A General Strategy for Synthesis of Binary Transition Metal Phosphides Hollow Sandwich Heterostructures.

The hollow sandwich core-shell micro-nanomaterials are widely used in materials, chemistry, and medicine, but their fabrication, particularly for transition metal phosphides (TMPs), remains a great challenge. Herein, a general synthesis strategy is presented for binary TMPs hollow sandwich heterostructures with vertically interconnected nanosheets on the inside and outside surfaces of polyhedron FeCoPx /C, demonstrated by a variety of transition metals (including Co, Fe, Cd, Mn, Cu, Cr, and Ni). Density functional theory (DFT) calculation reveals the process and universal mechanism of layered double hydroxide (LDH) growth on Prussian blue analog (PBA) surface in detail for the first time, which provides the theoretical foundations for feasibility and rationality of the synthesis strategy. This unique structure exhibits a vertical nanosheet-shell-vertical nanosheet configuration combining the advantages of sandwich, hollow and vertical heterostructures, effectively achieving their synergistic effect. As a proof-of-concept of their applications, the CoNiPx @FeCoPx /C@CoNiPx hollow sandwich polyhedron architectures (representative samples) show excellent catalytic performance for the oxygen evolution reaction (OER) in alkaline electrolytes. This work provides a general method for constructing hollow-sandwich micro-nanostructures, which provides more ideas and directions for design of micro-nano materials with special geometric topology.

A geometry-enhanced graph neural network for learning the smoothness of glassy dynamics from static structure.

Modeling the dynamics of glassy systems has been challenging in physics for several decades. Recent studies have shown the efficacy of Graph Neural Networks (GNNs) in capturing particle dynamics from the graph structure of glassy systems. However, current GNN methods do not take the dynamic patterns established by neighboring particles explicitly into account. In contrast to these approaches, this paper introduces a novel dynamical parameter termed "smoothness" based on the theory of graph signal processing, which explores the dynamic patterns from a graph perspective. Present graph-based approaches encode structural features without considering smoothness constraints, leading to a weakened correlation between structure and dynamics, particularly on short timescales. To address this limitation, we propose a Geometry-enhanced Graph Neural Network (Geo-GNN) to learn the smoothness of dynamics. Results demonstrate that our method outperforms state-of-the-art baselines in predicting glassy dynamics. Ablation studies validate the effectiveness of each proposed component in capturing smoothness within dynamics. These findings contribute to a deeper understanding of the interplay between glassy dynamics and static structure.

Pattern Formation under Deep Supercooling by Classical Density Functional-Based Approach.

Solidification patterns during nonequilibrium crystallization are among the most important microstructures in the natural and technical realms. In this work, we investigate the crystal growth in deeply supercooled liquid using the classical density functional-based approaches. Our result shows that the complex amplitude expanded phase-field crystal (APFC) model containing the vacancy nonequilibrium effects proposed by us could naturally reproduce the growth front nucleation (GFN) and various nonequilibrium patterns, including the faceted growth, spherulite, symmetric and nonsymmetric dendrites among others, at the atom level. Moreover, an extraordinary microscopic columnar-to-equiaxed transition is uncovered, which is found to depend on the seed spacing and distribution. Such a phenomenon could be attributed to the combined effects of the long-wave and short-wave elastic interactions. Particularly, the columnar growth could also be predicted by an APFC model containing inertia effects, but the lattice defect type in the growing crystal is different due to the different types of short-wave interactions. Two stages are identified during the crystal growth under different undercooling, corresponding to diffusion-controlled growth and GFN-dominated growth, respectively. However, compared with the second stage, the first stage becomes too short to be noticed under the high undercooling. The distinct feature of the second stage is the dramatic increments of lattice defects, which explains the amorphous nucleation precursor in the supercooled liquid. The transition time between the two stages at different undercooling is investigated. Crystal growth of BCC structure further confirms our conclusions.

Unraveling TM Migration Mechanisms in LiNi1/3Mn1/3Co1/3O2 by Modeling and Experimental Studies.

