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The oxygen evolution reaction (OER) is key for the transition to a hydrogen-based energy economy. The observed activity of the OER catalysts arises from the combined effects of surface area, intrinsic activity, and stability. Therefore, alloys provide an effective platform to search for catalysts that balance these factors. In particular, high-entropy oxides provide a vast material composition space that could contain catalysts with optimal OER performance. In this work, the OER performance of the AuIrOsPdPtReRhRu composition space was modeled using an experimentally obtained dataset of 350 nanoparticles. This machine-learned model based on experimental data found the optimal catalyst to be a mixture of AuIrOsPdRu. However, as a “black-box model”, it cannot explain the underlying chemistry. Therefore, density functional theory (DFT) calculations were performed to provide a complementary theoretical model with defined assumptions and, hence, a physical interpretation through comparison with the experimental model. The DFT calculations suggest that the majority of the activity originates from Ru and Ir active sites and that the addition of Pd improves the performance of these sites. However, the DFT calculation did not find the experimentally observed beneficial effects of Au and Os. Therefore, we hypothesize that the Os contributed to the performance of the tested catalysts by roughening the surface, whereas Au fulfilled the role of a structural support. Overall, it is demonstrated how machine learning can help accelerate catalyst discovery, and combining machine-learned models obtained from experimental data with models based on DFT calculations can provide important insights into the complex chemistry of OER catalysts.

The oxygen evolution reaction (OER) is key for the transition to a hydrogen-based energy economy. The observed activity of the OER catalysts arises from the combined effects of surface area, intrinsic activity, and stability. Therefore, alloys provide an effective platform to search for catalysts that balance these factors. In particular, high-entropy oxides provide a vast material composition space that could contain catalysts with optimal OER performance. In this work, the OER performance of the AuIrOsPdPtReRhRu composition space was modeled using an experimentally obtained dataset of 350 nanoparticles. This machine-learned model based on experimental data found the optimal catalyst to be a mixture of AuIrOsPdRu. However, as a “black-box model”, it cannot explain the underlying chemistry. Therefore, density functional theory (DFT) calculations were performed to provide a complementary theoretical model with defined assumptions and, hence, a physical interpretation through comparison with the experimental model. The DFT calculations suggest that the majority of the activity originates from Ru and Ir active sites and that the addition of Pd improves the performance of these sites. However, the DFT calculation did not find the experimentally observed beneficial effects of Au and Os. Therefore, we hypothesize that the Os contributed to the performance of the tested catalysts by roughening the surface, whereas Au fulfilled the role of a structural support. Overall, it is demonstrated how machine learning can help accelerate catalyst discovery, and combining machine-learned models obtained from experimental data with models based on DFT calculations can provide important insights into the complex chemistry of OER catalysts.

Nitrogen and phosphorus co-doped porous carbons (NPCs) were successfully prepared by pyrolysis of the mixture of PANI and phytic acid. The synthesized NPCs exhibited excellent degradation abilities to tetracycline (90.34% within 60 mins). Based on the results of quenching experiments and electron paramagnetic resonance (EPR), metastable reactive complexes mediated electron transfer was the major pathway and singlet oxygen (1O2) played an auxiliary role in the TC degradation. Graphitic N, pyridinic N and defects were identified as the catalytic sites. Linear sweep voltammetry, chronoamperometry tests and electrochemical impedance spectroscopy tests revealed that defects as the active sites to form metastable surface-confined reactive species. The density functional theory (DFT) calculations results indicated that the introduction of phosphorus could promote the peroxydisulfate (PDS) adsorption and activation by adjusting the electron density of the carbon skeleton. This study provides new insights into the designation of metal-free PDS activators towards the high-efficiency removal of contaminants. © 2022 Elsevier B.V.

