Adam Lee 🇬🇧🇦🇺🌏♻️⚗🐨

#IUPAC2025 at the Photo Wall representing! 🇦🇺 🤠

📢 BRJ March 2026 Issue Out Now! ‣ Highlights: • Artificial peat mimicking natural humification • Monochromatic light boosting biohydrogen • Pd-catalyzed furfural → furan • Biomass-derived CoMo for thiophene hydrodesulfurization Read free at:📖 biofueljournal.com

Chemical Research Society of India has conferred the Bronze medal for our scientific contribution. Thanks to all the supporters, collaborators and stakeholders. @ChemResSocIndia @ICTMumbai1933 @ugc_india

📢 BRJ December 2025 Issue Out Now! ‣ Highlights: • Biomass pelletization for better saccharification • Poplar biorefinery for furfural & butanol • Transcription-factor-engineered C. glabrata for α-KG • CRISPRi boosting PHB from crude glycerol 📖 biofueljournal.com

Do you remember when you joined X? I do! #MyXAnniversary

Elemental Abundance of Earth This is quite an important chart to understand the progress of humanity and maybe identify some things that we might have skipped over in our tech tree progress as a civilisation. Here’s how to read it. The X axis is all the naturally occurring elements ranked by their atom number (size of their nucleus). Small atoms on left, big atoms on right. The Y axis is logarithmic and tells you the abundance of each element in the Earth’s crust. Side note: All of these elements (other than hydrogen) were made inside an old star that existed before our sun and exploded in a supernova. Our planet is made from the ashes of a dead star. Now different planets that orbit our sun have different orbit distances and at diff distances there are different combinations of all these elements to form each planet. The chart below is what we rolled for Earth. Some stuff is very abundant, some stuff is rare. Now, if you think about this from a high level, the stuff that is very common, should be easily come by, it should be readily available to Earthlings, it should be relatively cheap. Stuff that is rarer should be harder to find, should be less available should naturally be more expensive. Stuff that is cheap should be very economic for us to use, we should therefore use more of that stuff and we should therefore get really good at working with that stuff. Stuff that is harder to find, stuff that is therefore relatively expensive would also be stuff that we use less (economic reasons), and therefore we get less good at using that stuff. This are very general rules that should apply to any civilisation on any planet at any stage of development. You might be able to estimate what sort of materials and technologies a civilisation on a far away planet would be more likely to develop based purely on the abundance profile of their home world. You can also look introspectively and check are the elements that are most abundant on Earth also the ones that form the cheapest materials in our economy? Did we get good with the thing easier to get good at on Earth? If not why not? Because maybe there’s a huge opportunity there. This suggests we are underachieving with our use of magnesium, titanium, calcium, sodium, sulphur. We are overachieving with our use of copper, lithium, silver, nitrogen, carbon, nickel, cobalt. Human civilisation is currently over optimised for extraction and use of rare conductive and catalytic elements, and we are under optimised for use of our abundant lightweight reactive elements. Why has this happened? 1. Economic inertia, iron and copper matured before titanium and magnesium. 2. Chemical accessibility, oxides and silicates demand high energy reduction. 3. Utility density, because of transport costs we value compact specific systems rather than bulk designs. 4. Historic lock in, infrastructure path dependence (steel - cu - al). If we were more rationally utilised… Structural alloys, we still use Fe and Al when Ti and Mg are superior and more abundant. Batteries, we use Li and Co when Na, Mg, Al should be more economic. Catalysis, we use Pt, Rd, Rh when we should be using Ti, Fe, Mo, W, nitrides. Electronics, we use Cu when Al and graphene should be more economical. There are myriad reasons for all these but it’s down to economic drivers and usually because we lack some technological step to bring the more abundant material to our economy more efficiently. Overall this suggests our entire process chemistry industry is not performing for humanity as well as it could. Although we have no alien civilisation for any frame of reference, so maybe we are doing well? But this exercise shows our economy and material use has massive economic opportunities to rebalance our economy’s material demands to reflect the resource wealth of Earth. We should think about this much more deeply as we look to develop other worlds and moons.

Discovering catalytic cooperativity with pooling and deconvolution Many catalytic reactions rely on more than one catalyst working together. In principle, pairing catalysts could unlock reactivity, efficiency, or selectivity far beyond what each can achieve alone. In practice, however, identifying which catalysts cooperate is prohibitively difficult: a panel of just 50 catalysts already contains more than a thousand possible pairs to test. Most of those pairs do nothing. A few may inhibit each other. And only a very small number may exhibit the kind of synergistic behavior synthetic chemists are looking for. Marcus H. Sak and coauthors present a strategy inspired by group testing that makes this search experimentally tractable. Instead of testing catalysts one pair at a time, they test pools of catalysts arranged according to a covering design, ensuring that each potential pair appears multiple times across different contexts. A simple “cooperativity score” reflects whether a pool performs better than expected from the individual catalysts alone. A second “deconvolution” step traces those performance boosts back to the specific catalyst pairs responsible. The authors first validate the approach on a known cooperative system in an enantioselective oxetane opening. They then apply it to a far more challenging case: a Pd-catalyzed decarbonylative Suzuki–Miyaura coupling. The result is striking. The workflow identifies ligand pairs that enable the reaction at lower temperature and lower Pd loading than state-of-the-art single-ligand systems—discoveries unlikely to have emerged from intuition or standard high-throughput screening. What’s compelling here is not just the chemistry, but the discovery method. By combining combinatorial pool structures with minimal assumptions and rapid experimental readout, the workflow efficiently explores landscapes that are too discontinuous and too sparse for conventional optimization or machine learning to navigate directly. It suggests a direction for discovery workflows where experimental design, not model complexity, is the main accelerator—and where synergy, rather than single-variable optimization, becomes the core target. This could reshape how we search for cooperative behavior in catalysis, materials, and biochemical systems: not by guessing, but by systematically letting the chemistry reveal where the cooperation actually happens. Paper: nature.com/articles/s4158…