Electrochemical cycling induces transition-metal (TM) ion migration and oxygen vacancy formation in layered transition-metal oxides, thus causing performance decay. Here, a combination of ab initio calculations and atomic level imaging is used to explore the TM migration mechanisms in LiNi1/3Mn1/3Co1/3O2 (NMC333). For the bulk model, TM/Li exchange is an favorable energy pathway for TM migration. For the surface region with the presence of oxygen vacancies, TM condensation via substitution of Li vacancies (TMsub) deciphers the frequently observed TM segregation phenomena in the surface region. Ni migrates much more easily in both the bulk and surface regions, highlighting the critical role of Ni in stabilizing layered cathodes. Moreover, once TM ions migrate to the Li layer, it is easier for TM ions to diffuse and form a TM-enriched surface layer. The present study provides vital insights into the potential paths to tailor layered cathodes with a high structural stability and superior performance.

Selective hydrogenation of acetylene on Cu-Pd intermetallic compounds and Pd atoms substituted Cu(111) surfaces.

The selective hydrogenation of acetylene was studied on the ordered Cu-Pd intermetallic compounds (L10-type CuPd, L12-type Cu3Pd, and L12-type CuPd3) and Pd-modified Cu(111) surfaces through first-principles calculations. The catalytic selectivity and activity of Cu-Pd alloy catalysts are closely related to the crystal structure and composition of Cu-Pd intermetallic compounds and the size of Pd ensembles of Cu-based dilute alloy surface for the selective hydrogenation of acetylene to ethylene. Significantly, we found that the ordered Cu-Pd alloy surface containing isolated Pd atoms (i.e., L12-type Cu3Pd(111) surface) is highly efficient for the selective hydrogenation reaction of C2H2 + H2→ C2H4. The contiguous Pd atom ensembles (Pd dimer and trimer) are catalytically active towards C2H2 + H → C2H3 and C2H3 + H → C2H4 reactions than the single Pd atom on a Pd-decorated Cu(111) surface. However, the small Pd ensembles on Cu(111) present a low chemical activity for H2 dissociation compared with the ordered Cu-Pd intermetallic compounds. Our theoretical results provide a strategy of crystal phase and composition control for enhancing the selectivity and activity of Cu-Pd catalysts towards acetylene selective hydrogenation.

A design rule for two-dimensional van der Waals heterostructures with unconventional band alignments.

The energetic alignment of band edges at the interface plays a central role in determining the properties and applications of two-dimensional (2D) van der Waals (vdW) heterostructures. Generally, three conventional heterojunction types (type-I, type-II, and type-III) have widely been investigated and used in diverse fields. Unconventional band alignments (type-IV, type-V, and type-VI) are, however, hitherto unreported in the vdW heterostructures. We find that 2D binary semiconductors composed of group IV-V elements manifest a similar electronic structure, offering in principle the possibility of designing heterostructures with novel band alignments due to the hybridization of band-edge states. We first show here that a 2D SiAs/GeP heterostructure exhibits a type-VI band alignment, which is induced by the interlayer pz orbital hybridization, and a transition of band alignment from type-VI to type-V occurs when strain or electric field is applied over a critical value. The unconventional band alignments and their transition natures enable broad application of these vdW heterostructures in special opto-electronic devices and energy conversion.

Assessment of van der Waals inclusive density functional theory methods for adsorption and selective dehydrogenation of formic acid on Pt(111) surface.

