John Ward

🚀 We’re recruiting a postdoc to join a @ukcatalysishub.bsky.social project at the @liverpooluni.bsky.social. Collaboration with @donnablack.bsky.social, @virtualatoms.bsky.social, @astrazeneca.bsky.social, @glaxosmithkline.bsky.social, @aichemyhub.bsky.social. Please share or apply if interested

Interesting paper on superhydrophobic HOFs for selective ethene/ethane separation: pubs.rsc.org/en/Content/A.... We used the same molecule/phase last year to create a superhydrophobic HOF for selective CO2/H2O separation: pubs.acs.org/doi/10.1021/...

Decoding the Nested, Multicycle Mechanism of Ni-Catalyzed Redox-Neutral Cross-Coupling through Temperature Scanning Reaction Calorimetry Catalytic reactions involving multiple cycles are common in many key organic transformations. We report a detailed mechanistic analysis of one such network of “nested” cycles, the Ni-catalyzed cross-c...

Out today on JACS ASAP - Baran/Blackmond collaboration demonstrating the power of temperature scanning reactions in mechanistic studies of multicycle catalytic systems. Fantastic work by @dacagan.bsky.social and Aron Peter and Phil who is still over on the other place.

pubs.acs.org/doi/full/10....

Our research showcased on the European stage and major investments for global impact Liverpool has been named one of three finalists for the European Capital of Innovation Awards, and we are proud to be a cornerstone of the bid by showcasing world-leading research and innovation. We’r...

@liverpooluni.bsky.social research news 🌍

🏆 European Capital of Innovation finalist
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🧪 £100M AI Materials Hub for Innovation
💡 Enterprise Report 2024–25
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🎓 Research Fellowships open
📊 Global subject success

👉 www.linkedin.com/pulse/our-re...

Decoding the Nested, Multi-Cycle Mechanism of Ni-Catalyzed Redox Neutral Cross-Coupling Through Temperature Scanning Reaction Calorimetry Catalytic reactions involving multiple cycles are common in many key organic transformations. We report a detailed mechanistic analysis of one such network of “nested” cycles, the Ni-catalyzed cross-c...

New on ChemRxiv!

chemrxiv.org/engage/chemr...

A digital tool for liquid–liquid extraction process design Aqueous liquid–liquid extractions are crucial for purifying compounds and removing impurities in the pharmaceutical industry. However, the extensive solvent space involved in such operations highlight...

AstraZeneca scientists have developed an in-house web app that streamlines the design of LLE lab experimentation

#ChemSky

pubs.rsc.org/en/content/a...

Accelerated Discovery of Energy Transfer-Catalyzed Dearomative Cycloadditions through a Data-Driven Three-Layer Screening Strategy Visible-light-mediated energy transfer (EnT) photocatalysis has emerged as a highly appealing strategy for converting planar (hetero)arenes into complex, medicinally relevant, three-dimensional (3D) a...

🚀Unlocking new frontiers in photocatalysis with AI!
Our latest @jacs.acspublications.org paper presents a 3️⃣-layer screening strategy for accelerated discovery of EnT-catalyzed dearomative cycloadditions! ✨
Check this out: pubs.acs.org/doi/10.1021/...

#Photocatalysis #AIforScience #OrganicChemistry

Just out, "Selective CO2 Adsorption in Ultrahydrophobic Molecular Pyrene Frameworks by Computational Design" pubs.acs.org/doi/10.1021/.... Sam Harding was the student who led this. MeTBAP-α is one of the most hydrophobic porous solids reported, and this came out of a priori computational design 🚫💧

Being a first generation university graduate, the impact on a career in science Being in the first generation to access Higher Education (First Gen) is a barrier to academic success. First Gens face difficulties transitioning into, completing, and attaining competitive grades in ...

New study from the Women in Supramolecular Chemistry (WISC) revealing the unique challenges resulting from being First Gen (first generation of a family to access Higher Education) in science and showing how these persist at every stage of a career in academia:
pubs.rsc.org/en/content/a...

A meta-learning approach for selectivity prediction in asymmetric catalysis - Nature Communications The need for large amount of experimental data can present a bottleneck for implementing machine learning models. Here, the authors propose a meta-learning workflow that can harness the literature-der...

Singh & Hernández-Lobato introduce meta-learning for predicting enantioselective outcomes in catalytic hydrogenations. Their approach quickly adapts to new reactions—often outdoing standard ML—using only minimal data. A leap forward in asymmetric catalysis. www.nature.com/articles/s41...

