Hierarchical structures and magnetism of Co clusters: a perspective from integration of deep learning and a hybrid differential evolution algorithm.

Theoretically determining the lowest-energy structure of a cluster has been a persistent challenge due to the inherent difficulty in accurate description of its potential energy surface (PES) and the exponentially increasing number of local minima on the PES with the cluster size. In this work, density-functional theory (DFT) calculations of Co clusters were performed to construct a dataset for training deep neural networks to deduce a deep potential (DP) model with near-DFT accuracy while significantly reducing computational consumption comparable to classic empirical potentials. Leveraging the DP model, a high-efficiency hybrid differential evolution (HDE) algorithm was employed to search for the lowest-energy structures of CoN (N = 11-50) clusters. Our results revealed 38 of these clusters superior to those recorded in the Cambridge Cluster Database and identified diverse architectures of the clusters, evolving from layered structures for N = 11-27 to Marks decahedron-like structures for N = 28-42 and to icosahedron-like structures for N = 43-50. Subsequent analyses of the atomic arrangement, structural similarity, and growth pattern further verified their hierarchical structures. Meanwhile, several highly stable clusters, i.e., Co13, Co19, Co22, Co39, and Co43, were discovered by the energetic analyses. Furthermore, the magnetic stability of the clusters was verified, and a competition between the coordination number and bond length in affecting the magnetic moment was observed. Our study provides high-accuracy and high-efficiency prediction of the optimal structures of clusters and sheds light on the growth trend of Co clusters containing tens of atoms, contributing to advancing the global optimization algorithms for effective determination of cluster structures.

Effect of composition and architecture on the thermodynamic behavior of AuCu nanoparticles.

The chemical and physical properties of nanomaterials ultimately rely on their crystal structures, chemical compositions and distributions. In this paper, a series of AuCu bimetallic nanoparticles with well-defined architectures and variable compositions has been addressed to explore their thermal stability and thermally driven behavior by molecular dynamics simulations. By combination of energy and Lindemann criteria, the solid-liquid transition and its critical temperature were accurately identified. Meanwhile, atomic diffusion, bond order, and particle morphology were examined to shed light on thermodynamic evolution of the particles. Our results reveal that composition-dependent melting point of AuCu nanoparticles significantly departs from the Vegard's law prediction. Especially, chemically disordered (ordered) alloy nanoparticles exhibited markedly low (high) melting points in comparison with their unary counterparts, which should be attributed to enhancing (decreasing) atomic diffusivity in alloys. Furthermore, core-shell structures and heterostructures demonstrated a mode transition between the ordinary melting and the two-stage melting with varying Au content. AuCu alloyed nanoparticles presented the evolution tendency of chemical ordering from disorder to order before melting and then to disorder during melting. Additionally, as the temperature increases, the shape transformation was observed in AuCu nanoparticles with heterostructure or L10 structure owing to the difference in thermal expansion coefficients of elements and/or of crystalline orientations. Our findings advance the fundamental understanding on thermodynamic behavior and stability of metallic nanoparticles, offering theoretical insights for design and application of nanosized particles with tunable properties.

Structural Determination and Hierarchical Evolution of Transition Metal Clusters Based on an Improved Self-Adaptive Differential Evolution with Neighborhood Search Algorithm.

Determining the optimal structures and clarifying the corresponding hierarchical evolution of transition metal clusters are of fundamental importance for their applications. The global optimization of clusters containing a large number of atoms, however, is a vastly challenging task encountered in many fields of physics and chemistry. In this work, a high-efficiency self-adaptive differential evolution with neighborhood search (SaNSDE) algorithm, which introduced an optimized cross-operation and an improved Basin Hopping module, was employed to search the lowest-energy structures of CoN, PtN, and FeN (N = 3-200) clusters. The performance of the SaNSDE algorithm was first evaluated by comparing our results with the parallel results collected in the Cambridge Cluster Database (CCD). Subsequently, different analytical methods were introduced to investigate the structural and energetic properties of these clusters systematically, and special attention was paid to elucidating the structural evolution with cluster size by exploring their overall shape, atomic arrangement, structural similarity, and growth pattern. By comparison with those results listed in the CCD, 13 lower-energy structures of FeN clusters were discovered. Moreover, our results reveal that the clusters of three metals had different magic numbers with superior stable structures, most of which possessed high symmetry. The structural evolution of Co, Pt, and Fe clusters could be, respectively, considered as predominantly closed-shell icosahedral, Marks decahedral, and disordered icosahedral-ring growth. Further, the formation of shell structures was discovered, and the clusters with hcp-, fcc-, and bcc-like configurations were ascertained. Nevertheless, the growth of the clusters was not simply atom-to-atom piling up on a given cluster despite gradual saturation of the coordination number toward its bulk limit. Our work identifies the general growth trends for such a wide region of cluster sizes, which would be unbearably expensive in first-principles calculations, and advances the development of global optimization algorithms for the structural prediction of clusters.

NiPd co-doped nitrogen-coordinated graphene as a high-efficiency electrocatalyst for oxygen reduction reactions: a first-principles determination.