In this work, we studied the adsorption and catalytic dehydrogenation of formic acid (HCOOH) on Pt(111) surface using different van der Waals inclusive density functional theory (DFT) methods. Our results indicate that the PBE + dDsC method has the best overall performance on the description of adsorption and catalytic selectivity. We found the improved van der Waals (vdW) corrected methods (PBE + D3, PBE + TS, PBE + TS-SCS, PBE + TS/IH, PBE + MBD@rsSCS, and PBE + dDsC) and optimized vdW functionals (optPBE-vdW, optB88-vdW, and optB86b-vdW) perform well to estimate the adsorption energies of HCOOH and HCOO molecules on Pt(111) surface. The vdW-inclusive DFT approaches as well as the conventional PBE functional predict a higher activation barrier for C-H breaking by comparison of O-H breaking in the selective dehydrogenation of formic acid. However, the optimized vdW functionals evidently underestimate the rate constant of C-H breaking reaction, and then fail to describe the catalytic selectivity of the HCOOH's dehydrogenation. Both PBE + dDsC and PBE predict a similar temperature dependence of the ratio of reaction rate constants for O-H breaking versus C-H breaking, though PBE functional underestimate the adsorption energies.

Molecular dynamics simulations of shock loading of nearly fully dense granular Ni-Al composites.

We used molecular dynamics simulations to study the shock propagation, inhomogeneous deformation, and initiation of the chemical reaction characteristics of nearly fully dense reactive Ni-Al composites. For shocks with piston velocities Up ≤ 2.0 km s-1, particle velocity dispersion was observed at the shock front, which increased on increasing the shock strength. Plastic deformation mainly occurred at the grain boundaries or grain junction during the shock rise and was accompanied by the generation of a potential hot spot in the region where severe plasticity happens. The composite exhibited higher strength and lower reactivity than the mixtures with certain porosity. In addition, the shock-induced premature melting of Al led to the expansion of particle velocity dispersion from the wavefront to the shocked zone and the formation of a heterogeneous velocity field for stronger shocks beyond critical Up (2.5 km s-1). The velocity heterogeneity in the shocked region led to localized shear, strong erosion of Ni, and occurrence of ultrafast chemical reactions. Therefore, the shock-induced premature melting of Al led to the mechanochemical effect and played a role in the shock-induced chemical reaction in the reactive metal system.

Effect of particle packing and density on shock response in ordered arrays of Ni + Al nanoparticles.

We investigate the shock response of Ni + Al reactive nanoparticle systems through molecular dynamics simulations. The powder configurations with varying arrangements and densities are constructed by stacking equal-sized Ni and Al particles based on five typical crystal structures, i.e., zinc-blende, NaCl, CsCl, AuCu and the close-packed. The effects of configuration and shock strength on mechanochemical and diffusion processes in the shock-induced chemical reactions are characterized. A reaction kinetic model is developed to describe these behaviors, assess the extent of mechanochemical effect, and explain the occurrence of ultra-fast reaction. Significant dependence of shock wave velocity, plastic deformation, temperature response, chemistry and microstructure change on particle packing and density is observed under shock loading at the same piston velocity, but we see a relatively weak dependency on the stacking mode with the same density. Our results indicate the important role of particle coordination number and density in shock response of energetic powder materials.

Intrinsic strain-induced segregation in multiply twinned Cu-Pt icosahedra.

We present an atomistic simulation study on the compositional arrangements throughout Cu-Pt icosahedra, with a specific focus on the effects of inherent strain on general segregation trends. The coexistence of radial and site-selective segregation patterns is found in bimetallic nanoparticles for a broad range of sizes and compositions, consistent with prior analytical and atomistic models. Through a thorough comparison between the composition patterns and strain-related patterns, it is suggested that the presence of gradient and site-selective segregation is natural to largely relieve the inherent strain by preferential segregation of big atoms at tensile sites and vice versa, as previously hypothesized in the literature. Analogous to the case of single crystal particles, Cu-rich surface and damped oscillations can also be found in the outer shells of icosahedra, which are dominated by the lowering of both the surface energy and the chemical energy. The thermodynamic stability of segregated icosahedra is similar to segregated cuboctahedra but higher than disordered bulk alloys, validating prior thinking that element segregation driven by strain relief can extend the stability range of multiply-twinned nanoparticles. Our work sheds new light on understanding strain-induced segregation in multiply-twinned nanosystems that have elements with large lattice mismatch and strong alloying ability.

