Unravelling CO2 Reduction Reaction Intermediates on High Entropy Alloy Catalysts: An Interpretable Machine Learning Approach to Establish Scaling Relations

Establishment of a scaling relation among the reaction intermediates is highly important but very much challenging on complex surfaces, such as surfaces of high entropy alloys (HEAs). Herein, we designed an interpretable machine learning (ML) approach to establish a scaling relation among CO2 reduction reaction (CO2 RR) intermediates adsorbed at the same adsorption site. Local Interpretable Model-Agnostic Explanations (LIME), Accumulated Local Effects (ALE), and Permutation Feature Importance (PFI) are used for the global and local interpretation of the utilized black box models. These methods were successfully applied through an iterative way and validated on CuCoNiZnMg and CuCoNiZnSnbased HEAs data. Finally, we successfully predicted adsorption energies of *H2 CO (MAE: 0.24 eV) and *H3 CO (MAE: 0.23 eV) by using the *HCO training data. Similarly, adsorption energy of *O (MAE: 0.32 eV) is also predicted from *H training data. We believe that our proposed method can shift the paradigm of state-of-the-art ML in catalysis towards better interpretability.

Nano-Scale Engineering of Heterojunction for Alkaline Water Electrolysis

Alkaline water electrolysis is promising for low-cost and scalable hydrogen production. Renewable energy-driven alkaline water electrolysis requires highly effective electrocatalysts for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). However, the most active electrocatalysts show orders of magnitude lower performance in alkaline electrolytes than that in acidic ones. To improve such catalysts, heterojunction engineering has been exploited as the most efficient strategy to overcome the activity limitations of the single component in the catalyst. In this review, the basic knowledge of alkaline water electrolysis and the catalytic mechanisms of heterojunctions are introduced. In the HER mechanisms, the ensemble effect emphasizes the multi-sites of different components to accelerate the various intermedium reactions, while the electronic effect refers to the d-band center theory associated with the adsorption and desorption energies of the intermediate products and catalyst. For the OER with multi-electron transfer, a scaling relation was established: the free energy difference between HOO* and HO* is 3.2 eV, which can be overcome by electrocatalysts with heterojunctions. The development of electrocatalysts with heterojunctions are summarized. Typically, Ni(OH)2/Pt, Ni/NiN3 and MoP/MoS2 are HER electrocatalysts, while Ir/Co(OH)2, NiFe(OH)x/FeS and Co9S8/Ni3S2 are OER ones. Last but not the least, the trend of future research is discussed, from an industry perspective, in terms of decreasing the number of noble metals, achieving more stable heterojunctions for longer service, adopting new craft technologies such as 3D printing and exploring revolutionary alternate alkaline water electrolysis.

Engineering Sub-Nanometer Hafnia-Based Ferroelectrics to Break the Scaling Relation for High-Efficiency Piezocatalytic Water Splitting

Reversible control of ferroelectric polarization is essential to overcome the heterocatalytic kinetic limitation. This can be achieved by creating a surface with switchable electron density; however, owing to the rigidity of traditional ferroelectric oxides, achieving polarization reversal in piezocatalytic processes remains challenging. Herein, sub-nanometer-sized Hf0.5 Zr0.5 O2 (HZO) nanowires with a polymer-like flexibility are synthesized. Oxygen K-edge X-ray absorption spectroscopy and negative spherical aberration-corrected transmission electron microscopy reveal an orthorhombic (Pca21 ) ferroelectric phase of the HZO sub-nanometer wires (SNWs). The ferroelectric polarization of the flexible HZO SNWs can be easily switched by slight external vibration, resulting in dynamic modulation of the binding energy of adsorbates and thus breaking the "scaling relationship" during piezocatalysis. Consequently, the as-synthesized ultrathin HZO nanowires display superb water-splitting activity, with H2 production rate of 25687 µmol g-1  h-1 under 40 kHz ultrasonic vibration, which is 235 and 41 times higher than those of non-ferroelectric hafnium oxides and rigid BaTiO3 nanoparticles, respectively. More strikingly, the hydrogen production rates can reach 5.2 µmol g-1  h-1 by addition of stirring exclusively.

Promoting Oxygen Reduction Reaction on Carbon-based Materials by Selective Hydrogen Bonding

Electrochemical oxygen reduction reaction (ORR) is fundamental for many energy conversion and storage devices. Selective tuning of *OOH/*OH adsorption energy to break the intrinsic scaling limitation (ΔG*OOH =ΔG*OH +3.2 eV) is effective in optimizing the ORR limiting potential (UL ), which is practically challenging to achieve by constructing a particular catalyst. Herein, using first-principles calculations, we elucidated how to rationally plant an additional *OH that can selectively interact with the ORR intermediate of *OOH via hydrogen bonding, while not affecting the *OH intermediate. Guided by the design principle, we successfully tailored a series of novel carbon-based catalysts, with merits of low-cost, long-lasting, synthesis feasibility, exhibiting a high UL (1.06 V). Our proposed strategy comes up with a new linear scaling relationship of ΔG*OOH =ΔG*OH +2.84 eV. This approach offers a great possibility for the rational design of efficient catalysts for ORR and other chemical reactions.

