The Matter Lab

The Matter Lab

@thematterlab.bsky.social

The materials for tomorrow, today. We are the Matter Lab at the University of Toronto, led by Professor Alán Aspuru-Guzik. Our group works at the interface of theoretical chemistry with physics, computer science, and applied mathematics.

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🎉Congratulations to our the Matter Lab team <The|Matter>, comprised of Yuma Nakamura, Yoshihiro Ogura, and Jenyu Chang, on receiving the Excellent Research Award (優秀研究賞) in the NEDO Quantum Computing Challenge QoL category!

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🚀The team earned recognition in the award tier and secured continued priority access to IBM and Quantinuum quantum hardware to support the next phase of their research.

With this recognition in Season 1 (2025–2026), and continued hardware access, the team is moving forward into Season 2 (2026–2027), aiming for the top prize. We look forward to seeing what they accomplish next!

🎉Congratulations to our the Matter Lab team <The|Matter>, comprised of Yuma Nakamura, Yoshihiro Ogura, and Jenyu Chang, on receiving the Excellent Research Award (優秀研究賞) in the NEDO Quantum Computing Challenge QoL category!

Congratulations to @aspuru.bsky.social on being named a 2026 ScholarGPS® Highly Ranked Scholar™! This recognition places him among the top 0.05% of scholars worldwide within his ranking categories, reflecting his publication record, research impact, and the quality of his scholarly contributions.

Instead of screening a supplier catalogue, the team built a virtual library of 74,000 compounds, none of them for sale, all reachable in a single synthetic step. Boltz-2 then navigated that space prospectively, and the resulting predictions were translated directly into a synthesis plan.

🦾Six specialist AI agents, coordinated by a central agent, support tasks ranging from quantum circuits to energy transport in photosynthetic systems. The goal is to make advanced simulations more accessible and give researchers more time to develop ideas and evaluate results.

🔑 As Varinia mentioned, successful automation still requires careful validation and human oversight. Looking ahead, the team aims to connect simulations with laboratory experiments, bringing computation and experiment into a shared research cycle. Thank you to ScienceNews for featuring our work!

El Agente Cuántico helps lower these barriers: researchers describe their scientific question, and the system selects computational tools, writes and runs code, and corrects errors along the way.

🤔 What if AI could not only automate scientific experiments, but also design and build the laboratories needed to perform them? We are excited to introduce Self-Building Labs (SBL), a new paradigm for autonomous scientific laboratories! 🌐 self-building-labs.github.io 📜 arxiv.org/abs/2610.23826

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Our vision is to move beyond laboratories that simply execute predefined experiments toward scientific infrastructure that can build new capabilities from scratch, continuously adapt, and evolve alongside scientific discovery. We also envision leveraging SBL to build safer laboratories.

🤔 What if AI could not only automate scientific experiments, but also design and build the laboratories needed to perform them? We are excited to introduce Self-Building Labs (SBL), a new paradigm for autonomous scientific laboratories! 🌐 self-building-labs.github.io 📜 arxiv.org/abs/2610.23826

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In our latest work, we demonstrate how SBL can: 🔹 Automatically reconstruct digital twins of laboratory equipment and environments. 🔹 Develop and validate new robotic manipulation skills through simulation and physical feedback.

🔹 Execute real-world quantum-dot synthesis experiments, coordinating liquid handling, robotic manipulation, plate sealing, and optical measurements. 🔹 Scale from individual robotic workstations to interconnected laboratories with multiple robots and instruments.

🤔 What if AI could not only automate scientific experiments, but also design and build the laboratories needed to perform them? We are excited to introduce Self-Building Labs (SBL), a new paradigm for autonomous scientific laboratories! 🌐 self-building-labs.github.io 📜 arxiv.org/abs/2610.23826

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Whether starting from an empty laboratory or an existing self-driving lab, SBL aims to autonomously develop the capabilities needed to achieve scientific objectives, from laboratory layouts and digital twins to robotic skills and experimental workflows.

🤔 What if AI could not only automate scientific experiments, but also design and build the laboratories needed to perform them? We are excited to introduce Self-Building Labs (SBL), a new paradigm for autonomous scientific laboratories! 🌐 self-building-labs.github.io 📜 arxiv.org/abs/2610.23826

While self-driving laboratories (SDLs) have significantly advanced scientific automation, their capabilities are often limited by predefined equipment, robotic skills, and experimental workflows.

The Matter Lab reposted

A few weeks ago, more than 80 current and former graduate students and postdocs came together to celebrate him and inaugurate the Matter Lab International Conference at the Universidad Nacional Autónoma de México (UNAM). What an incredible community 👨‍🔬❤️

The Matter Lab reposted

The Matter Lab reposted

The AC is training today’s talent with the skills in AI, automation and ethics needed to advance accelerated discovery. From self-driving lab 101 workshops to a $1M+ national training initiative, learn more about how the AC is building capacity in our latest impact report: shorturl.at/hVBsI

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🚀 We also find that DIA can reach successful states more efficiently and move further from the pretrained behavior distribution, highlighting the importance of assigning credit to the intermediate decisions that construct an action.

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🔑 Key insights: DIA introduces credit assignment within the denoising process itself. We showed that better credit assignment inside the generative process can lead to better policy optimization.

🤔 Diffusion policies generate actions through multiple denoising steps, but standard RL fine-tuning methods often assign the same environment-level credit across the full denoising trajectory.

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- Screen metal-organic frameworks containing an X node and a Y ligand for methane or other gas adsorption - Identify plausible transition states for the reaction of A and B leading to product C

Using El Agente Quntur, Gráfico and Estructural, the team will select several questions and demonstrate how El Agente approaches them, based on scientific relevance and what can reasonably be addressed during the webinar. Looking forward to see you there!

Registrants are invited to submit questions through the form above. Examples: - Investigate the IR, UV, and Raman spectra of a series of organic molecules - Evaluate small-molecule binding to transition-metal complexes relevant to investigating a given catalytic activity

The Matter Lab reposted

Today #ArtemMishchenko gave an #ACseminar on why experimental data is the next frontier for AI-driven materials discovery. He’s #hiring a thin-film research scientist to join the #GoogleDeepMind Materials Discovery Lab in London!🔬To apply DM Artem your CV + why you’re a fit for the role on LinkedIn.

The Matter Lab reposted

Accelerated discovery (AI for science) is foundational to the Acceleration Consortium. In 2025-26, the AC: 🔬 Secured $34M+ in leveraged research funds 📚 Published 267 papers in top journals 🤖 Built 94 self-driving lab tools & platforms Learn more in our impact report: shorturl.at/hVBsI