Recent Progress in the Theoretical Investigation of Electrocatalytic Reduction of CO2

Advances in machine learning methods in copper alloys: a review

CONTEXT

Advanced copper and copper alloys, as significant engineering structural materials, have recently been extensively used in energy, electron, transportation, and aviation domains. Higher requirements urge the emergence of high-performance copper alloys. However, the traditional trial-and-error experimental observations and computational simulation research used to design and develop novel materials are time-consuming and costly. With the accumulation of material research and rapid development of computational ability, the thorough application of material genome engineering has sped up the development of novel materials and facilitates the process of systematic engineering application.

METHODS

This review summarizes the benefits of data-driven machine learning techniques and the state of the art of machine learning research in the area of copper alloys. It also displays the widely used computational simulation approaches (e.g., the first-principles calculation, molecular dynamics simulation, phase-field simulations, and finite element analysis) and their combined applications in material design and property prediction. Finally, the limitations of machine learning research methods are outlined, and future development directions are proposed.

Theoretical Investigation of the Potential-Dependent CO Adsorption on Copper Electrodes

Despite the importance of CO adsorption in many electrocatalytic reaction mechanisms, there has been little investigation of the dependence of the free energy of CO adsorption on the applied potential. Herein, we report on the potential-dependent adsorption of CO on Cu electrodes using a grand-canonical density functional theory approach. We demonstrate that, within the working potential range of electrocatalytic CO2 reduction on Cu(111) and Cu(100), the CO adsorption strength can change by over 0.1 eV. Our analyses explain the potential dependence through an interfacial capacitance loss upon CO adsorption as well as orbital relaxation induced by the electrode potential. Via sensitivity analysis with respect to two electrolyte model parameters (solvent dielectric constant and Debye screening length), we find that the surface excess charge density is a useful descriptor of the CO adsorption free energy.

Atomic/molecular layer deposition strategies for enhanced CO2 capture, utilisation and storage materials

Elevated levels of carbon dioxide (CO2) in the atmosphere and the diminishing reserves of fossil fuels have raised profound concerns regarding the resulting consequences of global climate change and the future supply of energy. Hence, the reduction and transformation of CO2 not only mitigates environmental pollution but also generates value-added chemicals, providing a dual remedy to address both energy and environmental challenges. Despite notable advancements, the low conversion efficiency of CO2 remains a major obstacle, largely attributed to its inert chemical nature. It is imperative to engineer catalysts/materials that exhibit high conversion efficiency, selectivity, and stability for CO2 transformation. With unparalleled precision at the atomic level, atomic layer deposition (ALD) and molecular layer deposition (MLD) methods utilize various strategies, including ultrathin modification, overcoating, interlayer coating, area-selective deposition, template-assisted deposition, and sacrificial-layer-assisted deposition, to synthesize numerous novel metal-based materials with diverse structures. These materials, functioning as active materials, passive materials or modifiers, have contributed to the enhancement of catalytic activity, selectivity, and stability, effectively addressing the challenges linked to CO2 transformation. Herein, this review focuses on ALD and MLD's role in fabricating materials for electro-, photo-, photoelectro-, and thermal catalytic CO2 reduction, CO2 capture and separation, and electrochemical CO2 sensing. Significant emphasis is dedicated to the ALD and MLD designed materials, their crucial role in enhancing performance, and exploring the relationship between their structures and catalytic activities for CO2 transformation. Finally, this comprehensive review presents the summary, challenges and prospects for ALD and MLD-designed materials for CO2 transformation.

Composite interfaces of g-C3N4 fragments loaded on a Cu substrate for CO2 reduction

