A single atom Ti-Cu(111) surface alloy can be generated by depositing small amounts of Ti onto Cu(111) at slightly elevated surface temperatures (∼500 to 600 K). Scanning tunneling microscopy shows that small Ti-rich islands covered by a Cu single layer form preferentially on ascending step edges of Cu(111) during Ti deposition below about 400 K but that a Ti-Cu(111) alloy replaces these small islands during deposition between 500 and 600 K, producing an alloy in the brims of the steps. Larger partially Cu-covered Ti-containing islands also form on the Cu(111) terraces at temperatures between 300 and 700 K. After surface exposure to CO at low temperatures, reflection absorption infrared spectroscopy (RAIRS) reveals distinct C-O stretch bands at 2102 and 2050 cm^-1 attributed to CO adsorbed on Cu-covered Ti-containing domains vs sites in the Ti-Cu(111) surface alloy. Calculations using density functional theory (DFT) suggest that the lower frequency C-O stretch band originates specifically from CO adsorbed on isolated Ti atoms in the Ti-Cu(111) surface alloy and predicts a higher C-O stretch frequency for CO adsorbed on Cu above subsurface Ti ensembles. DFT further predicts that CO preferentially adsorbs in flat-lying configurations on contiguous Ti surface structures with more than one Ti atom and thus that CO adsorbed on such structures should not be observed with RAIRS. The ability to generate a single atom Ti-Cu(111) alloy will provide future opportunities to investigate the surface chemistry promoted by a representative early transition metal dopant on a Cu(111) host surface.

The development of new catalyst materials for energy-efficient chemical synthesis is critical as over 80% of industrial processes rely on catalysts, with many of the most energy-intensive processes specifically using heterogeneous catalysis. Catalytic performance is a complex interplay of phenomena involving temperature, pressure, gas composition, surface composition, and structure over multiple length and time scales. In response to this complexity, the integrated approach to heterogeneous dilute alloy catalysis reviewed here brings together materials synthesis, mechanistic surface chemistry, reaction kinetics, in situ and operando characterization, and theoretical calculations in a coordinated effort to develop design principles to predict and improve catalytic selectivity. Dilute alloy catalysts─in which isolated atoms or small ensembles of the minority metal on the host metal lead to enhanced reactivity while retaining selectivity─are particularly promising as selective catalysts. Several dilute alloy materials using Au, Ag, and Cu as the majority host element, including more recently introduced support-free nanoporous metals and oxide-supported nanoparticle "raspberry colloid templated (RCT)" materials, are reviewed for selective oxidation and hydrogenation reactions. Progress in understanding how such dilute alloy catalysts can be used to enhance selectivity of key synthetic reactions is reviewed, including quantitative scaling from model studies to catalytic conditions. The dynamic evolution of catalyst structure and composition studied in surface science and catalytic conditions and their relationship to catalytic function are also discussed, followed by advanced characterization and theoretical modeling that have been developed to determine the distribution of minority metal atoms at or near the surface. The integrated approach demonstrates the success of bridging the divide between fundamental knowledge and design of catalytic processes in complex catalytic systems, which can accelerate the development of new and efficient catalytic processes.

Rational catalyst design is crucial toward achieving more energy-efficient and sustainable catalytic processes. Understanding and modeling catalytic reaction pathways and kinetics require atomic level knowledge of the active sites. These structures often change dynamically during reactions and are difficult to decipher. A prototypical example is the hydrogen-deuterium exchange reaction catalyzed by dilute Pd-in-Au alloy nanoparticles. From a combination of catalytic activity measurements, machine learning-enabled spectroscopic analysis, and first-principles based kinetic modeling, we demonstrate that the active species are surface Pd ensembles containing only a few (from 1 to 3) Pd atoms. These species simultaneously explain the observed X-ray spectra and equate the experimental and theoretical values of the apparent activation energy. Remarkably, we find that the catalytic activity can be tuned on demand by controlling the size of the Pd ensembles through catalyst pretreatment. Our data-driven multimodal approach enables decoding of reactive structures in complex and dynamic alloy catalysts.