Heterostructured Pt-PbS Nanobelt Achieves Remarkable Direct Formic Acid Oxidation Catalysis.

Developing efficient and CO-tolerant platinum (Pt)-based anodic catalysts is challenging for a direct formic acid fuel cell (DFAFC). Herein, we report heterostructured Pt-lead-sulfur (PtPbS)-based nanomaterials with gradual phase regulation as efficient formic acid oxidation reaction (FAOR) catalysts. The optimized Pt-PbS nanobelts (Pt-PbS NBs/C) display the mass and specific activities of 5.90 A mgPt-1 and 21.4 mA cm-2, 2.2/1.2, 1.5/1.1, and 36.9/79.3 times greater than those of PtPb-PbS NBs/C, Pt-PbSO4 NBs/C, and commercial Pt/C, respectively. Simultaneously, it exhibits a higher membrane electrode assembly (MEA) power density (183.5 mW cm-2) than commercial Pt/C (40.3 mW cm-2). This MEA stably operates at 0.4 V for 25 h, demonstrating a competitive potential of device application. The distinctive heterostructure endows the Pt-PbS NBs/C with optimized dehydrogenation steps and resisting the CO poisoning, thus presenting the remarkable FAOR performance. This work paves an effective avenue for creating high-performance anodic catalysts for fuel cells and beyond.

Layered Double Hydroxide Derivatives for Polyolefin Upcycling.

While Ru-catalyzed hydrogenolysis holds significant promise in converting waste polyolefins into value-added alkane fuels, a major constraint is the high cost of noble metal catalysts. In this work, we propose, for the first time, that Co-based catalysts derived from CoAl-layered double hydroxide (LDH) are alternatives for efficient polyolefin hydrogenolysis. Leveraging the chemical flexibility of the LDH platform, we reveal that metallic Co species serve as highly efficient active sites for polyolefin hydrogenolysis. Furthermore, we introduced Ni into the Co framework to tackle the issue of restricted hydrogenation ability associated with contiguous Co-Co sites. In-situ analysis indicates that the integration of Ni induces electron transfer and facilitates hydrogen spillover. This dual effect synergistically enhances the hydrogenation/desorption of olefin intermediates, resulting in a significant reduction in the yield of low-value CH4 from 27.1 to 12.6%. Through leveraging the unique properties of LDH, we have developed efficient and cost-effective catalysts for the sustainable recycling and valorization of waste polyolefin materials.

Stable Interfacial Ruthenium Species for Highly Efficient Polyolefin Upcycling.

The present polyolefin hydrogenolysis recycling cases acknowledge that zerovalent Ru exhibits high catalytic activity. A pivotal rationale behind this assertion lies in the propensity of the majority of Ru species to undergo reduction to zerovalent Ru within the hydrogenolysis milieu. Nonetheless, the suitability of zerovalent Ru as an optimal structural configuration for accommodating multiple elementary reactions remains ambiguous. Here, we have constructed stable Ru0-Ruδ+ complex species, even under reaction conditions, through surface ligand engineering of commercially available Ru/C catalysts. Our findings unequivocally demonstrate that surface-ligated Ru species can be stabilized in the form of a Ruδ+ state, which, in turn, engenders a perturbation of the σ bond electron distribution within the polyolefin carbon chain, ultimately boosting the rate-determining step of C-C scission. The optimized catalysts reach a solid conversion rate of 609 g·gRu-1·h-1 for polyethylene. This achievement represents a 4.18-fold enhancement relative to the pristine Ru/C catalyst while concurrently preserving a remarkable 94% selectivity toward valued liquid alkanes. Of utmost significance, this surface ligand engineering can be extended to the gentle mixing of catalysts in ligand solution at room temperature, thus rendering it amenable for swift integration into industrial processes involving polyolefin degradation.

Motivating Inert Strontium Manganate with Iridium Dopants as Efficient Electrocatalysts for Oxygen Evolution in Acidic Electrolyte.

The search for high-performance and low-cost electrocatalysts in acid conditions still remains a challenging target. Herein, iridium (Ir) doped strontium manganate (named as Irx -SMO) is proposed as an efficient and durable low-iridium electrocatalyst for water oxidation in acidic media. The Ir0.1 -SMO with 75% less iridium in comparison to that of iridium dioxide (IrO2 ) exhibits excellent performance for oxygen evolution reaction (OER), which is even better than most of the iridium-based oxide electrocatalysts. The theoretical outcomes confirm the activation of the inert manganese sites in strontium manganate by the incorporation of iridium dopants. This work reveals the boosted effect of the iridium dopants on the OER activity of strontium manganate, providing a strategy to tune the activity of manganese-based perovskites in electrocatalysis.