Designing an electrocatalyst with high efficiency and product selectivity is always crucial for an electrocatalytic CO2 reduction reaction (CO2RR). Inspired by the great progress of two-dimensional (2D) nanomaterials growing on Cu surfaces and their promising CO2RR catalytic efficiencies at their interfaces, the unique performance of Cu-based 2D materials as high-efficiency and low-cost CO2RR electrocatalysts has attracted extensive attention. Herein, based on density functional theory (DFT) calculations, we proposed a composite structure of graphitic carbon nitride (g-C3N4) fragments loaded on a Cu surface to explore the CO2RR catalytic property of the interface between g-C3N4 and the Cu surface. Three composite interfaces of C3N4/Cu(111), C3N4/Cu(110) and C3N4/Cu(100) have been studied by considering the reaction sites of vertex nitrogen atoms, edge nitrogen atoms and the nearby Cu atoms. It was found that the C3N4/Cu interfaces where nitrogen atoms contact the Cu substrate present competitive CO2RR activity. Among them, C3N4/Cu(111)-N3 exhibited a better activity for CH3OH production, with a low overpotential of 0.38 V. For HCOOH and CH4 production, C3N4/Cu(111)-Cu and C3N4/Cu(100)-N1 have overpotentials of 0.26 V and 0.44 V. The electronic analysis indicates the electron transfer from the Cu substrate to the g-C3N4 fragment and mainly accumulates on the nitrogen atoms of the interface. Such charge accumulation can activate the adsorbed CO bond of CO2 and lead to lower energetic barriers of CO2RR. DFT calculations indicate that the boundary nitrogen sites reduced the energy barrier of *CHO, which is crucial for CO2RR, compared with that of the pristine Cu surface. Our study explores a new Cu-based electrocatalyst and indicates that the C3N4/Cu interface can enhance the activities and selectivity of CO2RR and open a new strategy to design high-efficiency electrocatalysts for CO2RR.

A DFT study of CO2 electroreduction catalyzed by hexagonal boron-nitride nanosheets with vacancy defects

In addition to providing a sustainable route to green alternative energy and chemical supplies from a cheap and abundant carbon source, recycling CO2 offers an excellent way to reduce net anthropogenic global CO2 emissions. This can be achieved via catalysis on 2D materials. These materials are atomically thin and have unique electrical and catalytic properties compared to bigger nanoparticles and conventional bulk catalysts, opening a new arena in catalysis. This paper examines the efficacy of hexagonal boron nitride (h-BN) lattices with vacancy defects for CO2 electroreduction (CO2RR). We conducted in-depth investigations on different CO2RR electrocatalytic reaction pathways on various h-BN vacancy sites using a computational hydrogen model (CHE). It was shown that CO binds to h-BN vacancies sufficiently to ensure additional electron transfer processes, leading to higher-order reduction products. For mono-atomic defects VN (removed nitrogen), the electrochemical path of (H+ + e-) pair transfers that would lead to the formation of methanol is most favorable with a limiting potential of 1.21 V. In contrast, the reaction pathways via VB (removed boron) imposes much higher thermodynamic barriers for the formation of all relevant species. With a divacancy VBN, the hydrogen evolution reaction (HER) would be the most probable process due to the low rate-determining barrier of 0.69 eV. On the tetravacancy defects VB3N the pathways toward the formation of both CH4 and CH3OH impose a limiting potential of 0.85 V. At the same time, the HER is suppressed by requiring much higher energy (2.15 eV). Modeling the edges of h-BN reveals that N-terminated zigzag conformation would impose the same limiting potential for the formation of methanol and methane (1.73 V), simultaneously suppressing the HER (3.47 V). At variance, the armchair conformation favors the HER, with a rate-determining barrier of 1.70 eV. Hence, according to our calculations, VB3N and VN are the most appropriate vacancy defects for catalyzing CO2 electroreduction reactions.

Copper Catalysis-Based Amperometric Microsensors for Carbon Dioxide Monitoring

A fast response microsensor that can detect the distribution of CO2 at the microscale level is essential for the observation of biophysiological activity, carbon flux, and carbon burial. Inspired by the previous success of Cu catalysis, we attempted to use this metal Cu material to develop an amperometric microsensor that can meet the requirements. Specifically, the ambient gases diffuse through a silicone membrane into a trap casing filled with an acidic CrCl2 solution, where the otherwise interfering O2 interferent is removed by a redox with Cr2+. The gases then diffuse through a second silicone membrane into an electrolyte, where CO2 is selectively reduced to methanol (CH3OH) at a Cu cathode through a carbon monoxide (CO) pathway. Due to the use of Cu catalysis at the WE tip, CO2 can be reduced at a less negative polarization (-470 mV) instead of the previously reported -1200 mV, thus avoiding hydrogen-evolution interference due to water from the byproduct or from water diffusion through the silicone membrane. This moderate polarization results in a stable baseline, making the microsensor suitable for long-term monitoring. Interferences from other gases, such as N2O, which may be of much concern in environmental monitoring, can be ignored. Applications and limitations are also discussed with a view to further improvement in the future.