Enabling long cyclability of high-voltage oxide cathodes is a persistent challenge for all-solid-state batteries, largely because of their poor interfacial stabilities against sulfide solid electrolytes. While protective oxide coating layers such as LiNbO3 (LNO) have been proposed, its precise working mechanisms are still not fully understood. Existing literature attributes reductions in interfacial impedance growth to the coating's ability to prevent interfacial reactions. However, its true nature is more complex, with cathode interfacial reactions and electrolyte electrochemical decomposition occurring simultaneously, making it difficult to decouple each effect. Herein, we utilized various advanced characterization tools and first-principles calculations to probe the interfacial phenomenon between solid electrolyte Li6PS5Cl (LPSCl) and high-voltage cathode LiNi0.85Co0.1Al0.05O2 (NCA). We segregated the effects of spontaneous reaction between LPSCl and NCA at the interface and quantified the intrinsic electrochemical decomposition of LPSCl during cell cycling. Both experimental and computational results demonstrated improved thermodynamic stability between NCA and LPSCl after incorporation of the LNO coating. Additionally, we revealed the in situ passivation effect of LPSCl electrochemical decomposition. When combined, both these phenomena occurring at the first charge cycle result in a stabilized interface, enabling long cyclability of all-solid-state batteries.

Enabling long cyclability of high-voltage oxide cathodes is a persistent challenge for all-solid-state batteries, largely because of their poor interfacial stabilities against sulfide solid electrolytes. While protective oxide coating layers such as LiNbO3 (LNO) have been proposed, its precise working mechanisms are still not fully understood. Existing literature attributes reductions in interfacial impedance growth to the coating's ability to prevent interfacial reactions. However, its true nature is more complex, with cathode interfacial reactions and electrolyte electrochemical decomposition occurring simultaneously, making it difficult to decouple each effect. Herein, we utilized various advanced characterization tools and first-principles calculations to probe the interfacial phenomenon between solid electrolyte Li6PS5Cl (LPSCl) and high-voltage cathode LiNi0.85Co0.1Al0.05O2 (NCA). We segregated the effects of spontaneous reaction between LPSCl and NCA at the interface and quantified the intrinsic electrochemical decomposition of LPSCl during cell cycling. Both experimental and computational results demonstrated improved thermodynamic stability between NCA and LPSCl after incorporation of the LNO coating. Additionally, we revealed the in situ passivation effect of LPSCl electrochemical decomposition. When combined, both these phenomena occurring at the first charge cycle result in a stabilized interface, enabling long cyclability of all-solid-state batteries.

Dyads formed by an electron donor unit (D) covalently linked to an electron acceptor (A) by an organic bridge are promising materials as molecular rectifiers. Very recently, we have reported the charge transport measurements across self-assembled monolayers (SAMs) of two D–A systems consisting of the ferrocene (Fc) electron-donor linked to a polychlorotriphenylmethane (PTM) electron-acceptor in its non-radical (SAM 1) and radical (SAM 2) forms. Interestingly, we observed that the non-radical SAM 1 showed rectification behavior of 2 orders of magnitude higher than its radical analogue dyad 2. In order to study the influence of the donor unit on the transport properties, we report herein the synthesis and characterization of two new D–A SAMs in which the electron-donor Fc unit is replaced by a tetrathiafulvalene (TTF) moiety linked to the PTM unit in its non-radical (SAM 3) and radical (SAM 4) forms. The observed decrease in the rectification ratio and increased current density for TTF-PTM based SAMs 3 and 4 in comparison to Fc-PTM based SAMs 1 and 2 are explained, supported by theoretical calculations, by significant changes in the electronic and supramolecular structures.

High-resolution vacuum ultraviolet photoabsorption measurements in the wavelength range of 115-320 nm (10.8-3.9 eV) have been performed together with comprehensive relativistic time-dependent density functional calculations (TDDFT) on the low-lying excited sates of tungsten hexacarbonyl, W(CO). The higher resolution obtained reveals previously unresolved spectral features of W(CO). The spectrum shows two higher-energy bands (in the energy ranges of 7.22-8.12 eV and 8.15-9.05 eV), one of them with clear vibrational structure, and a few lower-energy shoulders in addition to a couple of lower-energy metal-to-ligand charge-transfer (MLCT) bands reported in the literature before. Absolute photoabsorption cross sections are reported and, where possible, compared to previously published results. On the basis of this combined experimental/theoretical study the absorption spectrum of the complex has been totally re-assigned between 3.9 and 10.8 eV under the light of spin-orbit coupling (SOC) effects. The present comprehensive knowledge of the nature of the electronically excited states may be of relevance to estimate neutral dissociation cross sections of W(CO), a precursor molecule in focused electron beam induced deposition (FEBID) processes, from electron scattering measurements.