Strain-induced catalytic enhancement in Co-BTA and Rh-BTA for efficient 2e- oxygen reduction: a DFT study.

Here we design TM-BTA catalysts for the electrochemical synthesis of hydrogen peroxide (H2O2), focusing on the efficient two-electron (2e-) oxygen reduction pathway. Employing density functional theory (DFT), we screened 17 transition metals, identifying Co-BTA and Rh-BTA as outstanding candidates based on their low overpotentials and superior catalytic activity. A key innovation is the application of mechanical strain to these catalysts, significantly optimizing their performance by modulating the d-band center. This approach enhances the adsorption of oxygen-containing intermediates, crucial for the 2e- ORR process. Our findings demonstrate that a tensile strain of 1.95% optimally enhances catalytic efficiency in both Co-BTA and Rh-BTA, substantially reducing overpotential. This research not only highlights the potential of TM-BTA catalysts in H2O2 production but also underscores the importance of strain modulation as a cost-effective and efficient method to improve the selectivity and activity of electrocatalysts, offering a novel perspective in the field of sustainable chemical synthesis.

Influence factors of CO adsorption on C2N-supported dual-atom catalysts unveiled by machine learning and twofold feature engineering.

Dual-atom catalysts (DACs) have emerged as a compelling frontier in the realm of the electrochemical carbon dioxide reduction reaction (CO2RR). However, elucidating the intrinsic properties of dual-atom pairs and their direct correlation with catalytic activity poses significant challenges. Herein, we investigate CO adsorption on 248 kinds of C2N-supported DACs and analyze the underlying structure-activity relationships of dual transition metal (TM) atoms based on density functional theory (DFT) calculations and machine learning (ML) models. Compared to the direct input of atomic features in the decision tree model of ML, we confirm that extra feature engineering with the introduction of the arithmetic combination of atomic features can better reflect the correlation of dual TM atoms on C2N-based DACs. Further feature importance analysis reveals a strong relationship between the last one occupied orbital radius (rv), group number (G) for dual TM atoms and the CO binding strength, as well as a potential connection with the d band centre (εd). Our work provides deeper insights into the design of DACs and highlights the significance of twofold feature engineering for the synergistic effects between dual TM atoms.

Continuous Phase Regulation of a Pd-Te Hexagonal Nanoplate Library.

Phase regulation of noble metal-based nanomaterials provides a promising strategy for boosting the catalytic performance. However, realizing the continuous phase modulation in two-dimensional structures and unveiling the relevant structure-performance relationship remain significant challenges. In this work, we present the first example of continuous phase modulation in a library of Pd-Te hexagonal nanoplates (HNPs) from cubic-phase Pd4Te, rhombohedral-phase Pd20Te7, rhombohedral-phase Pd8Te3, and hexagonal-phase PdTe to hexagonal-phase PdTe2. Notably, the continuous phase regulation of the well-defined Pd-Te HNPs enables the successful modulation of the distance between adjacent Pd active sites, triggering an exciting way for tuning the relevant catalytic reactions intrinsically. The proof-of-concept oxygen reduction reaction (ORR) experiment shows a Pd-Pd distance-dependent ORR performance, where the hexagonal-phase PdTe HNPs present the best electrochemical performance in ORR (mass activity and specific activity of 1.02 A mg-1Pd and 1.83 mA cm-2Pd at 0.9 V vs RHE). Theoretical investigation reveals that the increased Pd-Pd distance relates to the weak *OH adsorption over Pd-Te HNPs, thus contributing to the remarkable ORR activity of PdTe HNPs. This work advances the phase-controlled synthesis of noble metal-based nanostructures, which gives huge impetus to the design of high-efficiency nanomaterials for diverse applications.

Multidentate Molecule Anchoring Halide Perovskite Surface and Regulating Crystallization Kinetics toward Efficient Light-Emitting Diodes.