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides

Fusing high-throughput quantum mechanical screening techniques with modern artificial intelligence strategies is among the most fundamental ─yet revolutionary─ science activities, capable of opening new horizons in catalyst discovery. Here, we apply this strategy to the process of finding appropriate key descriptors for CO₂ activation over two-dimensional transition metal (TM) carbides/nitrides (MXenes). Various machine learning (ML) models are developed to screen over 114 pure and defective MXenes, where the random forest regressor (RFR) ML scheme exhibits the best predictive performance for the CO₂ adsorption energy, with a mean absolute error ± standard deviation of 0.16 ± 0.01 and 0.42 ± 0.06 eV for training and test data sets, respectively. Feature importance analysis revealed d-band center (ε_d), surface metal electronegativity (χ_M), and valence electron number of metal atoms (M_V) as key descriptors for CO₂ activation. These findings furnish a fundamental basis for designing novel MXene-based catalysts through the prediction of potential indicators for CO₂ activation and their posterior usage.

In Situ Surface Reconstruction of Catalysts for Enhanced Hydrogen Evolution

The in situ surface reconstitution of a catalyst for hydrogen evolution refers to its structure evolution induced by strong interactions with reaction intermediates during the hydrogen evolution reaction (HER), which eventually leads to the self-optimization of active sites. In consideration of the superior performance that can be achieved by in situ surface reconstitution, more and more attention has been paid to the relationship between active site structure evolution and the self-optimization of HER activity. More and more in situ and/or operando techniques have been explored to track the dynamic structural evolution of HER catalysts in order to clarify the underlying mechanism. This review summarizes recent advances in various types of reconstruction such as the reconfiguration of crystallinity, morphological evolution, chemical composition evolution, phase transition refactoring, surface defects, and interface refactoring in the HER process. Finally, different perspectives and outlooks are offered to guide future investigations. This review is expected to provide some new clues for a deeper understanding of in situ surface reconfiguration in hydrogen evolution reactions and the targeted design of catalysts with desirable structures.

Interfacing single-atom catalysis with continuous-flow organic electrosynthesis

The global warming crisis has sparked a series of environmentally cautious trends in chemistry, allowing us to rethink the way we conduct our synthesis, and to incorporate more earth-abundant materials in our catalyst design. "Single-atom catalysis" has recently appeared on the catalytic spectrum, and has truly merged the benefits that homogeneous and heterogeneous analogues have to offer. Further still, the possibility to activate these catalysts by means of a suitable electric potential could pave the way for a true integration of diverse synthetic methodologies and renewable electricity. Despite their esteemed benefits, single-atom electrocatalysts are still limited to the energy sector (hydrogen evolution reaction, oxygen reduction, etc.) and numerous examples in the literature still invoke the use of precious metals (Pd, Pt, Ir, etc.). Additionally, batch electroreactors are employed, which limit the intensification of such processes. It is of paramount importance that the field continues to grow in a more sustainable direction, seeking new ventures into the space of organic electrosynthesis and flow electroreactor technologies. In this piece, we discuss some of the progress being made with earth abundant homogeneous and heterogeneous electrocatalysts and flow electrochemistry, within the context of organic electrosynthesis, and highlight the prospects of alternatively utilizing single-atom catalysts for such applications.

Dynamics of Heterogeneous Catalytic Processes at Operando Conditions

The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions-so-called operando modeling-is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.

Machine Learning in Screening High Performance Electrocatalysts for CO2 Reduction

Converting CO₂ into carbon-based fuels is promising for relieving the greenhouse gas effect and the energy crisis. However, the selectivity and efficiency of current electrocatalysts for CO₂ reductions are still not satisfactory. In this paper, the development of machine learning methods in screening CO₂ reduction electrocatalysts over the recent years is reviewed. Through high-throughput calculation of some key descriptors such as adsorption energies, d-band center, and coordination number by well-constructed machine learning models, the catalytic activity, optimal composition, active sites, and CO₂ reduction reaction pathway over various possible materials can be predicted and understood. Machine learning is now realized as a fast and low-cost method to effectively explore high performance electrocatalysts for CO₂ reduction.

