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NanoManufacturing

Michael De Volder, Engineering Department - IfM
 

Wed 12 Feb 13:00: Short-term, high-resolution sea ice forecasting with diffusion model ensembles

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 15:27
Short-term, high-resolution sea ice forecasting with diffusion model ensembles

Sea ice plays a key role in Earth’s climate system and exhibits significant seasonal variability as it advances and retreats across the Arctic and Antarctic every year. The production of sea ice forecasts provides great scientific and practical value to stakeholders across the polar regions, informing shipping, conservation, logistics, and the daily lives of inhabitants of local communities. Machine learning offers a promising means by which to develop such forecasts, capturing the nonlinear dynamics and subtle spatiotemporal patterns at play as effectively—if not more effectively—than conventional physics-based models. In particular, the ability of deep generative models to produce probabilistic forecasts which acknowledge the inherent stochasticity of sea ice processes and represent uncertainty by design make them a sensible choice for the task of sea ice forecasting. Diffusion models, a class of deep generative models, present a strong option given their state-of-the-art performance on computer vision tasks and their strong track record when adapted to spatiotemporal modelling tasks in weather and climate domains. In this talk, I will present preliminary results from a IceNet-like [1] diffusion model trained to autoregressively forecast daily, 6.25 km resolution sea ice concentration in the Bellingshausen Sea along the Antarctic Peninsula. I will also touch on the downstream applications for these forecasts, from conservation to marine route planning, which are under development at the British Antarctic Survey (BAS). I welcome ideas and suggestions for improvement and look forward to discussing opportunities for collaboration within and beyond BAS .

[1] Andersson, Tom R., et al. “Seasonal Arctic sea ice forecasting with probabilistic deep learning.” Nature communications 12.1 (2021): 5124. https://www.nature.com/articles/s41467-021-25257-4

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Thu 13 Mar 16:00: Algorithmic stability for regression and classification

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 14:41
Algorithmic stability for regression and classification

In a supervised learning setting, a model fitting algorithm is unstable if small perturbations to the input (the training data) can often lead to large perturbations in the output (say, predictions returned by the fitted model). Algorithmic stability is a desirable property with many important implications such as generalization and robustness, but testing the stability property empirically is known to be impossible in the setting of complex black-box models. In this work, we establish that bagging any black-box regression algorithm automatically ensures that stability holds, with no assumptions on the algorithm or the data. Furthermore, we construct a new framework for defining stability in the context of classification, and show that using bagging to estimate our uncertainty about the output label will again allow stability guarantees for any black-box model. This work is joint with Jake Soloff and Rebecca Willett.

Evaluating a black-box algorithm: stability, risk, and model comparisons

When we run a complex algorithm on real data, it is standard to use a holdout set, or a cross-validation strategy, to evaluate its behavior and performance. When we do so, are we learning information about the algorithm itself, or only about the particular fitted model(s) that this particular data set produced? In this talk, we will establish fundamental hardness results on the problem of empirically evaluating properties of a black-box algorithm, such as its stability and its average risk, in the distribution-free setting. This work is joint with Yuetian Luo and Byol Kim.

A wine reception in the Central Core will follow this lecture

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Fri 14 Feb 16:00: Flavour Physics at the Intensity Frontier

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 14:14
Flavour Physics at the Intensity Frontier

Flavour physics and CP violation provide powerful probes for physics beyond the Standard Model that are sensitive to very high energy scales beyond direct detection experiments. The construction of the unitarity triangle provides the ultimate probe for flavoured new physics. We discuss current highlights of this program in the sectors of beauty, charm and strange quark decays.

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Wed 12 Feb 16:30: Tensor product functoriality via p-adic propagation

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 13:29
Tensor product functoriality via p-adic propagation

Tensor product functoriality predicts that the tensor product of two automorphic Galois representations should be automorphic. We will motivate this statement, and describe forthcoming work establishing this conjecture in some cases.

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Fri 21 Feb 16:00: Title to be confirmed

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 13:04
Title to be confirmed

Abstract not available

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Fri 21 Mar 16:00: Title to be confirmed

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 13:04
Title to be confirmed

Abstract not available

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Tue 11 Feb 18:30: Enterprise Tuesday: Quantum – ready or not

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 12:54
Enterprise Tuesday: Quantum – ready or not

Quantum Computing is set to redefine the limits of what we can achieve. It is predicted to have an impact sooner rather than later and now is the time to think about its impact on your start up or organisation.

This talk is chaired by Ilyas Khan, Founder and Chief Product Officer of Quantinuum. Our guest panellists are Nick Fishwick, Non-Executive Director of the HM Courts & Tribunal Service; Phil O’Donovan, Cambridge Angel; Dr Jeremy Sosabowski, Co-founder Executive Director, AlgoDynamix; and Zuzanna Kosobudzka, Engineering PhD, Cambridge University Sustainable Aviation Fuels.