After 4 years in writing, and 1.8 years in peer review, our work on porosity was just published in @ScienceMagazine. This paper has a rich life-story by now, which I will tell later. Right now, we're just happy :) science.org/doi/10.1126/sc… @TechnionLive

Darwinian evolution—now in chemistry Life, at its core, is a chemical process that learns through trial and error. Molecules replicate with small variations, and those that perform better at survival or function become dominant. This simple feedback loop—Darwinian evolution—is the engine behind every biological innovation on Earth. For decades, chemists have dreamed of recreating that same logic from scratch: not with DNA or enzymes, but with fully synthetic molecules that can evolve outside biology. The goal is profound—to uncover how life might have first emerged from inanimate matter, and to design chemical systems that adapt, learn, or improve their own functions. In a new study, Kai Liu and coauthors take a major step toward that goal. They create self-replicating molecular rings that spontaneously assemble into fibers. These fibers can recruit a photocatalytic dye (Thioflavin T), which under light generates singlet oxygen—a reactive species that helps make the very building blocks the fibers need to grow. In other words, the replicators catalyze their own survival. The team then places this chemistry in a flow reactor, where new material is continuously supplied while old products are removed. In this out-of-equilibrium environment, natural selection begins to operate: replicators that are better photocatalysts gradually dominate the population, while less efficient ones fade away. Even subtle structural differences matter—mutants that produce singlet oxygen more effectively gain an evolutionary edge. High-speed atomic force microscopy reveals this process at work, capturing in real time how small reservoirs of precursor material form and are consumed on the fiber surfaces as they grow. The result is the first demonstration of Darwinian evolution for a functional trait—here, photocatalysis—in a completely synthetic molecular system. Overall, this work unites self-replication, catalysis, and selection in one experiment, bridging chemistry and biology. Paper: nature.com/articles/s4192…

Stop Forced Redundancies at QUT's Faculty of Science - Sign the Petition! c.org/wQSRfWgvWM via @ChangeAUS

Our lab recently discussed the impactful career of Donna Blackmond @scrippsresearch. What’s your favorite paper from the Blackmond Lab? Here are some papers selected by our lab:

In this Account, I summarize my PhD research with @AizenbergLab @hseas on how colloidal templating can afford a modularly versatile and robustly stable catalytic platform to elucidate clear structure-property relationships pubs.acs.org/doi/full/10.10…

Susumu Kitagawa, Richard Robson and Omar M. Yaghi have been awarded the 2025 #NobelPrize in Chemistry for the development of a new type of molecular architecture. In 1989, chemistry laureate Richard Robson tested utilising the inherent properties of atoms in a new way. He combined positively charged copper ions with a four-armed molecule; this had a chemical group that was attracted to copper ions at the end of each arm. When they were combined, they bonded to form a well-ordered, spacious crystal. It was like a diamond filled with innumerable cavities.

Still much to be done to fix university governance but nonetheless a huge win for the thousands of NTEU members who have campaigned tirelessly to build better unis. abc.net.au/news/2025-09-1…

SurFF: A foundation model for predicting catalyst surfaces Most industrial chemical reactions take place on the surfaces of solid materials. Catalysts are crystals, and in theory they can expose many different surfaces (or “facets”). But in reality, only a few show up when the crystal grows—and those are the ones that determine how well the catalyst works. Figuring out which surfaces appear is usually slow and expensive, involving either density functional theory (DFT) simulations or high-resolution microscopy. Jun Yin and coauthors present SurFF, a foundation model trained to predict which crystal surfaces will actually be exposed. Built on a huge dataset of intermetallic surfaces (12,000+ surfaces, 340k DFT calculations), it uses a machine-learning force field to mimic DFT accuracy at 100,000× faster speed. It then applies a geometry method called Wulff construction to estimate the shapes and surfaces of nanoparticles. SurFF matches DFT accuracy within a few meV/Ų and even aligns with experimental observations. The team used it to generate surface exposure predictions for more than 6,000 intermetallic crystals. Importantly, the model can also be fine-tuned with just a small amount of new data to handle new material families. The big shift here: catalyst discovery usually focuses only on activity (how reactive a surface is). SurFF adds exposure (whether that surface will actually exist in the real material) into the equation. That means faster, more realistic catalyst screening—turning the search from “what could work” into “what will actually show up. Paper: nature.com/articles/s4358…

Research is crucial for innovation & solving the big problems we’re facing. If we’re serious about building an economy for the future & ‘future made in Australia’ we have to better fund the CSIRO & university research. I’ve been pushing Gov for 3yrs & will continue to do so.

We invite you to read the Top Cited papers in 2023-2024 in section “Nanostructured Catalysts” 👉Find these papers at: mdpi.com/about/announce… 👉Find section at: mdpi.com/journal/cataly…

A potentially carrier defining paper is out in @angew_chem Novit! We show how to simulate supported nanoparticle catalysts with 1-5 nm in diameter under experimental conditions in quantitative agreement with benchmark microcalorimetric measurements onlinelibrary.wiley.com/doi/10.1002/an…

🚨Just out in @angew_chem: cross couplings fuel synthesis, but C–S bonds over #SACs were uncharted territory, until now. Here, the first SAC for C–S coupling: selective, recyclable & thiol-poisoning resistant.👏 @GazisTheo, @PalitShilpa & coauthors! Link: shorturl.at/w9FpX