Learning to learn by using nonequilibrium training protocols for adaptable materials.

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally responsive materials therefore open up the possibility of creating a wide range of synthetic materials which can also be trained for adaptability. We consider high-dimensional inverse problems for materials where any particular functionality can be realized by numerous equivalent choices of design parameters.

Epithelial tissue confinement inhibits cell growth and leads to volume-reducing divisions.

Cell proliferation is a central process in tissue development, homeostasis, and disease, yet how proliferation is regulated in the tissue context remains poorly understood. Here, we introduce a quantitative framework to elucidate how tissue growth dynamics regulate cell proliferation. Using MDCK epithelial monolayers, we show that a limiting rate of tissue expansion creates confinement that suppresses cell growth; however, this confinement does not directly affect the cell cycle.

3D-printed machines that manipulate microscopic objects using capillary forces.

Objects that deform a liquid interface are subject to capillary forces, which can be harnessed to assemble the objects. Once assembled, such structures are generally static. Here we dynamically modulate these forces to move objects in programmable two-dimensional patterns.

Collagen-Inspired Self-Assembly of Twisted Filaments.

Collagen consists of three peptides twisted together through a periodic array of hydrogen bonds. Here we use this as inspiration to find design rules for programmed specific interactions for self-assembling synthetic collagenlike triple helices, starting from disordered configurations. The assembly generically nucleates defects in the triple helix, the characteristics of which can be manipulated by spatially varying the enthalpy of helix formation.

Can surface hopping sans decoherence recover Marcus theory? Understanding the role of friction in a surface hopping view of electron transfer.

We compare the dynamics of Fewest Switches Surface Hopping (FSSH) in different parameter regimes of the spin-boson model. We show that for exceptional regions of the spin-boson parameter space, FSSH dynamics are in fact time-reversible. In these rare instances, FSSH does recover the correct Marcus rate scaling (as a function of diabatic coupling) without the addition of decoherence.

Communication: The correct interpretation of surface hopping trajectories: how to calculate electronic properties.

In a recent paper, we presented a road map for how Tully's fewest switches surface hopping (FSSH) algorithm can be derived, under certain circumstances, from the mixed quantum-classical Liouville equation. In this communication, we now demonstrate how this new interpretation of surface hopping can yield significantly enhanced results for electronic properties in nonadiabatic calculations. Specifically, we calculate diabatic populations for the spin-boson problem using FSSH trajectories.