Register to book your place > https://www.jbs.cam.ac.uk/events/enterprise-tuesday-quantum-ready-or-not/

Surpassing the capabilities of traditional computers, the remarkable potential of quantum computing lies in performing highly complex calculations at unprecedented speeds, paving the way for groundbreaking advancements across various sectors that will transform industries significantly.

In the healthcare field, it may accelerate the creation of innovative treatments and enhance personalised medicine. In manufacturing, it could optimise supply chains and boost production efficiency. In the energy sector, it might hasten the progress of fusion power development. And in finance, it has the potential to introduce new financial products and services while improving risk management and trading strategy models.

Quantum computing holds the promise to unlock discoveries we’ve only imagined. Join our expert panel to help you get a head start on thinking about how you will be impacted as they delve into the multi-faceted possibilities of this cutting-edge technology and the hurdles that might arise.

Register now and get ready for an evening filled with insightful conversations and networking opportunities within the Cambridge community.

Enterprise Tuesday is managed by Cambridge Judge Entrepreneurship Centre. It is open to all members of the University of Cambridge, aspiring entrepreneurs and members of the business community. The talks are free to attend, enable audiences to learn from experienced entrepreneurs and experts, and to build relationships with a high value group of like-minded individuals through the networking. Registration is essential.

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Wed 19 Feb 14:30: Unraveling Water’s Behavior in Anisotropic Environments

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 12:02
Unraveling Water’s Behavior in Anisotropic Environments

The structure and reactivity of water in anisotropic environments, such as at interfaces or under the influence of electric fields, can differ significantly from those observed in bulk. Understanding these differences is crucial for gaining insights into various atmospheric and electrochemical processes that impact our society.

In the first part of my talk, I will discuss how ions organize at the water/air interface and demonstrate that the conventional electric double-layer model fails to provide a complete microscopic picture of these interfaces [1,2]. Using first-principles simulations, I will show that the surface of common electrolyte solutions is stratified into two distinct water layers: one depleted of ions and the other enriched with them.

Next, I will present our recent investigation into water autodissociation [3]. We employ the modern theory of polarization to perform periodic ab initio molecular dynamics simulations of water under external electric fields. Our simulations reveal that the enhancement of water dissociation in these conditions is primarily driven by entropic effects rather than enthalpic ones, as is normally assumed. Finally, I will discuss how these findings may provide crucial insights into recent kinetic measurements of the hydrogen evolution reaction (HER) across various electrochemical systems [4].

[1] Y. Litman, J. Lan, Y Nagata, D. M. Wilkins, J. Phys. Chem. Lett. 14, 8175-8182 (2023) [2] Y. Litman, K-Y. Chiang, T. Seki, Y. Nagata, M. Bonn, Nat. Chem. (2024) 16, 644–650 (2024) [3] Y. Litman, A. Michaelides (in preparation) [4] J. M. Gisbert-González, C. G. Rodellar, J. Druce, E. Ortega, B. Roldan Cuenya, S. Z. Oener, J. Am. Chem. Soc (in press, DOI : 10.1021/jacs.4c18638)

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Bio-inspired proton relay for promoting continuous 5-hydroxymethylfurfural electrooxidation in a flowing system

http://feeds.rsc.org/rss/ee - Mon, 10/02/2025 - 10:43

Energy Environ. Sci., 2025, Advance Article
DOI: 10.1039/D4EE05745G, PaperDexin Chen, Wenlong Li, Junbo Liu, Licheng Sun
A ligand-modified catalyst, Ni(OH)2–TPA, is synthesized for efficient HMF oxidation, wherein the uncoordinated carboxylate functions as the proton relay center, enabling continuous HMF oxidation in a flowing system.
To cite this article before page numbers are assigned, use the DOI form of citation above.
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Thu 06 Mar 11:00: Learning to Interact in Real-World Multiagent Systems

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 10:19
Learning to Interact in Real-World Multiagent Systems

From autonomous robots to digital assistants, the future of AI is inherently multiagent—where systems must learn, adapt, and strategize in dynamic environments. How do robots collaborate and compete to outmaneuver opponents in soccer and push the limits in quadrotor racing? How can AI help millions of users find the best routes every day? This talk explores the role of reinforcement learning in such settings, where cooperation and competition shape intelligent behavior. We will dive into robotics applications like bipedal robot soccer and quadrotor racing, alongside large-scale digital systems such as Google Maps. By highlighting key challenges and breakthroughs, we will uncover how multiagent systems are shaping the next generation of autonomy.

