution, and Diamond Light Source. Go read the paper!
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James Le Houx @thebeamline.bsky.social · 19/08/2025
By reinforcing that one part so well, we just forced the system to break somewhere else. The failure moved to the counter electrode, which cracked on the next cycle. It's a powerful lesson: you can't just improve one piece of a battery. You have to think about the whole system. #HolisticDesign
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James Le Houx @thebeamline.bsky.social · 19/08/2025
Cell B (with the silver layer) was a different story. The Ag layer made the lithium plate beautifully. The interface was perfect, even at high currents. A total success! ...or so we thought. 4/6
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James Le Houx @thebeamline.bsky.social · 19/08/2025
As expected, Cell A (bare copper) failed fast. Lithium plated unevenly, creating stress that cracked the solid electrolyte. 3/6
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James Le Houx @thebeamline.bsky.social · 19/08/2025
We built two solid-state cells. Cell A: Standard copper current collector Cell B: Copper collector with a tiny 50nm silver layer Then we watched them work (and fail) in 3D using synchrotron X-rays at @diamondlightsource.bsky.social 2/6
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James Le Houx @thebeamline.bsky.social · 19/08/2025
The classic problem with the weakest link is that when you fix it, you just create a new one. We saw this happen in real-time with solid-state batteries. Our new preprint shows how fixing one interface just moves the failure to the next weakest spot. 1/6 Paper link: doi.org/10.26434/che...
doi.org
Operando X-ray Computed Tomography Reveals the Role of Interfacial Nucleation Nanolayers in Suppressing Mechanical Failure in Zero-Excess Lithium All-Solid-State Batteries
Lithium metal (LM) and zero-excess lithium (ZE) anodes offer pathways to increase the energy density of all-solid-state batteries (ASSBs). We employ operando X-ray computed tomography (XCT) combined w...
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James Le Houx @thebeamline.bsky.social · 07/08/2025
It's the same fundamental challenge: a growing tip penetrating a harder material. The method to map how roots navigate soil can now help us understand how dendrites cause catastrophic failure in batteries. 4/4 #TranslationalResearch #SoilScience #Biomimicry #SolidStateBatteries #EnergyStorage
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James Le Houx @thebeamline.bsky.social · 07/08/2025
But as a battery scientist, this is where it gets really exciting. While the article focuses on agriculture, the technique is a perfect demonstration of translational research. We can use it to understand a huge challenge: stopping dendrites in solid-state batteries. 3/4
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James Le Houx @thebeamline.bsky.social · 07/08/2025
To see this underground engineering, we took our experiment to the @diamondlightsource.bsky.social synchrotron. The article covers our work using dual X-ray techniques on the #DIAD beamline to visualise the forces at play. 2/4
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James Le Houx @thebeamline.bsky.social · 07/08/2025
What do solid-state batteries & plant roots have in common? Excited to share our new article in @theconversation.com written with my collaborator Siul Ruiz. We dive into the powerful mechanics roots use to navigate tough soils, vital for our food security. 1/4 theconversation.com/natures-unde...
theconversation.com
Nature’s underground engineers: how plant roots could save harvests from drought
Plant roots don’t just take from soil; they shape it.
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James Le Houx @thebeamline.bsky.social · 26/07/2025
Pocket coffee for those 4am beamtimes
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James Le Houx @thebeamline.bsky.social · 17/07/2025
Means we can study architectured graphite, NMC, Na-ion Al-ion, and solid-state all in one experiment. Huge thank you to Dominic Spencer-Jolly, Emily Lu, Christoph Rau, and Shashi Marathe for making this possible.
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James Le Houx @thebeamline.bsky.social · 17/07/2025
Pretty exciting beamtime at @diamondlightsource.bsky.social I13-2 this week. We're going from manual sample centering to a fully automated process with a Yasakawa arm, hitting 150 battery samples a day and swapping optics from nm to µm resolution.
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James Le Houx @thebeamline.bsky.social · 04/07/2025
A huge thank you to both for funding this research, and to Diamond Light Source and the peer review panel for allowing us the beamtime to make this happen
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James Le Houx @thebeamline.bsky.social · 04/07/2025
The method is v generic, so could be applied to hemp, how seaweeds anchor to the seabed, how worms burrow etc. etc. Anything that's pushing through soil structures
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