High-energy-density fuel cells and metal-air batteries are difficult to commercialize on a large scale mainly because of the sluggish oxygen reduction reaction (ORR) at the cathode. Hence, the development of high-efficiency and low-cost electrocatalysts as Pt substitutes for the ORR is of significance for the mass applications of these devices. In this work, we thoroughly investigated the structural and catalytic properties of NiPd co-doped N-coordinated graphene (denoted as NiPdN6-G) as an ORR electrocatalyst by using density-functional theory (DFT) calculations. Our results show that NiPdN6-G is structurally and thermodynamically stable. Furthermore, we explored all the possible paths and intermediates of the ORR, and identified the preferable active sites and the most stable adsorption configurations of the intermediates and transition states. In general, there are 15 possible reaction paths, of which 8 paths have lower energy barriers than pure Pt, and the maximum energy barrier and overpotential of the ORR for the optimal path are only 0.14 eV and 0.37 V, respectively. This work demonstrates that NiPdN6-G should be a promising candidate for substituting Pt and Pt-based catalysts for the ORR in energy conversion and storage devices.

Computational determination of a graphene-like TiB4 monolayer for metal-ion batteries and a nitrogen reduction electrocatalyst.

As an emerging two-dimensional (2D) material, the TiB4 monolayer possesses intrinsic advantages in electrochemical applications owing to its graphene-like structure and metallic characteristics. In this work, we performed density functional calculations to investigate the electrochemical properties of the TiB4 monolayer as an anode material for Li/Na/K ion batteries and as an electrocatalyst for the nitrogen reduction reaction (NRR). Our investigation reveals that Li/Na/K ions could be steadily adsorbed on the TiB4 monolayer with moderate adsorption energies, and tended to diffuse along two adjacent C-sites with lower energy barriers (0.231/0.094/0.067 eV for Li/Na/K ions) compared to the currently reported transition-metal boride monolayers. Furthermore, a N2 molecule can be spontaneously captured by the TiB4 monolayer with a negative Gibbs free energy (-0.925 eV and -0.326 eV for end-on and side-on adsorptions, respectively), hence provoking a conversion into NH3 along the most efficient reaction pathway (i.e., N2* → N2H* → HNNH* → H2NNH* → H3NNH* → NH* → NH2* → NH3*). In the hydrogenation process, the TiB4 monolayer exhibits much higher catalytic activity for the NRR as compared with other electrocatalysts, which should be attributed to the spontaneous achievement (ΔG < 0) at all hydrogenation reaction steps except the potential-determining step. Moreover, the TiB4 monolayer exhibits higher selectivity toward the NRR than the hydrogen evolution reaction. Our work advances the mechanistic understanding on the electrochemical properties of the TiB4 monolayer as an anode material for metal-ion batteries and as a NRR electrocatalyst, and provides significant guidance for developing high-performance multifunctional 2D materials.

Thermally Activated Microstructural Evolution of PtIrCu Alloyed Nanorings: Insights from Molecular Dynamics Simulations.

Nanoalloys have attracted extensive interest from the research and industrial community due to their unique properties. In this work, the thermally activated microstructural evolution and resultant collapse of PtIrCu nanorings were investigated using molecular dynamics simulations. Three PtIrCu nanorings with a fixed outer radius and varied inner radii were addressed to investigate the size effects on their thermal and shape stabilities. The shape factor was introduced to monitor their shape changes, and a common neighbor analysis was employed to characterize the local structures of atoms. The results reveal that both the thermal and shape stabilities of these nanorings can be remarkably improved by decreasing the inner radius. Furthermore, they all experienced the evolutionary process from ring to pie and spherelike morphologies, finally resulting in structural collapse. The stacking faults were observed in these rings during the heating process. Our work sheds light on the fundamental understanding of alloyed nanorings subjected to heating, hence offering a theoretical foundation for their syntheses and applications.

Thermally activated microstructural evolution of metallic heterophase nanoparticles: insights from molecular dynamics simulations.

A crystal phase is a key factor to determine the physical and chemical properties of crystalline materials. As a new class of nanoscale structures, heterophase nanoparticles, which assemble conventional and unconventional phases, exhibit exceptional properties in comparison with their single-phase counterparts. In this work, we explored the thermodynamic stability of Au, Co, and AuCo heterophase nanoparticles with fcc and hcp phases by using molecular dynamics simulations. These heterostructured nanoparticles were continuously heated to examine their thermally activated structural evolutions. Au and Co single-phase nanoparticles were also considered for comparison. The results show that the phase transition between fcc and hcp is absent in these heterophase nanoparticles despite the existence of an unconventional phase. Although the melting of Au and Co heterophase nanoparticles is homogeneous, AuCo heterophase nanoparticles show heterogeneous melting, i.e., the Au fcc domain firstly melts, followed by the melting of the Co hcp domain, exhibiting a typical two-stage melting characteristic and resulting in the existence of a solid-core/liquid-shell structure within a considerable temperature region. Furthermore, the mutual diffusion of atoms between fcc and hcp domains is observed in the Au and Co heterophase nanoparticles. However, the unidirectional diffusion from the Au domain to the Co domain is found in the AuCo heterophase nanoparticles prior to their overall melting. This study deepens the fundamental understanding of the thermodynamic evolution of metallic heterogeneous nanoparticles and provides mechanistic and quantitative guidance for the rational design and applications of nanoscale multiphase heterostructures.