Lewis-Basic EDTA as a Highly Active Molecular Electrocatalyst for CO2 Reduction to CH4

The most active catalysts so far successful in hydrogenation reduction of CO₂ are mainly heterogeneous Cu-based catalysts. The complex coordination environments and multiple active sites in heterogeneous catalysts result in low selectivity of target product, while molecular catalysts with well-defined active sites and tailorable structures allow mechanism-based performance optimization. Herein, we firstly report a single ethylenediaminetetraacetic acid (EDTA) molecular-level immobilized on the surface of carbon nanotube as a catalyst for transferring CO₂ to CH₄ with an excellent performance. This catalyst exhibits a high Faradaic efficiency of 61.6 % toward CH₄ , a partial current density of -16.5 mA cm^-2 at a potential of -1.3 V versus reversible hydrogen electrode. Density functional theory calculations reveal that the Lewis basic COO^- groups in EDTA molecule are the active sites for CO₂ reduction reaction (CO₂ RR). The energy barrier for the generation of CO from *CO intermediate is as high as 0.52 eV, while the further protonation of *CO to *CHO follows an energetic downhill path (-1.57 eV), resulting in the high selectivity of CH₄ . This work makes it possible to control the product selectivity for CO₂ RR according to the relationship between the energy barrier of *CO intermediate and molecular structures in the future.

Theoretical investigation of defective MXenes as potential electrocatalysts for CO reduction toward C2 products

Electrochemical CO2/CO conversion to valuable chemical products is an attractive strategy for storage of clean energy and control of greenhouse gas emission. Currently, CO2 reduction to CO is relatively mature, whereas the deep reduction and further conversion of CO into multi-carbon products, such as ethylene (C2H4) and ethanol (C2H5OH), are highly challenging. Based on the density functional theory (DFT) calculations, we explored the possibility of CO reduction reaction (CORR), to obtain C2 products, with defective MXenes in which the defect is created by removing two neighboring oxygen atoms on the surface. Our results revealed that the dual-oxygen vacancy in defective Mo2TiC2O2 (labeled as Mo2TiC2O2-2OV) can offer a unique environment that confines and enriches the active *COH species, significantly promoting the reduction process as well as C-C bond coupling. The thermodynamic barrier of the potential-determining step (PDS) for Mo2TiC2O2-2OV is 0.32 eV with promising selectivity of C2 products over the competing hydrogen evolution reaction (HER). This work provides a feasible strategy for designing MXene-based electrocatalysts for highly efficient CO2/CO reduction to C2 products.

Defect-Enhanced CO2 Reduction Catalytic Performance in O-Terminated MXenes

Electrochemical carbon dioxide reduction reaction (CO₂ RR) represents a promising way to generate fuels and chemical feedstock sustainably. Recently, studies have shown that two-dimensional metal carbides and nitrides (MXenes) can be promising CO₂ RR electrocatalysts due to the alternating -C and -H coordination with intermediates that decouples scaling relations seen on transition metal catalysts. However, further by tuning the electronic and surface structure of MXenes it should still be possible to reach higher turnover number and selectivities. To this end, defect engineering of MXenes for electrochemical CO₂ RR has not been investigated to date. In this work, first-principles modelling simulations are employed to systematically investigate CO₂ RR on M₂ XO₂ -type MXenes with transition metal and carbon/nitrogen vacancies. We found that the -C-coordinated intermediates take the form of fragments (e. g., *COOH, *CHO) whereas the -H-coordinated intermediates form a complete molecule (e. g., *HCOOH, *H₂ CO). Interestingly, the fragment-type intermediates become more strongly bound when transition-metal vacancies are present on most MXenes, while the molecule-type intermediates are largely unaffected, allowing the CO₂ RR overpotential to be tuned. The most promising defective MXene is Hf₂ NO₂ containing Hf vacancies, with a low overpotential of 0.45 V. More importantly, through electronic structure analysis it could be observed that the Fermi level of the MXene changes significantly in the presence of vacancies, indicating that the Fermi level shift can be used as an ideal descriptor to rapidly predict the catalytic performance of defective MXenes. Such an evaluation strategy is applicable to other catalysts beyond MXenes, which could enhance high throughput screening efforts for accelerated catalyst discovery.