Materials Screening by the Descriptor G max(η): The Free-Energy Span Model in Electrocatalysis

To move from fossil-based energy resources to a society based on renewables, electrode materials free of precious noble metals are required to efficiently catalyze electrochemical processes in fuel cells, batteries, or electrolyzers. Materials screening operating at minimal computational cost is a powerful method to assess the performance of potential electrode compositions based on heuristic concepts. While the thermodynamic overpotential in combination with the volcano concept refers to the most popular descriptor-based analysis in the literature, this notion cannot reproduce experimental trends reasonably well. About two years ago, the concept of G _max(η), based on the idea of the free-energy span model, has been proposed as a universal approach for the screening of electrocatalysts. In contrast to other available descriptor-based methods, G _max(η) factors overpotential and kinetic effects by a dedicated evacuation scheme of adsorption free energies into an analysis of trends. In the present perspective, we discuss the application of G _max(η) to different electrocatalytic processes, including the oxygen evolution and reduction reactions, the nitrogen reduction reaction, and the selectivity problem of the competing oxygen evolution and peroxide formation reactions, and we outline the advantages of this screening approach over previous investigations.

Achieving industrial ammonia synthesis rates at near-ambient conditions through modified scaling relations on a confined dual site

The production of ammonia through the Haber-Bosch process is regarded as one of the most important inventions of the 20th century. Despite significant efforts in optimizing the process, it still consumes 1 to 2% of the worldwide annual energy for the high working temperatures and pressures. The design of a catalyst with a high activity at milder conditions represents another challenge for this reaction. Herein, we combine density functional theory and microkinetic modeling to illustrate a strategy to facilitate low-temperature and -pressure ammonia synthesis through modified energy-scaling relationships using a confined dual site. Our results suggest that an ammonia synthesis rate two to three orders of magnitude higher than the commercial Ru catalyst can be achieved under the same reaction conditions with the introduction of confinement. Such strategies will open pathways for the development of catalysts for the Haber-Bosch process that can operate at milder conditions and present more economically viable alternatives to current industrial solutions.

Biomass hydrodeoxygenation catalysts innovation from atomistic activity predictors

Circular economy emphasizes the idea of transforming products involving economic growth and improving the ecological system to reduce the negative consequences caused by the excessive use of raw materials. This can be achieved with the use of second-generation biomass that converts industrial and agricultural wastes into bulk chemicals. The use of catalytic processes is essential to achieve a viable upgrade of biofuels from the lignocellulosic biomass. We carried out density functional theory calculations to explore the relationship between 13 transition metals (TMs) properties, as catalysts, and their affinity for hydrogen and oxygen, as key species in the valourization of biomass. The relation of these parameters will define the trends of the hydrodeoxygenation (HDO) process on biomass-derived compounds. We found the hydrogen and oxygen adsorption energies in the most stable site have a linear relation with electronic properties of these metals that will rationalize the surface's ability to bind the biomass-derived compounds and break the C-O bonds. This will accelerate the catalyst innovation for low temperature and efficient HDO processes on biomass derivates, e.g. guaiacol and anisole, among others. Among the monometallic catalysts explored, the scaling relationship pointed out that Ni has a promising balance between hydrogen and oxygen affinities according to the d-band centre and d-band width models. The comparison of the calculated descriptors to the adsorption strength of guaiacol on the investigated surfaces indicates that the d-band properties alone are not best suited to describe the trend. Instead, we found that a linear combination of work function and d-band properties gives significantly better correlation. This article is part of a discussion meeting issue 'Science to enable the circular economy'.

Electronic Polarizability as the Fundamental Variable in the Dielectric Properties of Two-Dimensional Materials

The dielectric constant, which defines the polarization of the media, is a key quantity in condensed matter. It determines several electronic and optoelectronic properties important for a plethora of modern technologies from computer memory to field effect transistors and communication circuits. Moreover, the importance of the dielectric constant in describing electromagnetic interactions through screening plays a critical role in understanding fundamental molecular interactions. Here, we show that despite its fundamental transcendence, the dielectric constant does not define unequivocally the dielectric properties of two-dimensional (2D) materials due to the locality of their electrostatic screening. Instead, the electronic polarizability correctly captures the dielectric nature of a 2D material which is united to other physical quantities in an atomically thin layer. We reveal a long-sought universal formalism where electronic, geometrical, and dielectric properties are intrinsically correlated through the polarizability, opening the door to probe quantities yet not directly measurable including the real covalent thickness of a layer. We unify the concept of dielectric properties in any material dimension finding a global dielectric anisotropy index defining their controllability through dimensionality.

Glacial Steady State Topography Controlled by the Coupled Influence of Tectonics and Climate

Glaciers and rivers are the main agents of mountain erosion. While in the fluvial realm empirical relationships and their mathematical description, such as the stream power law, improved the understanding of fundamental controls on landscape evolution, simple constraints on glacial topography and governing scaling relations are widely lacking. We present a steady state solution for longitudinal profiles along eroding glaciers in a coupled system that includes tectonics and climate. We combined the shallow ice approximation and a glacial erosion rule to calculate ice surface and bed topography from prescribed glacier mass balance gradient and rock uplift rate. Our approach is inspired by the classic application of the stream power law for describing a fluvial steady state but with the striking difference that, in the glacial realm, glacier mass balance is added as an altitude-dependent variable. From our analyses we find that ice surface slope and glacial relief scale with uplift rate with scaling exponents indicating that glacial relief is less sensitive to uplift rate than relief in most fluvial landscapes. Basic scaling relations controlled by either basal sliding or internal deformation follow a power law with the exponent depending on the exponents for the glacial erosion rule and Glen's flow law. In a mixed scenario of sliding and deformation, complicated scaling relations with variable exponents emerge. Furthermore, a cutoff in glacier mass balance or cold ice in high elevations can lead to substantially larger scaling exponents which may provide an explanation for high relief in high latitudes.