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We report a joint negative ion photoelectron spectroscopy (NIPES) and quantum chemical computational study on glycine-chloride/bromide complexes (denoted Gly·X−, X = Cl/Br) in close comparison to the previously studied Gly·I− cluster ion. Combining experimental NIPE spectra and theoretical calculations, various Gly·X− complexes were found to adopt the same types of low-lying isomers, albeit with different relative energies. Despite more congested spectral profiles for Gly·Cl− and Gly·Br−, spectral assignments were accomplished with the guidance of the knowledge learned from Gly·I−, where a larger spin–orbit splitting of iodine afforded well-resolved, recognizable spectral peaks. Three canonical plus one zwitterionic isomer for Gly·Cl− and four canonical conformers for Gly·Br− were experimentally identified and characterized in contrast to the five canonical ones observed for Gly·I− under similar experimental conditions. Taken together, this study investigates both genericity and variations in binding patterns for the complexes composed of glycine and various halides, demonstrating that iodide-tagging is an effective spectroscopic means to unravel diverse ion-molecule binding motifs for cluster anions with congested spectral bands by substituting the respective ion with iodide. 

Replicating human-like dexterity in robot hands represents one of the largest open problems in robotics. Reinforcement learning is a promising approach that has achieved impressive progress in the last few years; however, the class of problems it has typically addressed corresponds to a rather narrow definition of dexterity as compared to human capabilities. To address this gap, we investigate piano-playing, a skill that challenges even the human limits of dexterity, as a means to test high-dimensional control, and which requires high spatial and temporal precision, and complex finger coordination and planning. We introduce RoboPianist, a system that enables simulated anthropomorphic hands to learn an extensive repertoire of 150 piano pieces where traditional model-based optimization struggles. We additionally introduce an open-sourced environment, benchmark of tasks, interpretable evaluation metrics, and open challenges for future study. 

Electroreduction of carbon dioxide (CO₂) or carbon monoxide (CO) toward C₂₊hydrocarbons such as ethylene, ethanol, acetate and propanol represents a promising approach toward carbon-negative electrosynthesis of chemicals. Fundamental understanding of the carbon─carbon (C-C) coupling mechanisms in these electrocatalytic processes is the key to the design and development of electrochemical systems at high energy and carbon conversion efficiencies. Here, we report the investigation of CO electreduction on single-atom copper (Cu) electrocatalysts. Atomically dispersed Cu is coordinated on a carbon nitride substrate to form high-density copper─nitrogen moieties. Chemisorption, electrocatalytic, and computational studies are combined to probe the catalytic mechanisms. Unlike the Langmuir-Hinshelwood mechanism known for copper metal surfaces, the confinement of CO adsorption on the single-copper-atom sites enables an Eley-Rideal type of C-C coupling between adsorbed (*CO) and gaseous [CO(g)] carbon moxide molecules. The isolated Cu sites also selectively stabilize the key reaction intermediates determining the bifurcation of reaction pathways toward different C₂₊products.