Chemical Kinetics seminars

Reaction–diffusion theory explains how molecular diffusion and reaction rates can set the scale of biological patterns. Yet structures such as the nucleus and mitotic spindle scale with the cell containing them, suggesting a mechanism that measures cell size. Jané Kondev presents mathematical models of chemical networks capable of this measurement and compares their predictions with quantitative experiments. The talk uses cell-size sensing to show how physical reasoning, explicit mathematical models, and measurement can resolve questions in cell biology.

Mechanochemical recycling uses collisions in ball mills to create reactive environments within solid plastic feedstocks. Carsten Sievers examines how these environments enable depolymerization and where they impose kinetic and thermodynamic limits. For PET milled with sodium hydroxide, reaction rates depend on interfaces between reactants. Raman microscopy, focused-ion-beam transmission electron microscopy, small-angle X-ray scattering and material-point simulations characterize individual impact craters. Amorphous regions react above a minimum impact force, whereas crystalline regions require impacts exceeding PET’s yield point. Milling polystyrene produces styrene at steady rate and selectivity alongside minor products, including oxygenates. Removing monomer continuously prevents repolymerization, while thermodynamic analysis identifies limits on olefin release from chain-end radicals and motivates more energetic, longer-lived reaction environments. Coupling chain cleavage to hydrogenation or oxidation provides another driving force. An example uses hydrogen peroxide and an iron-oxide catalyst during polyethylene milling, producing oxidation at positions along the backbone followed by carbon-carbon bond cleavage.

Light-driven synthesis offers opportunities for more sustainable chemistry, but effective reaction design depends on understanding interactions among photons, substrates and catalysts. This seminar combines spectroscopy with kinetic analysis to resolve those mechanisms. It shows how such evidence can guide more efficient transformations and extend the range of molecules accessible through photochemical synthesis.

Living systems select one molecular handedness, making the origin of homochirality a central problem in understanding how life began. David Lacoste examines how this asymmetry can emerge in autocatalytic chemical networks when they contain sufficiently many chiral species and operate far from equilibrium. Polymerization greatly expands molecular diversity, raising the question of whether it can also generate and preserve a preference for one handedness. The talk develops this connection through an RNA reactor model, studying the conditions under which template-directed ligation and polymerization produce and maintain homochirality.

Donna Blackmond examines two linked problems in the origin of life: how an initially balanced mixture of molecular mirror images could acquire a handedness bias, and how that small bias could be amplified. She compares four experimental approaches using chemical kinetics and solid–solution equilibria. The first is asymmetric autocatalysis, including the Soai reaction and kinetic models connecting self-replication with suppression of the opposite enantiomer. Blackmond distinguishes this powerful model from a demonstrated prebiotic pathway. She then discusses amplification through eutectic partitioning and through attrition-enhanced deracemization, where dissolution, crystal growth and interconversion can produce a single-handed solid. The final approach incorporates stereochemical selection into plausible prebiotic chemistry. Examples explore reciprocal enrichment involving sugars and amino-acid precursors. The lecture argues that accounts of how biological building blocks arose must explain their chirality alongside their synthesis.

The question of the origin of homochirality of living matter, or the dominance of one handedness for all molecules of life across the entire biosphere, is a long-standing puzzle in the research on the Origin of Life. In the fifties, Frank proposed a mechanism to explain homochirality based on the properties of a simple autocatalytic network containing only a few chemical species. Following this work, chemists struggled to find experimental realizations of this model, possibly due to a lack of proper methods to identify autocatalysis [1]. In any case, a model based on a few chemical species seems rather limited, because prebiotic earth is likely to have consisted of complex ‘soups’ of chemicals. To include this aspect of the problem, we recently proposed a mechanism based on certain features of large out-of-equilibrium chemical networks [2]. We showed that a phase transition towards an homochiral state is likely to occur as the number of chiral species in the system becomes large or as the amount of free energy injected into the system increases. Through an analysis of large chemical databases, we showed that there is no need for very large molecules for chiral species to dominate over achiral ones; it already happens when molecules contain about 10 heavy atoms. We also analyzed the various conventions used to measure chirality and discussed the relative chiral signs adopted by different groups of molecules [3]. We then proposed a generalization of Frank’s model for large chemical networks, which we characterized using random matrix theory. This analysis includes sparse networks, suggesting that the emergence of homochirality is a robust and generic transition. References: [1] A. Blokhuis, D. Lacoste, and P. Nghe, PNAS (2020), 117, 25230. [2] G. Laurent, D. Lacoste, and P. Gaspard, PNAS (2021) 118 (3) e2012741118. [3] G. Laurent, D. Lacoste, and P. Gaspard, Proc. R. Soc. A 478:20210590 (2022).

The richness of active matter's spatiotemporal patterns continues to capture our imagination. Shaping these emergent dynamics into pre-determined forms of our choosing is a grand challenge in the field. To complicate matters, multiple dynamical attractors can coexist in such systems, leading to initial condition-dependent dynamics. Consequently, non-trivial spatiotemporal inputs are generally needed to access these states. Optimal control theory provides a general framework for identifying such inputs and represents a promising computational tool for guiding experiments and interacting with various systems in soft active matter and biology. As an exemplar, I first consider an extensile active nematic fluid confined to a disk. In the absence of control, the system produces two topological defects that perpetually circulate. Optimal control identifies a time-varying active stress field that restructures the director field, flipping the system to its other attractor that rotates in the opposite direction. As a second, analogous case, I examine a small network of coupled Belousov-Zhabotinsky chemical oscillators that possesses two dominant attractors, two wave states of opposing chirality. Optimal control similarly achieves the task of attractor switching. I conclude with a few forward-looking remarks on how the same model-based control approach might come to bear on problems in biology.