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Tim E. Veenstra

Publications and source records attributed to Tim E. Veenstra.

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Synthetic paracrine signaling of colloids drives self-assembly limit cycles

Developing synthetic materials that exhibit life-like behavior, such as internally driven cycles, remains a central challenge in active matter. Here, we introduce a minimal colloidal model of chemical signaling in which particles produce diffusing signaling molecules that selectively promote or inhibit attractive interactions among neighboring particles. This bio-inspired, paracrine-like signaling mechanism generates context- and history-dependent many-body interactions that break time-reversal symmetry and drive the system far from equilibrium, leading to the spontaneous emergence of autonomous, internally sustained limit cycles in the composition of particle clusters. Using computer simulations, we map the resulting nonequilibrium phase behavior and identify distinct dynamical regimes controlled by the rates of signal production and degradation, together with the diffusion range of the signaling molecules. Among these, we find a robust oscillatory state in which particle clusters autonomously assemble in a cyclic fashion, driven entirely by internal feedback loops. Our results establish paracrine-signaling colloids as a minimal, physically realizable platform for programmable nonequilibrium materials with life-like functionality and provide a general route toward synthetic active matter with self-regulated collective dynamics.

cond-mat.soft

Counting, Computing, and Pattern Recognition with Self-Assembling Non-Reciprocal DNA Tiles

Harnessing the intrinsic dynamics of physical systems for information processing opens new avenues for computation embodied in matter. Using simulations of a model system, we show that assemblies of DNA tiles capable of self-organizing into multiple target structures can perform basic computational tasks analogous to those of finite-state automata when equipped with programmable non-reciprocal interactions that drive controlled dynamical transitions between these structures. By establishing design rules for multifarious self-assembly while budgeting the energy input required to drive these non-equilibrium transitions, we demonstrate that these systems can execute a wide variety of tasks including counting, computing modulo functions, and recognizing specific input patterns. This framework integrates memory, sensing, and actuation within a single physical platform, paving the way toward energy-efficient physical computation embedded in materials ranging from DNA and enzymes to proteins and colloids.

cond-mat.soft