Interfacial Interactions in Monolayer and Few-Layer SnS/CH3 NH3 PbI3 Perovskite van der Waals Heterostructures and Their Effects on Electronic and Optical Properties.

A high light-absorption coefficient and long-range hot-carrier transport of hybrid organic-inorganic perovskites give huge potential to their composites in solar energy conversion and environmental protection. Understanding interfacial interactions and their effects are paramount for designing perovskite-based heterostructures with desirable properties. Herein, we systematically investigated the interfacial interactions in monolayer and few-layer SnS/CH3 NH3 PbI3 heterostructures and their effects on the electronic and optical properties of these structures by density functional theory. It was found that the interfacial interactions in SnS/CH3 NH3 PbI3 heterostructures were van der Waals (vdW) interactions, and they were found to be insensitive to the layer number of 2D SnS sheets. Interestingly, although their band gap decreased upon increasing the layer number of SnS, the near-gap electronic states and optical absorption spectra of these heterostructures were found to be strikingly similar. This feature was determined to be critical for the design of 2D layered SnS-based heterostructures. Strong absorption in the ultraviolet and visible-light regions, type II staggered band alignment at the interface, and few-layer SnS as an active co-catalyst make 2D SnS/CH3 NH3 PbI3 heterostructures promising candidates for photocatalysis, photodetectors, and solar energy harvesting and conversion. These results provide first insight into the nature of interfacial interactions and are useful for designing hybrid organic-inorganic perovskite-based devices with novel properties.

Theoretical prediction of LiScO2 nanosheets as a cathode material for Li-O2 batteries.

Our previous study (J. Mater. Chem. A, 2018, 6, 3171-3180) theoretically predicted that a scandium oxide (ScO2) monolayer can deliver high specific capacity and energy density as the active material of a lithium-ion (Li-ion) battery, but the voltage will drop below 0.5 V when ScO2 is lithiated to LiScO2 during the discharge process. The current study predicts that the discharge product LiScO2 in the Li-ion battery mode can potentially work as the host material of Li-O2 batteries. It is found that the adsorption of O2 on the LiScO2 substrate is energetically favored. The LiScO2 substrate can also provide strong affinities to molecular LiO2 and Li2O2 species. It is interesting to find that the presence of an O2 molecule can oxidize the pre-adsorbed Li2O2 molecule and result in two LiO2 molecules. Hence, the final discharge product of the Li-O2 battery using the LiScO2 cathode is expected to be a crystalline-like LiO2 layer. The discharge voltage related to forming a LiO2 layer on the LiScO2 substrate is 3.50 V vs. Li+/Li according to the present theoretical calculation.

Revealing reaction mechanisms of nanoconfined Li2S: implications for lithium-sulfur batteries.

Using Li2S as an active material and designing nanostructured cathode hosts are considered as promising strategies to improve the performance of lithium-sulfur (Li-S) batteries. In this study, the reaction mechanisms during the delithiation of nanoconfined Li2S as an active material, represented by a Li20S10 cluster, are examined by first-principles based calculations and analysis. Local reduction and disproportionation reactions can be observed although the overall delithiation process is an oxidation reaction. Long-chain polysulfides can form as intermediate products; however they may bind to insoluble S2-via Li atoms as mediators. Activating the charging process only requires an overpotential of 0.37 V if using Li20S10 as the active material. Sulfur allotropes longer than cyclo-S8 are observed at the end of the charge process. Although the discharge voltage of Li20S10 is only 1.27 V, it can still deliver an appreciable theoretical energy density of 1480 W h kg-1. This study also suggests that hole polarons, in Li20S10 and intermediate products, can serve as carriers to facilitate charge transport. This work provides new insights toward revealing the detailed reaction mechanisms of nanoconfined Li2S as an active material in the Li-S battery cathode.

Investigation of the shock-induced chemical reaction (SICR) in Ni + Al nanoparticle mixtures.