Functional passivators are conventionally utilized in modifying the crystallization properties of perovskites to minimize the non-radiative recombination losses in perovskite light-emitting diodes (PeLEDs). However, the weak anchor ability of some commonly adopted molecules has limited passivation ability to perovskites and even may desorb from the passivated defects in a short period of time, which bring about plenty of challenges for further development of high-performance PeLEDs. Here, a multidentate molecule, formamidine sulfinic acid (FSA), is introduced as a novel passivator to perovskites. FSA has multifunctional groups (S≐O, C≐N and NH2 ) where the S≐O and C≐N groups enable coordination with the lead ions and the NH2 interacts with the bromide ions, thus providing the most effective chemical passivation for defects and in turn the formation of highly stable perovskite emitters. Moreover, the interaction between the FSA and octahedral [PbBr6 ]4- can inhibit the formation of unfavorable low-n domains to further minimize the inefficient energy transfer inside the perovskite emitters. Therefore, the FSA passivated green-emitting PeLED exhibits a high external quantum efficiency (EQE) of 26.5% with fourfold enhancement in operating lifetime as compared to the control device, consolidating that the multidentate molecule is a promising strategy to effectively and sustainably passivate the perovskites.

Structural stability, dihydrogen bonding, and pressure-induced polymorphic transformations in hydrazine borane.

Hydrazine borane (N2H4BH3) has attracted considerable interest as a promising solid-state hydrogen storage material owing to its high hydrogen content and easy preparation. In this work, pressure-induced phase transitions of N2H4BH3 were investigated using a combination of vibrational spectroscopy, X-ray diffraction, and density functional theory (DFT) up to 30 GPa. Our results showed that N2H4BH3 exhibits remarkable structural stability in a very broad pressure region up to 15 GPa, and then two phase transitions were identified: the first one is from the ambient-pressure Pbcn phase to a Pbca phase near 15 GPa; the second is from the Pbca phase to a Pccn phase near 25 GPa. As revealed by DFT calculations, the unusual stability of N2H4BH3 and the late phase transformations were attributed to the pressure-mediated evolutions of dihydrogen bonding frameworks, the compressibility and the enthalpies of the high-pressure polymorphs. Our findings provide new insight into the structures and bonding properties of N2H4BH3 that are important for hydrogen storage applications.

Unexpected electro-catalytic activity of the CO reduction reaction on Cr-embedded poly-phthalocyanine realized by strain engineering: a computational study.

The electrochemical conversion of carbon monoxide (CO) into value-added products is highly promising for carbon utilization and CO removal. Based on previous theoretical studies, we computationally explored the effect of strain engineering on electrocatalysis of the CO reduction reaction (CORR) by two-dimensional (2D) transition metal embedded polyphthalocyanines (MPPcs). By calculating the adsorption energy of CO and the free energies of key intermediates on the MPPcs under uniaxial and biaxial strains, it was revealed that only CrPPc under biaxial strain has the potential to exhibit significant enhancement of the catalytic performance. The free energy diagrams of the CORR catalyzed by CrPPc were plotted under specific biaxial strains, where both the optimal reaction pathway and rate-determining step are found to be evidently changed. What's more, the 5% compressive strain imposed on CrPPc results in an ultra-low limiting potential (UL = -0.09 V) with high selectivity on CH4 as the final product, indicating unexpected electro-catalytic activity. Our study clearly elucidates that moderate strain could greatly enhance the electrocatalytic performance of 2D materials in the CORR.

SLI-GNN: A Self-Learning-Input Graph Neural Network for Predicting Crystal and Molecular Properties.

Since the structures of crystals/molecules are often non-Euclidean data in real space, graph neural networks (GNNs) are regarded as the most prospective approach for their capacity to represent materials by graph-based inputs and have emerged as an efficient and powerful tool in accelerating the discovery of new materials. Here, we propose a self-learning-input GNN framework, named self-learning-input GNN (SLI-GNN), to uniformly predict the properties for both crystals and molecules, in which we design a dynamic embedding layer to self-update the input features along with the iteration of the neural network and introduce the Infomax mechanism to maximize the average mutual information between the local features and the global features. Our SLI-GNN can reach ideal prediction accuracy with fewer inputs and more message passing neural network (MPNN) layers. The model evaluations on the Materials Project dataset and QM9 dataset verify that the overall performance of our SLI-GNN is comparable to that of other previously reported GNNs. Thus, our SLI-GNN framework presents excellent performance in material property prediction, which is thereby promising for accelerating the discovery of new materials.

Chiral Carbon Dots Derived from Serine with Well-Defined Structure and Enantioselective Catalytic Activity.

Carbon dots (C-Dots), with unique properties from tunable photoluminescence to biocompatibility, show wide applications in biotechnology, optoelectronic device and catalysis. Chiral C-Dots are expected to have strongly chirality-dependent biological and catalytic properties. For chiral C-Dots, a clear structure and quantitative structure-property relationship need to be clarified. Here, chiral C-Dots were fabricated by electrooxidation polymerization from serine enantiomers. The oxidized serine has a reversed chiral configuration to serine, which leads to the chiral C-Dots possessing inverse handedness compared with their raw materials. Electron circular dichroism spectrum, together with other diverse characterization techniques and theoretical calculations, confirmed that these chiral C-Dots (2-7 nm) have a well-defined primary structure of polycyclic dipeptide and possess a spatial structure with a c-axis of hexagonal symmetry and two cyclic dipeptides as the spatial structural unit. These chiral C-Dots also show enantioselective catalytic activity on DOPA enantiomers oxidation.

