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Athina Anastasaki, materials chemist, Swiss Federal Institute of Technology (ETH), Zurich

Credit: Courtesy of Athina Anastasaki
Athina Anastasaki
“With increased focus from academic and industry researchers on developing a sustainable and circular polymer economy, many of the highly selective strategies used in organic chemistry may find applications in chemical recycling. Developing new methods to selectively break down waste polymeric materials into desirable raw materials could realize the true potential of plastic waste as a feedstock. Advances in the fields of mechanochemistry, photochemistry, and organometallic catalysis show particular promise in achieving this objective. Effectively utilizing the large amounts of polyethylene and polypropylene in waste streams in an economically viable manner is the ultimate goal of these efforts.”
Connor W. Coley, computational chemist, Massachusetts Institute of Technology

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Connor Coley
“We’ll continue to see increased accessibility and routine adoption of [artificial intelligence] techniques in chemistry, in particular Bayesian optimization for identifying reaction conditions and the use of neural network potentials as surrogates for quantum mechanical modeling. There will be newer proofs-of-concept tackling more ambitious tasks like anticipating the selectivity of C–H activation and proposing novel transformations entirely. A recognition that AI is a pervasive part of the molecular discovery toolkit might obsolesce terms like ‘AI-discovered drug,’ which often only reinforce prior support or distaste for AI techniques. Greater focus will be placed on molecular evaluation than design. For example, we may see a new wave of structure-based drug-design techniques for binding affinity prediction that build on the extensive advances in deep learning for protein structure prediction and ligand binding-pose prediction.”
Roxanne Kieltyka, supramolecular chemist, Leiden University

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Roxanne Kieltyka
“As knowledge of living systems and tools to modify them continue to increase, we, as chemists, are provided with new opportunities to create soft materials that can interact with them and steer their function for applications spanning healthcare to the environment. This is made possible by the rapidly growing number of methods to control the synthesis of polymers with advanced properties and functions, their characterization, and fabrication using 3D printing technologies. Reversible covalent or non-covalent bonding chemistries that confer dynamic properties to these materials can unlock complex mechanical characteristics and even architectures found in cells and native tissues. For example, hydrogel designs that mimic the materials of life can influence a wide range of cell behaviors to impact how we understand, diagnose, and treat diseases. I expect that in 2024 we will see exciting examples of how far we can push these dynamic materials to emulate and leverage biological matter in ways that challenge what it means to be synthetic.”
Stafford Sheehan, chief technology officer, Air Company

Credit: Courtesy of Stafford Sheehan
Stafford Sheehan
“Breakthroughs in green chemistry will set the tone in a sustainable revolution for decarbonization. Technologies that sustainably produce molecules that are traditionally made by fossil fuels are at the forefront. In 2024, we’ll see further investment and advances in low-carbon hydrogen production, sustainable fuels, industrial electrification, and more, with a deeper understanding of next-generation catalysts and novel processing methods. These latest advancements will enhance the efficiency and impact of the energy industry, enabling humanity to grow without the resource and emissions limitations that come with using fossil fuels.”
Michael Snyder, genomicist and geneticist, Stanford University

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Michael Snyder
“2024 will continue the era of ‘big data,’ both in collection and analysis. The cost of genome sequencing will likely reach $100 (for reagents and supplies) and the scaling of other omics, particularly proteomics and metabolomics, will rise considerably. One area of particular emphasis—single-cell spatial omics, which presently is confined primarily to RNA and protein—will also continue to rise. Machine learning and artificial intelligence, which exploded in 2023, will become even more commonplace in 2024 and applied to large heterogeneous data types. These activities will lead to a greater depth of understanding of biological systems and human disease.”
Charlotte Vogt, spectroscopist, Technion—Israel Institute of Technology

Credit: Courtesy of Charlotte Vogt
Charlotte Vogt
“Catalysts, vital for a third of the global [gross domestic product], are often highly complex—yet we still generally rely on trial-and-error for their synthesis. Rational design of catalysts has been a goal for many years, and the wide availability now of lab automation and artificial intelligence brings that goal ever closer. Lab work that took us months a few years ago, we can now do in less than a day. I hope that in 2024, we will make leaps in our understanding due to the broader accessibility of such tools. This, alongside creativity and cross-disciplinary thinking, which could be sparked by the ease of gathering information with these tools, is absolutely necessary to drive novel processes facilitating the remediation of anthropogenic climate change, such as mass-scale (tens of [giga–metric tons per year]) carbon capture and storage, for which current solutions like direct air capture cannot effectively contribute.”
Note: All responses were sent via email.
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