Bimetallic and multi-component catalysts typically exhibit composition-dependent activity and selectivity, and when optimized often outperform single-component catalysts. Here we used ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) and in situ and ex situ transmission electron microscopy (TEM) to elucidate the origin of composition dependence observed in the catalytic activities of monodisperse CoPd bimetallic nanocatalysts for CO oxidation. We found that the catalysis process induced a reconstruction of the catalysts, leaving CoOx on the nanoparticle surface. The synergy between Pd and CoOx coexisting on the surface promotes the catalytic activity of the bimetallic catalysts. This synergistic effect can be optimized by tuning the Co/Pd ratios in the nanoparticle synthesis, and it reaches a maximum at compositions near Co0.24Pd0.76, which achieves complete CO conversion at the lowest temperature. Our combined AP-XPS and TEM studies provide direct observation of the surface evolution of the bimetallic nanoparticles under catalytic conditions and show how this evolution correlates with catalytic properties.

In the version of this Article originally published, the author Baran Eren was mistakenly affiliated with the Harbin Institute of Technology, China; it has now been corrected to Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Learning to engineer self-assembly would enable the precise organization of molecules by design to create matter with tailored properties. Here we demonstrate that proteins can direct the self-assembly of buckminsterfullerene (C60) into ordered superstructures. A previously engineered tetrameric helical bundle binds C60 in solution, rendering it water soluble. Two tetramers associate with one C60, promoting further organization revealed in a 1.67-Å crystal structure. Fullerene groups occupy periodic lattice sites, sandwiched between two Tyr residues from adjacent tetramers. Strikingly, the assembly exhibits high charge conductance, whereas both the protein-alone crystal and amorphous C60 are electrically insulating. The affinity of C60 for its crystal-binding site is estimated to be in the nanomolar range, with lattices of known protein crystals geometrically compatible with incorporating the motif. Taken together, these findings suggest a new means of organizing fullerene molecules into a rich variety of lattices to generate new properties by design.

The execution and analysis of complex experiments are challenged by the vast dimensionality of the underlying parameter spaces. Although an increase in data-acquisition rates should allow broader querying of the parameter space, the complexity of experiments and the subtle dependence of the model function on input parameters remains daunting owing to the sheer number of variables. New strategies for autonomous data acquisition are being developed, with one promising direction being the use of Gaussian process regression (GPR). GPR is a quick, non-parametric and robust approximation and uncertainty quantification method that can be applied directly to autonomous data acquisition. We review GPR-driven autonomous experimentation and illustrate its functionality using real-world examples from large experimental facilities in the USA and France. We introduce the basics of a GPR-driven autonomous loop with a focus on Gaussian processes, and then shift the focus to the infrastructure that needs to be built around GPR to create a closed loop. Finally, the case studies we discuss show that Gaussian-process-based autonomous data acquisition is a widely applicable method that can facilitate the optimal use of instruments and facilities by enabling the efficient acquisition of high-value datasets.