Ligand-Assisted Coupling Manipulation for Efficient and Stable FAPbI3 Colloidal Quantum Dot Solar Cells.

For emerging perovskite quantum dots (QDs), understanding the surface features and their impact on the materials and devices is becoming increasingly urgent. In this family, hybrid FAPbI3 QDs (FA: formamidium) exhibit higher ambient stability, near-infrared absorption and sufficient carrier lifetime. However, hybrid QDs suffer from difficulty in modulating surface ligand, which is essential for constructing conductive QD arrays for photovoltaics. Herein, assisted by an ionic liquid formamidine thiocyanate, we report a facile surface reconfiguration methodology to modulate surface and manipulate electronic coupling of FAPbI3 QDs, which is exploited to enhance charge transport for fabricating high-quality QD arrays and photovoltaic devices. Finally, a record-high efficiency approaching 15 % is achieved for FAPbI3 QD solar cells, and they retain over 80 % of the initial efficiency after aging in ambient environment (20-30 % humidity, 25 °C) for over 600 h.

Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power.

Protein kinases have been regarded as important therapeutic targets for many diseases. Currently, a total of 41 kinase inhibitors have been approved by the Food and Drug Administration, along with a large number of kinase inhibitors being evaluated in clinical and preclinical trials. Among all, allosteric inhibitors, such as type II kinase inhibitors, have attracted extensive attention owing to their potential high selectivity. Nowadays, molecular docking has become a powerful tool to search for novel kinase inhibitors. However, as for type II kinase inhibitors, their allosteric characteristics may exert a deep influence on docking accuracy. In this study, a comprehensive assessment was conducted to evaluate the effectiveness of nine docking algorithms towards type II kinase inhibitors. The calculation results showed that most tested docking programs, especially Glide with XP scoring, LeDock and Surflex-Dock, succeeded in the accurate identification of near-native binding poses, with the success rates ranging from 0.80 to 0.90, and the scoring functions in GOLD and LeDock outperformed the others in the prediction of relative binding affinities. In terms of the P-values, areas under the curve and enrichment factors, Glide with XP scoring, Surflex-Dock, GOLD with Astex Statistical Potential scoring and LeDock had better screening power to discriminate between active compounds and decoys. However, the screening power is sensitive to different initial conformations of the same target. It is expected that our study can provide some guidance for docking-based virtual screening to discover novel type II kinase inhibitors, as well as other allosteric inhibitors.

Layer-stacking of chalcogenide-terminated MXenes Ti2CT2(T = O, S, Se, Te) and their applications in metal-ion batteries.

Owning to limited supply of lithium for Li-ion batteries, the development of non-Li-ion batteries (such as Na+, K+Mg2+, Ca2+, and Al3+ion batteries) has attracted significant research interest. In this work, by means of the first-principles calculations, we systematically investigated the performance of chalcogenide-terminated MXenes Ti2CT2(T = O, S, Se, and Te) as electrodes for Li-ion and non-Li-ion batteries, as well as the layer-stacking and electronic properties of Ti2CT2. We find that the stacking type of O and Te terminated Ti2C multilayers with AA stacking differs from that of S and Se terminated Ti2C multilayers with AB stacking. More importantly, Ti2CO2monolayer can be potential anode material for Na- and K-ion batteries with high capacities and very low diffusion barriers (0.03-0.11 eV), while Ti2CS2and Ti2CSe2are promising anode materials with relatively low average open circuit voltages (OCVs) for Na-, K-, and Ca-ion batteries (0.4-0.87 V). Among these materials, Ti2CS2exhibits the largest ion capacity of 616 mAh g-1. These results of our work may inspire further studies of Ti2C-MXenes multilayers as electrodes for metal-ion batteries either experimentally or theoretically.

Prediction of SiS2 and SiSe2 as promising anode materials for sodium-ion batteries.