Bio: Markus Wulfmeier is a researcher in machine learning and robotics at Google DeepMind with a focus on fundamental and applied research on reinforcement, imitation, and transfer learning. His work aims at efficiently scalable algorithms across a variety of real-world applications including robotics, navigation, and language modelling. Markus was a postdoctoral research scientist at the Oxford Robotics Institute and a member of Oxford University’s New College where he completed his PhD. Over the years, he has held visiting scholar positions with UC Berkeley, MIT , and ETH . His work received best paper awards including IROS and GVSETS and was covered in the press including 60 Minutes, The Verge, MIT News, Wired, BBC News, New Scientist, and Popular Science.

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Wed 26 Feb 14:30: Probing biomolecular phase separation through multiscale computer simulations.

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 09:57
Probing biomolecular phase separation through multiscale computer simulations.

Biomolecular condensates play crucial roles in cellular organisation, regulating diverse biological functions, as well as contributing to disease pathologies when phase separation is dysregulated. However, the physicochemical mechanisms by which they are formed and regulated are still not well understood, especially in the complex environment inside cells consisting of thousands of different components. Computer simulations have emerged as powerful tools to investigate phase transitions in these systems. In this talk, we will discuss how coarse-grained molecular-dynamics simulations at different resolutions can probe the molecular mechanisms governing biomolecular phase separation across different systems, as well as guide the design of proteins that can give rise to condensates with specific properties.

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Wed 12 Feb 11:00: Diffusion Models Beyond Mean Prediction Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.

http://talks.cam.ac.uk/show/rss/5408 - Mon, 10/02/2025 - 09:56
Diffusion Models Beyond Mean Prediction

Traditional diffusion models are typically trained to predict only the mean of the denoised distribution given a noisy sample. But what if we go beyond the mean? This talk explores how incorporating additional information—such as predicting the covariance of the denoised distribution—can significantly accelerate sampling and improve density estimation. We’ll dive into different techniques for covariance prediction, their theoretical connection, and practical benefits for more efficient and expressive generative modeling.

Teams link available upon request (it is sent out on our mailing list, eng-mlg-rcc [at] lists.cam.ac.uk). Sign up to our mailing list for easier reminders via lists.cam.ac.uk.

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Intrinsic Structural and Coordination Chemistry Insights of Li Salts in Rechargeable Lithium Batteries

Here, the development trend, solvation structures, interfacial chemistry, and latest progress of lithium salts are discussed from the perspectives of coordination chemistry and structural design, hoping to provide inspiration for the on-demand design/customization of lithium salts, thereby promoting the development of high-performance batteries.


Abstract

Lithium batteries, favored for their high energy density and long lifespan, are staples in electric vehicles, portable electronics, and aerospace. A key component, Li salts, aids lithium ion migration and electrode protection, significantly impacting battery performance. Developing an ideal Li salt, balancing stability, solubility, dissociation, solvation, and eco-friendliness, remains challenging. Given the scarcity of relevant reviews, it is endeavored here to present a novel perspective on Li salt chemistry, offering a concise roadmap for future designs and innovations. It is delved into the trends, opportunities, design principles, and evaluation methodologies related to Li salt chemistry, with a particular emphasis on organic anionic compositions. Furthermore, the latest and most representative organic Li salts from their intrinsic structure and coordination chemistry, highlighting their unique features and contributions are organized and presented. Finally, a visionary outlook is articulated for this field, exploring avenues, such as customizing Li salts for specific applications, synthesizing Li salts on demand, and discussing the potential of F-free Li salts alongside with their electrochemical window challenges. Here it is served as a strategic compass, addressing the shortcomings of existing reviews and guiding the design of functionalized Li salts.

A Printed Microscopic Universal Gradient Interface for Super Stretchable Strain‐Insensitive Bioelectronics

Stretchable bioelectronics conforming to dynamic body surfaces enable high-fidelity physiological monitoring but often suffer from motion artifacts. All-printed strain-insensitive bioelectronics are presented using a universal gradient interface (UGI) created via aerosol-based multi-materials printing (AMMP). The UGI minimizes local strain changes under 180% stretch, supporting artifact-free sensors for health monitoring and advancing wearable and implantable bioelectronics for personalized healthcare.


Abstract

Stretchable electronics capable of conforming to nonplanar and dynamic human body surfaces are central for creating implantable and on-skin devices for high-fidelity monitoring of diverse physiological signals. While various strategies have been developed to produce stretchable devices, the signals collected from such devices are often highly sensitive to local strain, resulting in inevitable convolution with surface strain-induced motion artifacts that are difficult to distinguish from intrinsic physiological signals. Here all-printed super stretchable strain-insensitive bioelectronics using a unique universal gradient interface (UGI) are reported to bridge the gap between soft biomaterials and stiff electronic materials. Leveraging a versatile aerosol-based multi-materials printing technique that allows precise spatial control over the local stiffnesses with submicron resolution, the UGI enables strain-insensitive electronic devices with negligible resistivity changes under a 180% uniaxial stretch ratio. Various stretchable devices are directly printed on the UGI for on-skin health monitoring with high signal quality and near-perfect immunity to motion artifacts, including semiconductor-based photodetectors for sensing blood oxygen saturation levels and metal-based temperature sensors. The concept in this work will significantly simplify the fabrication and accelerate the development of a broad range of wearable and implantable bioelectronics for real-time health monitoring and personalized therapeutics.

