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Direct design of complex functional materials would revolutionize technologies ranging from printable organs to novel clean energy devices. However, even incremental steps toward designing functional materials have proven challenging. If the material is constructed from highly complex components, the design space of materials properties rapidly becomes too computationally expensive to search. On the other hand, very simple components such as uniform spherical particles are not powerful enough to capture rich functional behavior. Here, we introduce a differentiable materials design model with components that are simple enough to design yet powerful enough to capture complex materials properties: rigid bodies composed of spherical particles with directional interactions (patchy particles). We showcase the method with self-assembly designs ranging from open lattices to self-limiting clusters, all of which are notoriously challenging design goals to achieve using purely isotropic particles. By directly optimizing over the location and interaction of the patches on patchy particles using gradient descent, we dramatically reduce the computation time for finding the optimal building blocks. 

Abstract Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well‐being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline‐specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph‐based “Translator” system capable of integrating existing biomedical data sets and “translating” those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system’s architecture, performance, and quality of results. We apply Translator to several real‐world use cases developed in collaboration with subject‐matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state‐of‐the‐art, biomedical graph‐based question‐answering systems. 

Abstract Ultralong afterglow emissions due to room‐temperature phosphorescence (RTP) are of paramount importance in the advancement of smart sensors, bioimaging and light‐emitting devices. We herein present an efficient approach to achieve rarely accessible phosphorescence of heavy atom‐free organoboranes via photochemical switching of sterically tunable fluorescent Lewis pairs (LPs). LPs are widely applied in and well‐known for their outstanding performance in catalysis and supramolecular soft materials but have not thus far been exploited to develop photo‐responsive RTP materials. The intramolecular LPM1BNMnot only shows a dynamic response to thermal treatment due to reversible N→B coordination but crystals ofM1BNMalso undergo rapid photochromic switching. As a result, unusual emission switching from short‐lived fluorescence to long‐lived phosphorescence (rad‐M1BNM,τ_RTP=232 ms) is observed. The reported discoveries in the field of Lewis pairs chemistry offer important insights into their structural dynamics, while also pointing to new opportunities for photoactive materials with implications for fast responsive detectors.