Pohang University of Science and Technology · Energy
Professor Seoin Back's research lab specializes in computational materials science and catalysis, focusing on the design and mechanistic understanding of advanced electrocatalysts for sustainable energy conversion. The lab employs first-principles density functional theory (DFT) calculations and machine learning techniques to investigate active sites, reaction mechanisms, and electronic structure relationships in heterogeneous and single-atom catalysts for CO2 reduction and nitrogen reduction reactions. Key research directions include breaking scaling relations in electrocatalysis, engineering defect- and vacancy-based catalysts, and developing predictive descriptors for activity and selectivity. The lab aims to bridge theoretical insights with practical catalyst design for environmentally benign production of chemicals and fuels.
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Highly active and selective CO2 conversion into useful chemicals is desirable to generate valuable products out of greenhouse gases. To date, various metal-based heterogeneous catalysts have shown promising electrochemical catalytic activities for CO2 reduction, yet there have been no systematic studies of the active sites of these metal catalysts that can guide further experiments. In this study, we use first-principles calculations to identify active sites for the CO2 reduction reaction for Ag
A single-atom catalyst (SAC) has an electronic structure that is very different from its bulk counterparts, and has shown an unexpectedly high specific activity with a significant reduction in noble metal usage for CO oxidation, fuel cell and hydrogen evolution applications, although physical origins of such performance enhancements are still poorly understood. Herein, by means of density functional theory (DFT) calculations, we for the first time investigate the great potential of single atom c
High-throughput screening of catalysts can be performed using density functional theory calculations to predict catalytic properties, often correlated with adsorbate binding energies. However, more complete investigations would require an order of 2 more calculations compared to the current approach, making the computational cost a bottleneck. Recently developed machine-learning methods have been demonstrated to predict these properties from hand-crafted features but have struggled to scale to l
CO2 electrochemical catalysis is limited by scaling relations due to a d-band theory of transition metals. As a means of breaking the scaling relation, it has recently been reported that hybridizing the d-orbitals of transition metal with p-orbitals of main group elements or using naturally hybridized materials such as metal carbides and nitrides is a promising strategy. In this Letter, by means of density functional theory calculations, we investigate the catalytic properties of TiC, TiN, and s
Catalytic electroreduction of carbon dioxide to useful chemical feedstocks is an environmentally and technologically important process, yet the low energy efficiency and difficulty in controlling product selectivity are great challenges. The reason for part of the latter is that there are presently no catalyst design principles to selectively control CO2 electroreduction toward a desired product. In this work, as a first attempt, we suggest combining a few criteria (CO binding energy, OH binding
We theoretically investigate the electrochemical N2 reduction reaction (NRR) mechanism to produce NH3 on the Ru catalyst. All possible N-N dissociation steps during the reduction processes were evaluated along with the conventional associative and dissociative pathways. Based on the calculated free energy diagrams, it is revealed that the kinetically facile intermediate dissociative pathways during the NRR require a thermodynamic limiting potential (-0.71 V) similar to the associative pathway (-
Developing active and stable oxygen evolution catalysts is a key to enabling various future energy technologies, and the state of the art catalysts are Ir-containing oxide materials. Understanding oxygen chemistry on oxide materials is significantly more complicated than studying transition-metal catalysts for two reasons: the most stable surface coverage under reaction conditions is extremely important but difficult to understand without many detailed calculations, and there are many possible a
Gold is known currently as the most active single-element electrocatalyst for CO2 electroreduction reaction to CO. In this work, we combine Au with a second metal element, Cu, to reduce the amount of precious metal content by increasing the surface-to-mass ratio and to achieve comparable activity to Au-based catalysts. In particular, we demonstrate that the introduction of a Au-Cu bifunctional "interface" is more beneficial than a simple and conventional homogeneous alloying of Au and Cu in stab
Abstract Single‐atom M‒N‒C catalysts have attracted tremendous attention for their application to electrocatalysis. Nitrogen‐coordinated mononuclear metal moieties (MN x moities) are bio‐inspired active sites that are analogous to various metal‐porphyrin cofactors. Given that the functions of metal‐porphyrin cofactors are highly dependent on the local coordination environments around the mononuclear active site, engineering MN x active sites in heterogeneous M‒N‒C catalysts would provide an addi
In light of the pressing need for practical materials and molecular solutions to renewable energy and health problems, to name just two examples, one wonders how to accelerate research and development in the chemical sciences, so as to address the time it takes to bring materials from initial discovery to commercialization. Artificial intelligence (AI)-based techniques, in particular, are having a transformative and accelerating impact on many if not most, technological domains. To shed light on
Se-based nanoalloys as an emerging class of metal chalcogenide with tunable crystalline structure, component distribution, and electronic structure have attracted considerable interest in renewable energy conversion and utilization. In this Letter, we report a series of nanosized M-Se catalysts (M = Cu, Ni, Co) as prepared from laser ablation method and screen their electrocatalytic performance for onsite H<sub>2</sub>O<sub>2</sub> generation from selective oxygen reduction reaction (ORR) in alk
Discovering acid-stable, cost-effective, and active catalysts for oxygen evolution reaction (OER) is critical since this reaction is a bottleneck in many electrochemical energy conversion systems. The current systems use extremely expensive iridium oxide catalysts. Identifying Ir-free or less-Ir containing catalysts has been suggested as the goal, but no systematic strategy to discover such catalysts has been reported. In this work, we perform first-principles-based high-throughput catalyst scre
Electrochemical reduction of O2 provides a clean and decentralized pathway to produce H2O2 compared to the current energy-intensive anthraquinone process. As the electrochemical reduction of O2 proceeds via either a two-electron or a four-electron pathway, it is thus essential to control the selectivity as well as to maximize the catalytic activity. Siahrostami et al. [ Nat. Mater. 2013, 12, 1137] demonstrated a novel approach to control the reaction pathway by optimizing an adsorption ensemble
Abstract Single metal atoms doped in two‐dimensional materials have attracted particular attention for various catalytic reactions, due to their unique properties beyond metal catalysts. Herein we present density functional theory (DFT) calculations to study a wide range of such systems for oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR) for application in cathode and anode of fuel cell, respectively. We find that the scaling relation of adsorption free energies of relevant
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