In this work, we suggest SiS2 and SiSe2 as anode materials for sodium-ion batteries based on a first-principles prediction. Both SiS2 and SiSe2 have suitable adsorption energies (-1.01/-1.24 eV) and large diffusion constants (1.24 × 10-4/6.72 × 10-5 cm2 s-1) for Na ions at 300 K, resulting in low diffusion barriers (less than 0.1 eV) at high Na adsorption concentrations. As anode materials, SiS2 and SiSe2 exhibit excellent electrochemical stability with high theoretical capacities (517/864 mA h g-1) and desirable average voltages (0.19/0.25 V). Given these exceptional properties, SiS2 and SiSe2 are desired to be promising electrode materials for sodium-ion batteries.

Turning the structure of the Aß42 peptide by different functionalized carbon nanotubes: a molecular dynamics simulation study.

Functionalized carbon nanotubes (CNTs) can inhibit the self-assembly of amyloid-beta (Aß) peptides. Under abnormal conditions, the structure of the Aß peptides undergoes a fundamental transformation, and this transformation will induce conformational conversions of other polymerized Aß peptides. Here, we explore the interactions between different functionalized CNTs and Aß42 peptides by molecular dynamics simulations. Our results show that compared to the original CNTs, the highly functionalized CNTs induce different adsorption patterns of the peptides. This adsorption pattern destroys the α-helix structure and increases the ß-turn and random coil content significantly. The hydrogen bonds formed by the peptide and water molecules or CNTs further reveal the reasons for the structural transformation of the peptide. Due to electrostatic interactions and π-π stacking interactions, some amino acids (such as Phe4, Lys16, Phe20, and Lys28) are tightly fixed on the surfaces, and other amino acids move around these amino acids to accelerate the unfolding and denaturation of the peptide. Our research shows that functionalized CNTs have excellent potential to inhibit the abnormal aggregation of Aß42 peptides. Our research also provides theoretical guidance in the design and synthesis of carbon nanomedicines for protein conformation diseases.

Significance of density functional theory (DFT) calculations for electrocatalysis of N2 and CO2 reduction reactions.

Density functional theory (DFT) based computational methods have shown great significance in developing high-performance electrocatalysts. In this perspective, we briefly summarized the state-of-the-art research progress of electrocatalysts for the nitrogen reduction reaction (NRR) and CO2 reduction reaction (CO2RR), which are important processes for the conversion of common molecules into value-added products. With the help of DFT calculations, various modulation strategies are employed to improve the catalytic activity and performance of NRR and CO2RR electrocatalysts. DFT calculations are performed to confirm the surface catalytic sites, evaluate the catalytic activity, reveal the possible reaction mechanisms, and design novel structures with high catalytic performance. By discussing the currently applied computational methods and conditions during the calculations, we outlined our concerns on the prospects and future challenges of DFT calculations in electrocatalysis studies.

Tuning low-temperature CO oxidation activities via N-doping on graphene-supported three-coordinated nickle single-atom catalysts.

Nitrogen doping is identified as an intriguing way to regulate graphene-supported single-atom catalysts (SACs) for heterogeneous catalysis. However, little theoretical effort has been directed towards exploring the activity trend in terms of N-doping level. In this study, we systematically investigated the N-doping effect on CO oxidation activities for graphene-supported three-coordinated Ni SACs (Ni-NxC3-x) in virtue of density functional theory (DFT) calculations and microkinetic modeling. We found that N-doping will shift the d-band center of single-atom Ni upwards, enhance the adsorption of intermediates, and tune the activation barrier to the overall reaction activities. Ni-N1C2 exhibits excellent catalytic performance with the highest total reaction rate comparable to that of noble metal SACs. These findings are helpful for understanding the N-doping influence and rationalizing the art of designing novel SACs for CO oxidation at low temperatures.

Monoatomic Platinum-Embedded Hexagonal Close-Packed Nickel Anisotropic Superstructures as Highly Efficient Hydrogen Evolution Catalyst.

The rational design of platinum (Pt) based nanostructures with specific crystal structure plays a significant role in their diverse applications. Herein, the anisotropic superstructures (ASs) of monoatomic Pt-embedded hexagonal close-packed nickel (hcp Ni) nanosheets were successfully synthesized for efficient hydrogen evolution in which an unusual dissociation-diffusion-desorption mechanism played a crucial role. The overpotential for the Pt/Ni ASs to reach the specific current density (10 mA cm-2) is 28.0 mV, which is much lower than that of conventional Pt/C catalyst (71.0 mV). Moreover, at the overpotential of 100 mV, the mass activity of 30.2 A mgPt-1 for the Pt/Ni ASs is 1060% greater than that in conventional Pt/C catalyst (2.6 A mgPt-1). This work provides a new approach to synthesize highly anisotropic superstructures embedded with monoatomic noble metals to boost their hopeful applications in catalytic applications.