Computational Screening of Doped α-MnO2 Catalysts for the Oxygen Evolution Reaction

Suppressing Jahn-Teller distortion of MnO2 via B-Ni dual single-atoms integration for methane catalytic combustion

Precisely managing electron transfer pathways throughout the catalytic reaction is paramount for bolstering both the efficacy and endurance of catalysts, offering a pivotal solution to addressing concerns surrounding host structure destabilization and cycling life degradation. This paper describes the integration of B-Ni dual single-atoms within MnO2 channels to serve as an electronic reservoir to direct the electron transfer route during methane catalytic combustion. Comprehensive analysis discovers that B atoms weaken the interaction between O and Mn atoms by forming bonds with lattice oxygen atoms. Meanwhile, Ni atoms facilitate electron transfer to achieve the heightened activity of MnO2. The B-Ni dual-sites instead of Mn (IV) could accommodate excess electrons generated during the reaction to inhibit the formation of high spin Mn (III) species, thereby hindering the Jahn-Teller distortion and maintaining the catalyst stability. This work demonstrates an effective modification strategy to substantially prolong the service life of MnO2-based materials.

Crystal-Phase Engineering in Heterogeneous Catalysis

The performance of a chemical reaction is critically dependent on the electronic and/or geometric structures of a material in heterogeneous catalysis. Over the past century, the Sabatier principle has already provided a conceptual framework for optimal catalyst design by adjusting the electronic structure of the catalytic material via a change in composition. Beyond composition, it is essential to recognize that the geometric atomic structures of a catalyst, encompassing terraces, edges, steps, kinks, and corners, have a substantial impact on the activity and selectivity of a chemical reaction. Crystal-phase engineering has the capacity to bring about substantial alterations in the electronic and geometric configurations of a catalyst, enabling control over coordination numbers, morphological features, and the arrangement of surface atoms. Modulating the crystallographic phase is therefore an important strategy for improving the stability, activity, and selectivity of catalytic materials. Nonetheless, a complete understanding of how the performance depends on the crystal phase of a catalyst remains elusive, primarily due to the absence of a molecular-level view of active sites across various crystal phases. In this review, we primarily focus on assessing the dependence of catalytic performance on crystal phases to elucidate the challenges and complexities inherent in heterogeneous catalysis, ultimately aiming for improved catalyst design.

Cation-doped sea-urchin-like MnO2 for electrocatalytic overall water splitting

It is necessary to take full account of the activity, selectivity, dynamic performance, economic benefits, and environmental impact of the catalysts in the overall water splitting of electrocatalysis for the reasonable design of electrocatalysts. Designing nanostructures of catalysts and optimizing defect engineering are considered environmentally friendly and cost-effective electrocatalyst synthesis strategies. Herein, we report that metal cations regulate the microstructure of sea-urchin-like MnO2 and act as dopants to cause the lattice expansion of MnO2, resulting in crystal surface defects. The valence unsaturated Mn4+/Mn3+ greatly promotes the electrocatalytic oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). The optimal Al-MnO2 showed that the overpotential is 390 and 170 mV in the process of catalyzing OER and HER, respectively, at a current density of 10 mA cm-2. It is exciting to note that after 5000 cycles of Al-MnO2 within the kinetic potential range of OER and HER, its performance remained almost unchanged. This work provides a simple, efficient, and environmentally friendly route for the design of efficient integrated water-splitting electrocatalysts.

Synergistic effect of p-type and n-type dopants in semiconductors for efficient electrocatalytic water splitting

The main challenge for acidic water electrolysis is the lack of active and stable oxygen evolution catalysts based on abundant materials, which are globally scalable. Iridium oxide is the only material which is active and stable. However, Ir is extremely rare. While both active materials and stable materials exist, those that are active are usually not stable and vice versa. In this work, we present a new design strategy for activating stable materials originally deemed unsuitable due to a semiconducting nature and wide band gap energy. These stable semiconductors cannot change oxidation state under the relevant reaction conditions. Based on DFT calculations, we find that adding an n-type dopant facilitates oxygen binding on semiconductor surfaces. The binding is, however, strong and prevents further binding or desorption of oxygen. By combining both n-type and p-type dopants, the reactivity can be tuned so that oxygen can be adsorbed and desorbed under reaction conditions. The tuning results from the electrostatic interactions between the dopants as well as between the dopants and the binding site. This concept is experimentally verified on TiO2 by co-substituting with different pairs of n- and p-type dopants. Our findings suggest that the co-substitution approach can be used to activate stable materials, with no intrinsic oxygen evolution activity, to design new catalysts for acid water electrolysis.

Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments

Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally benign, and affordable is amongst the most pressing challenges for future socio-economic development. To that goal, hydrogen is presumed to be the most promising energy carrier. Electrocatalytic water splitting, if driven by green electricity, would provide hydrogen with minimal CO2 footprint. The viability of water electrolysis still hinges on the availability of durable earth-abundant electrocatalyst materials and the overall process efficiency. This review spans from the fundamentals of electrocatalytically initiated water splitting to the very latest scientific findings from university and institutional research, also covering specifications and special features of the current industrial processes and those processes currently being tested in large-scale applications. Recently developed strategies are described for the optimisation and discovery of active and durable materials for electrodes that ever-increasingly harness first-principles calculations and machine learning. In addition, a technoeconomic analysis of water electrolysis is included that allows an assessment of the extent to which a large-scale implementation of water splitting can help to combat climate change. This review article is intended to cross-pollinate and strengthen efforts from fundamental understanding to technical implementation and to improve the 'junctions' between the field's physical chemists, materials scientists and engineers, as well as stimulate much-needed exchange among these groups on challenges encountered in the different domains.

Practical Deep-Learning Representation for Fast Heterogeneous Catalyst Screening

The binding site and energy is an invaluable descriptor in high-throughput screening of catalysts, as it is accessible and correlates with the activity and selectivity. Recently, comprehensive binding energy prediction machine-learning models have been demonstrated and promise to accelerate the catalyst screening. Here, we present a simple and versatile representation, applicable to any deep-learning models, to further accelerate such process. Our approach involves labeling the binding site atoms of the unrelaxed bare surface geometry; hence, for the model application, density functional theory calculations can be completely removed if the optimized bulk structure is available as is the case when using the Materials Project database. In addition, we present ensemble learning, where a set of predictions is used together to form a predictive distribution that reduces the model bias. We apply the labeled site approach and ensemble to crystal graph convolutional neural network and the ∼40 000 data set of alloy catalysts for CO₂ reduction. The proposed model applied to the data set of unrelaxed structures shows 0.116 and 0.085 eV mean absolute error, respectively, for CO and H binding energy, better than the best method (0.13 and 0.13 eV) in the literature that requires costly geometry relaxations. The analysis of the model parameters demonstrates that the model can effectively learn the chemical information related to the binding site.

Oxygen evolution reaction: a perspective on a decade of atomic scale simulations

Multiple strategies to overcome the intrinsic limitations of the oxygen evolution reaction (OER) have been proposed by numerous research groups. Despite the substantial efforts, the driving force required for water oxidation is largely making the reaction inefficient. In the present work, we collected published studies involving DFT calculations for the OER, with the purpose to understand why the progress made so far, for lowering the overpotential of the reaction, is relatively small. The data revealed that the universal scaling relationship between HO* and HOO* intermediates is still present and robust, despite the variety in methods and structures used for calculating the binding energies of the intermediates. On the other hand, the data did not show a clear trend line regarding the O* binding. Our analysis suggested that trends in doped semiconducting oxides behave very differently from those in other oxides. This points towards a computational challenge in describing doped oxides in a realistic manner. We propose a way to overcome these computational challenges, which can be applied to simulations corresponding to doped semiconductors in general.

Controllable Hortensia-like MnO2 Synergized with Carbon Nanotubes as an Efficient Electrocatalyst for Long-Term Metal-Air Batteries