On factors limiting the performance of photoelectrochemical CO2 reduction

The photoelectrochemical CO₂ reduction reaction (PEC-CO2RR) is a promising artificial photosynthetic system for storing solar energy as the energy of chemical bonds and stabilizing the atmospheric CO₂ level. An applicable PEC-CO2RR is expected to have broad light absorption, high selectivity to a single product, and high solar to fuel efficiency. However, the PEC-CO2RR still faces challenges from complex reaction pathways, obstructed mass transfer, and large photovoltage requirements. The goal of this perspective is to point out some of the limitations of PEC-CO2RR to a practical application. In brief, we discuss the basic concepts of PEC-CO2RR and summarize state-of-the-art progress. Moreover, we highlight the remaining challenges to both science and engineering and propose the key steps in developing a fully functional PEC-CO2RR system. Finally, an ideal PEC-CO2RR system is proposed for future studies, which is essentially wireless and combines the advantages of minimized polarization loss and broad light absorption.

Electrochemical CO2 Reduction to CO Catalyzed by 2D Nanostructures

Electrochemical CO2 reduction towards value-added chemical feedstocks has been extensively studied in recent years to resolve the energy and environmental problems. The practical application of electrochemical CO2 reduction technology requires a cost-effective, highly efficient, and robust catalyst. To date, vigorous research have been carried out to increase the proficiency of electrocatalysts. In recent years, two-dimensional (2D) graphene and transition metal chalcogenides (TMCs) have displayed excellent activity towards CO2 reduction. This review focuses on the recent progress of 2D graphene and TMCs for selective electrochemical CO2 reduction into CO.

Looking Back and Looking Ahead in Electrochemical Reduction of CO2

Electrochemical reduction of carbon dioxide (CO₂ ) to valuable organic compounds is promising as to recycling of carbon source of CO₂ and technical compatibility with systems using renewable energy resources. In recent years, considerable efforts have been devoted to the research field of CO₂ conversion using electrocatalysis. This personal account particularly focuses on the recent progress that has been achieved by the Ertl Center and a number of groups in South Korea that becomes one of the larger CO₂ emitters. The research trends of catalyst development divided into different categories according to the primary products are presented first. Afterwards, several studies on theoretical calculations and electrolytic reactors are reviewed taking into account the fundamental understanding and feasibility of the CO₂ electroreduction. Finally, a perspective on the challenges and needs in achieving the advanced level of research and development is presented.

Copper-Tin Alloys for the Electrocatalytic Reduction of CO2 in an Imidazolium-Based Non-Aqueous Electrolyte

The ability to synthesize value-added chemicals directly from CO2 will be an important technological advancement for future generations. Using solar energy to drive thermodynamically uphill electrochemical reactions allows for near carbon-neutral processes that can convert CO2 into energy-rich carbon-based fuels. Here, we report on the use of inexpensive CuSn alloys to convert CO2 into CO in an acetonitrile/imidazolium-based electrolyte. Synergistic interactions between the CuSn catalyst and the imidazolium cation enables the electrocatalytic conversion of CO2 into CO at −1.65 V versus the standard calomel electrode (SCE). This catalyst system is characterized by overpotentials for CO2 reduction that are similar to more expensive Au- and Ag-based catalysts, and also shows that the efficacy of the CO2 reduction reaction can be tuned by varying the CuSn ratio.

Understanding the Roadmap for Electrochemical Reduction of CO2 to Multi-Carbon Oxygenates and Hydrocarbons on Copper-Based Catalysts

Electrochemical reduction of CO₂ to high-energy-density oxygenates and hydrocarbons beyond CO is important for long-term and large-scale renewable energy storage. However, the key step of the C-C bond formation needed for the generation of C₂ products induces an additional barrier on the reaction. This inevitably creates larger overpotentials and greater variety of products as compared to the conversion of CO₂ to C₁ products. Therefore, an in-depth understanding of the catalytic mechanism is required for advancing the design of efficient electrocatalysts to control the reaction pathway to the desired products. Herein, we present a critical appraisal of reduction of CO₂ to C₂ products focusing on the connection between the fundamentals of reaction and efficient electrocatalysts. An in-depth discussion of the mechanistic aspects of various C₂ reaction pathways on copper-based catalysts is presented together with consideration of practical factors under electrocatalytic operating conditions. By providing some typical examples illustrating the benefit of merging theoretical calculations, surface characterization, and electrochemical measurements, we try to address the key issues of the ongoing debate toward better understanding electrochemical reduction of CO₂ at the atomic level and envisioning the roadmap for C₂ products generation.