A DNA Nanopatch‐Bacteriophage System Targeting Streptococcus Gallolyticus for Inflammatory Bowel Disease Treatment and Colorectal Cancer Prevention

Herein, this work constructs a novel DNA nanopatch (DNPs)-modified bacteriophages (P-Sg) therapeutic platform (DNPs@P) for precise, gut-targeted therapy that potently reduces inflammation and prevents the colonic inflammation-to-carcinoma transition. To protect DNPs@P from the harsh gastrointestinal environment, this work encapsulates them with an enteric polymer acrylic resin (L100-55) (DNPs@P-L). Upon oral administration, the L100-55, ensures their safe passage through the stomach and release in the intestine. Then P-Sg target and lyse pathogenic bacteria at inflammatory sites, delivering DNPs precisely to affected regions, which can scavenge ROS in the inflammatory site.


Abstract

Persistent inflammation in inflammatory bowel disease (IBD) increases Streptococcus gallolyticus (Sg) colonization, increasing the risk of colorectal cancer progression via the Sg-activated cyclooxygenase-2 (COX-2) pathway and β-catenin upregulation. This study presents Sg-specific bacteriophages modified with DNA nanopatches (DNPs@P) designed to treat IBD and prevent Sg-induced malignancy. The DNPs are composed of DNA origami nanosheets and phage capture strands. The DNPs scavenge reactive oxygen species, enhancing the therapeutic efficacy of the phages while targeting and lysing pathogenic bacteria. Coating with an enteric polymer, DNPs@P ensures effective delivery in the gastrointestinal tract. These findings demonstrate significant restoration of colonic length, reduced inflammation, and improved gut microbiota diversity compared with current clinical treatments. Additionally, DNPs@P effectively prevents colonic tumourigenesis in mouse models. This approach presents a promising strategy for treating gastrointestinal diseases by remodeling the gut microenvironment, addressing a critical gap in current therapies.

Dual‐Descriptor Tailoring: Rational Solvent Molecule Tuning Enables High‐Voltage Li‐Ion Batteries

A dual-descriptor approach is developed to design high-voltage electrolytes, combining Mulliken charge and Laplacian bond order to identify ideal solvents. Acetonitrile (AN) stabilizes meta-stable transition metal atoms and mitigates lattice oxygen instability at the cathode-electrolyte interface. This strategy enables precise control of interfacial stability, advancing high-voltage lithium-ion batteries with a versatile and adaptive framework.


Abstract

Electrolyte engineering to enhance the cathode-electrolyte interface stability is widely recognized as a promising strategy for achieving high-voltage lithium-ion batteries, which are currently hindered by the meta-stable surface of lithium-rich layered oxides. Despite significant progress in electrolyte development, clear design guidelines for high-voltage electrolytes remain lacking, making solvent selection unpredictable. Here, a dual-descriptor tailoring concept based on Mulliken charge (adsorption) and Laplacian bond order (antioxidation) to identify ideal solvent molecules for high-voltage electrolytes is proposed. This concept stabilizes meta-stable transition metal atoms in surface tetrahedral interstices through interactions between bottom solvent molecules and cathode dangling bonds. Acetonitrile (AN) is eventually selected as a promising bottom solvent that interacts strongly with unstable surface bonds, improving interfacial stability. Consequently, the prepared 0.6 Ah graphite||LCO pouch cell using AN-based electrolyte maintained a remarkable 80% capacity retention after 900 cycles with an average Coulombic efficiency of 99.92% at high cut-off voltage. This work revisits the interfacial stability mechanism across different electrolyte classes, where strong solvent adsorption mitigates the instability of the meta-stable Co spin state, reduces surface band overlap, and alleviates the instability of lattice oxygen at the interface. This dual-descriptor-guided design opens a new avenue for high-voltage Li-ion batteries is believed.

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4 January 2021

We are seeking to hire a research assistant to work on carbon nanotube based microdevices. More information is available here: www.jobs.cam.ac.uk/job/28202/

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4 January 2021

We are seeking to hire a postdoc researcher to work on the structuring of Li-ion battery electrodes. More information is available here: www.jobs.cam.ac.uk/job/28197/