Molecular dynamics (MD) simulations are used to investigate the shock-compression response of Ni + Al spherical nanoparticles arranged in a NaCl-like structure. The deformation and reaction characteristics are studied from the particle level to the atomic scale at various piston velocities. Shock-induced chemical reactions (SICRs) occur during non-equilibrium processes, accompanied by a sharp rise in temperature and rapid mixing of atoms. The preferentially deformed Al particles form a high-speed mass flow relative to the Ni at the shock front, which impinges on the Ni particles, and mixing of Ni and Al atoms occurs immediately at the interface. The particle velocity dispersion (PVD) that appears at the shock front has important implications for the initiation of shock-induced chemical reactions. We show that dislocations are mainly generated at the beginning of particle deformation or at the shock front, and do not directly affect the occurrence of SICRs. The intimate contact of the molten Al and the amorphous Ni is found to be critical to the subsequent reactions for the extensive mixing of Ni and Al. We conclude that the mechanisms of SICRs involve mechanochemical processes near the shock front and subsequent interdiffusion processes.

Simultaneous covalent and noncovalent carbon nanotube/Ag3PO4 hybrids: new insights into the origin of enhanced visible light photocatalytic performance.

Understanding the interfacial interaction is of paramount importance for rationally designing carbon nanomaterial-based hybrids with optimal performance for electronics, optoelectronics, sensing, advanced energy conversion and storage. Here, we firstly reveal that both covalent and noncovalent interactions simultaneously exist in carbon nanotube (CNT)/Ag3PO4 hybrids by studying systematically the electronic and optical properties to elucidate the mechanism of their enhanced photocatalytic performance. Metallic CNT(9,0) may chemically or physically interact with the Ag3PO4(100) surface depending on its relative orientations, whereas semiconducting CNT(10,0) can only noncovalently functionalize Ag3PO4. The C-Ag bond in the covalently bonded hybrid and type-II, staggered, band alignment in noncovalent hybrids lead to a robust separation of photoexcited charge carriers between two constituents, thus enhancing the photocatalytic activity. The small band gap makes the CNT/Ag3PO4 hybrids absorb sunlight from the ultraviolet to infrared region. Moreover, CNTs are not only effective sensitizers, but also highly active co-catalysts in hybrids. The results can be rationalized by the available experiments, thereby partly resolving a debate on the interpretation of the experimental results, and paving the way for developing highly efficient carbon-based nanophotocatalysts.

Enhanced photocatalytic performance of an Ag3PO4 photocatalyst via fullerene modification: first-principles study.

The coupling of carbon nanomaterials with semiconductor photocatalysts is a promising route to improve their photocatalytic performance. Herein, density functional theory was used to investigate the electronic structure, charge transfer, photocatalytic activity, and stability in a series of hybrid fullerene (C20, Li@C20, C26, Li@C26)/Ag3PO4(100) composites. When a Li atom is incorporated in fullerene, the adsorption energies significantly increase, although the change of interface distance is negligibly small due to the weak interface interaction. The charge transfer between constituents decreases with the C atom number of fullerene. Compared to pure Ag3PO4, the band gap of the composites is smaller, which enhances the visible-light absorption and photoinduced electron transfer. Most importantly, a type-II, staggered band alignment could be obtained in the C26-Ag3PO4(Li@C26-Ag3PO4) interface, leading to significantly reduced charge recombination and thus enhanced photocatalytic activity. These results reveal that fullerene modification would be an effective strategy to improve the photocatalytic performance of Ag3PO4 semiconductor photocatalysts.

Amorphization and thermal stability of aluminum-based nanoparticles prepared from the rapid cooling of nanodroplets: effect of iron addition.