The exploitation of a high-activity and low-cost bifunctional catalyst for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) as the cathode catalyst is a research priority in metal-air batteries. Herein, a novel bifunctional hybrid catalyst of hortensia-like MnO₂ synergized with carbon nanotubes (CNTs) (MnO₂/CNTs) is controllably synthesized by reasonably designing the crystal structure and morphology as well as electronic arrangement. On the basis of these strategies, the hybrid accelerates the reaction kinetics and avoids the change of structures. As expected, MnO₂/CNTs exhibit a remarkable ORR and OER activity [low ORR Tafel slope: 71 mV dec^-1, low OER Tafel slope: 67 mV dec^-1, and small potential difference (Δ E): 0.85 V] and a long-term stability, which should be attributed to its unique morphology, K⁺ ions in the 2 × 2 tunnels, and synergistic effect between MnO₂ and CNTs. Notably, in zinc-air batteries (ZABs), aluminum-air batteries (AABs), and magnesium-air batteries (MABs), the composite shows high power density (ZABs: 243 mW cm^-2, AABs: 530 mW cm^-2, and MABs: 614 mW cm^-2) and large specific capacities (793 mA h g_Zn^-1, 918 mA h g_Al^-1, and 878 mA h g_Mg^-1). Importantly, the rechargeable ZABs reveal small charge-discharge voltage drop (0.81 V) and strong cycle durability (500 h), which are better than the noble-metal Pt/C + IrO₂ mixture catalyst (the voltage drop: 1.15 V at first and 2 V after 100 h). These superior performances together with the simple synthetic method of the hybrid reveal great promise in large-power energy storage and conversion equipment.

One-step synthesis of bifunctional iron-doped manganese oxide nanorods for rechargeable zinc–air batteries

Iron doped MnO₂ nanorods are successfully synthesized via one step hydrothermal method. The nanorods shows remarkable high bifunctional electrocatalytic activity for oxygen reduction as well as oxygen evolution reaction. For practical applications, a solid-state zinc–air battery was made for powering a light emitting diode.

Thermodynamic and Kinetic Limitations for Peroxide and Superoxide Formation in Na-O2 Batteries

The Na-O₂ system holds great potential as a low-cost, high-energy-density battery, but under normal operating conditions, the discharge is limited to sodium superoxide (NaO₂), whereas the high-capacity peroxide state (Na₂O₂) remains elusive. Here, we apply density functional theory calculations with an improved error-correction scheme to determine equilibrium potentials and free energies as a function of temperature for the different phases of NaO₂ and Na₂O₂, identifying NaO₂ as the thermodynamically preferred discharge product up to ∼120 K, after which Na₂O₂ is thermodynamically preferred. We also investigate the reaction mechanisms and resulting electrochemical overpotentials on stepped surfaces of the NaO₂ and Na₂O₂ systems, showing low overpotentials for NaO₂ formation (η_dis = 0.14 V) and depletion (η_cha = 0.19 V), whereas the overpotentials for Na₂O₂ formation (η_dis = 0.69 V) and depletion (η_cha = 0.68 V) are found to be prohibitively high. These findings are in good agreement with experimental data on the thermodynamic properties of the Na _xO₂ species and provide a kinetic explanation for why NaO₂ is the main discharge product in Na-O₂ batteries under normal operating conditions.

Combined DFT and Differential Electrochemical Mass Spectrometry Investigation of the Effect of Dopants in Secondary Zinc-Air Batteries

Zinc-air batteries offer the potential of low-cost energy storage with high specific energy, but at present secondary Zn-air batteries suffer from poor cyclability. To develop economically viable secondary Zn-air batteries, several properties need to be improved: choking of the cathode, catalyzing the oxygen evolution and reduction reactions, limiting dendrite formation and suppressing the hydrogen evolution reaction (HER). Understanding and alleviating HER at the negative electrode in a secondary Zn-air battery is a substantial challenge, for which it is necessary to combine computational and experimental research. Here, we combine differential electrochemical mass spectrometry (DEMS) and density functional theory (DFT) calculations to investigate the fundamental role and stability when cycling in the presence of selected beneficial additives, that is, In and Bi, and Ag as a potentially unfavorable additive. We show that both In and Bi have the desired property for a secondary battery, that is, upon recharging they will remain on the surface, thereby retaining the beneficial effects on Zn dissolution and suppression of HER. This is confirmed by DEMS, where it is observed that In reduces HER and Bi affects the discharge potential beneficially compared to a battery without additives. Using a simple procedure based on adsorption energies calculated with DFT, it is found that Ag suppresses OH adsorption, but, unlike In and Bi, it does not hinder HER. Finally, it is shown that mixing In and Bi is beneficial compared to the additives by themselves as it improves the electrochemical performance and cyclic stability of the secondary Zn-air battery.