Automation accelerated screening of H-bond-rich iridium photosensitisers for hydrogen generation In the pursuit of a stable hydrogen evolution photosensitiser, we demonstrate the incorporation of a series of our H-bond rich guanidine-styled iridium(iii) complexes into a catalytic system. Using au...

Delighted to share the first publication from our group at @livunisps.bsky.social in collaboration with @barryblight.bsky.social! In this work, we combine two of our favourite things: #automation and #photocatalysis! 🤖💡🧪 Huge congrats to Harri Jones and Chris Bradshaw 🎉 shorturl.at/A67BG

Automation accelerated screening of H-bond-rich iridium photosensitisers for hydrogen generation In the pursuit of a stable hydrogen evolution photosensitiser, we demonstrate the incorporation of a series of our H-bond rich guanidine-styled iridium(iii) complexes into a catalytic system. Using au...

Excited to share our latest paper in collaboration with @jwward.bsky.social @uliverpoolMIF using the Chemspeed automated reaction platform to screen several photocatalysts and many reaction conditions for H2 production. Great job by Harri and Chris on this work! pubs.rsc.org/en/Content/A...

Discovering organic reactions with a machine-learning-powered deciphering of tera-scale mass spectrometry data - Nature Communications Mass spectrometry generates vast amounts of data in chemistry labs. Here, authors developed a machine learning-driven search engine that analyzes archived data to discover chemical reactions without p...

Kozlov et al. combined machine learning with terabyte-scale mass spectrometry data, uncovering unexpected reaction pathways hidden in archived experiments. Their approach confirms that unexamined data can yield new insights without extra lab work. www.nature.com/articles/s41...

Computational tools for the prediction of site- and regioselectivity of organic reactions The regio- and site-selectivity of organic reactions is one of the most important aspects when it comes to synthesis planning. Due to that, massive research efforts were invested into computational mo...

Really grateful to be part of this review on predictions of selectivity, driven by @lukasmsigmund.bsky.social ! doi.org/10.1039/D5SC...

Digital Transformation of Chemical Analysis for Sustainable Materials Development at University of Liverpool on FindAPhD.com PhD Project - Digital Transformation of Chemical Analysis for Sustainable Materials Development at University of Liverpool, listed on FindAPhD.com

🚀 #PhD studentship available to work with me and Gabriella Pizzuto on the #digital transformation of chemical analysis for #sustainable materials development @livunisps.bsky.social in collaboration with @unileveruki.bsky.social, starting October 2025 🧪🤖 Deadline 30th April tinyurl.com/yf38kshs

Using Gels to Encapsulate Reactive Low-Valent Platinum Group Metals for Applications in Catalysis and Synthesis at University of York on FindAPhD.com PhD Project - Using Gels to Encapsulate Reactive Low-Valent Platinum Group Metals for Applications in Catalysis and Synthesis at University of York, listed on FindAPhD.com

Four-year PhD available in my lab, funded by Johnson Matthey/EPSRC with joint supervision from Prof Ian Fairlamb (also York).
Come and explore using supramolecular gels in precious metal catalysis and create innovative, sustainable, ways of doing organic synthesis.
www.findaphd.com/phds/project...

@samblau.bsky.social, Brett Savoie (Notre Dame), and I are organizing a symposium for @amerchemsociety.bsky.social Fall 2025 called "Chemical Reaction Networks, Retrosynthesis, and Reaction Prediction" under @acscomp.bsky.social.

#reactionnetwork #CRN #retrosynthesis 🧪 ⚗️ #CompChem

Stevens et al. combined machine learning, high-throughput experimentation, and Bayesian optimization to rapidly optimize a nickel-catalyzed borylation. They achieved >99% yield and lower costs in just 120 experiments. pubs.acs.org/doi/full/10....

The Devil Is in the Details: Pitfalls and Ambiguities in the Analysis of X-ray Powder Diffraction Data of 2D Covalent Organic Frameworks X-ray powder diffraction (XRPD) data of covalent organic frameworks (COFs) seem to be simple and apparently do not contain a lot of structural information, as these patterns usually do not show more t...

If you are working with #cof and #pxrd check out Sam's paper on pitfalls when analysing pxrd patterns #chemsky
pubs.acs.org/doi/10.1021/...

Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While ea...

new preprint on chemical synthesis ML models

- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!

Feedback welcome!

arxiv.org/abs/2412.05269