Despite an intensive investigation on bimetallic nanoparticles, little attention has been paid to their amorphization in the past few decades. The study of amorphization on a nanoscale is of considerable significance for the preparation of amorphous nanoparticles and bulk metallic glass. Herein, we pursue the amorphization process of Al-based nanoparticles with classic molecular dynamics simulations and local structural analysis techniques. By a comparative study of the amorphization of pure Al and Fe-doped Al-based nanodroplets in the course of rapid cooling, we find that Fe addition plays a very important role in the vitrification of Al-based nanodroplets. Owing to the subsurface segregated Fe atoms with their nearest neighbors tending to form relatively stable icosahedral (ICO) clusters, the Fe-centred cluster network near the surface effectively suppresses the crystallization of droplets from surface nucleation and growth as the concentration of Fe attains a certain value. The glass formation ability of nanodroplets is suggested to be enhanced by the high intrinsic inner pressure as a result of small size and surface tension, combined with the dopant-inhibited surface nucleation. In addition, the effect of the size and the added concentration of nanoparticles on amorphization and the thermal stability of the amorphous nanoparticles are discussed. Our findings reveal the amorphization mechanism in Fe-doped Al-based nanoparticles and provide a theoretical guidance for the design of amorphous materials.

Toward Interpreting the Thermally Activated ß Dynamics in Metallic Glass Using the Structural Constraint Neural Network.

It is crucial to unravel the structural factors influencing the dynamics of the amorphous solids. Deep learning aids in navigating these complexities, while transparency issues persist. Drawing inspiration from the successful application of prototype neural networks in image analysis, this study introduces a novel machine learning approach to address interpretability challenges in glassy research. Distinguishing from traditional machine learning models, the proposed neural network tries to learn distant structural motifs for solid-like atoms and liquid-like atoms. Such learned structural motifs constrain the underlying structural space and thus can serve as a breakthrough in explaining how structural differences impact dynamics. We further used the proposed model to explore the correlation between the local structure and activation energy in the CuZr alloys. Building upon this interpretable model, we demonstrated significant structural differences among atoms with different activation energies. Our interpretable model is a data-driven solution that provides a pathway to reveal the origin of structural heterogeneity in amorphous alloys.

Dipole Effect on Oxygen Evolution Reaction of 2D Janus Single-Atom Catalysts: A Case of Rh Anchored on the P6m2-NP Configurations.

Catalytic performance of single-atom catalysts (SACs) relies fundamentally on the electronic nature and local coordination environment of the active site. Here, based on a machine-learning (ML)-aided density functional theory (DFT) method, we reveal that the intrinsic dipole in Janus materials has a significant impact on the catalytic activity of SACs, using 2D γ-phosphorus carbide (γ-PC) as a model system. Specifically, a local dipole around the active site is a key degree to tune the catalytic activity and can be used as an important descriptor with a high feature importance of 17.1% in predicting the difference of adsorption free energy (ΔGO* - ΔGOH*) to assess the activity of the oxygen evolution reaction. As a result, the catalytic performance of SACs can be tuned by an intrinsic dipole, in stark contrast to those external stimuli strategies previously used. These results suggest that dipole engineering and the revolutionary DFT-ML hybrid scheme are novel approaches for designing high-performance catalysts.

Strain driven enhancement of ferroelectricity and magnetoelectric effect in multiferroic tunnel junction.

The strain effect on the ferroelectric and magnetoelectric coupling in multiferroic tunnel junction (MFTJ) Co/BaTiO3/Co has been investigated systematically by using first-principles calculations within density functional theory. It is found that both in-plane compressive strain and uniaxial tensile strain lead to the enhancement of ferroelectric polarization stability and intensity of magnetoelectric coupling in the MFTJ. There is a transition from the paraelectric phase to the ferroelectric phase for the BaTiO3 layer in MFTJ when the loaded in-plane compressive strain increases up to -2.8% and the corresponding average ferroelectric polarization is about 0.13 C m(-2). Meanwhile, the calculated surface magnetoelectric coefficients increase with increasing in-plane compressive strain. Similar phenomena have been also observed in the case of uniaxial tensile strain implemented in MFTJ. The results suggest that the ferroelectric polarization and magnetoelectric coupling in multiferroic tunnel junctions can be controlled by strain and we expect that this study can provide a theoretical basis for the design of spintronic devices.