An Improved Self-Adaptive Differential Evolution with the Neighborhood Search Algorithm for Global Optimization of Bimetallic Clusters.

Global optimization of multicomponent cluster structures is considerably time-consuming due to the existence of a vast number of isomers. In this work, we proposed an improved self-adaptive differential evolution with the neighborhood search (SaNSDE) algorithm and applied it to the global optimization of bimetallic cluster structures. The cross operation was optimized, and an improved basin hopping module was introduced to enhance the searching efficiency of SaNSDE optimization. Taking (PtNi)N (N = 38 or 55) bimetallic clusters as examples, their structures were predicted by using this algorithm. The traditional SaNSDE algorithm was carried out for comparison with the improved SaNSDE algorithm. For all the optimized clusters, the excess energy and the second difference of the energy were calculated to examine their relative stabilities. Meanwhile, the bond order parameters were adopted to quantitatively characterize the cluster structures. The results reveal that the improved SaNSDE algorithm possessed significantly higher searching capability and faster convergence speed than the traditional SaNSDE algorithm. Furthermore, the lowest-energy configurations of (PtNi)38 clusters could be classified as the truncated octahedral and disordered structures. In contrast, all the optimal (PtNi)55 clusters were approximately icosahedral. Our work fully demonstrates the high efficiency of the improved algorithm and advances the development of global optimization algorithms and the structural prediction of multicomponent clusters.

Computational screening of MBene monolayers with high electrocatalytic activity for the nitrogen reduction reaction.

As an emerging family of two-dimensional (2D) materials, transition metal borides (MBenes) have attracted increasing interest due to their potential applications in electrochemistry, especially electrocatalysis. In this work, we addressed six MB (M = Sc, Ti, V, Cr, Mo and W) monolayers as catalysts to explore their electrocatalytic activity for the nitrogen reduction reaction (NRR) using first-principles calculations. Our results demonstrated that N2 molecules could be strongly adsorbed on these MB monolayers to provoke the NRR process. Furthermore, we examined five possible catalytic reaction pathways of the NRR, i.e., the alternating, distal, and three mixed pathways, on the MB monolayers with N2 adsorption (both side-on and end-on) configurations, and screened out three highly efficient NRR catalysts: VB, CrB, and MoB monolayers with the onset potential of -0.396, -0.277, and -0.403 V, respectively. By comparison of the limiting potentials, the most effective reaction pathways of the NRR were ascertained to be the alternating pathway on the VB monolayer with the end-on configuration and the mixed I pathway on the CrB monolayer with the end-on configuration and on the MoB monolayer with the side-on configuration. Our work sheds light on the electrocatalytic mechanisms of the NRR on 2D MBenes, and provides a theoretical foundation for developing highly efficient MBene electrocatalysts for the NRR.

Oxygen adsorption on high-index faceted Pt nanoparticles.

High-index faceted Pt nanoparticles with excellent electrocatalytic performances are promising to efficiently accelerate the oxygen reduction reactions in fuel cells. By adopting the hybrid grand canonical Monte Carlo reactive molecular dynamics (GCMC/RMD) simulations, we examined the oxygen adsorption on three 24-facet nanoparticles respectively enclosed by {310}, {311}, and {331} high-index facets. The site-dependent adsorption energies on each open-structure surface are calculated. Meanwhile, the adsorption ratios under various pressures and temperatures are presented. It is revealed that the adsorption capacity of these high-index faceted nanoparticles is considerably higher than that of the ones terminated by low-index facets. Moreover, oxygen adsorption exerts a significant impact on their thermodynamic behaviors.

Single Mn Atom Anchored on Nitrogen-Doped Graphene as a Highly Efficient Electrocatalyst for Oxygen Reduction Reaction.

Single Mn atom on nitrogen-doped graphene (MnN4 -G) has exhibited good structural stability and high activity for the adsorption and dissociation of an O2 molecule, becoming a promising single-atom catalyst (SAC) candidate for oxygen reduction reaction (ORR). However, the catalytic activity of MnN4 -G for the ORR and the optimal reaction pathway remain obscure. In this work, density-functional theory calculations were employed to comprehensively investigate all the possible pathways and intermediate reactions of the ORR on MnN4 -G. The feasible active sites and the most stable adsorption configurations of the intermediates and transition states during the ORR were identified. Screened from all the possibilities, three optimal four-electron O2 hydrogenation pathways with an ultralow energy barrier of 0.13 eV were discovered that are energetically more favorable than direct O2 dissociation pathways. Analysis of the free energy diagram further verified the thermodynamical feasibility of the three pathways. Thus, MnN4 -G possesses superior ORR activity. This study provides a fundamental understanding of the design of highly efficient SACs for the ORR.

Structural Evolution of the Surface and Interface in Bimetallic High-Index Faceted Heterogeneous Nanoparticles.

Bimetallic high-index faceted heterostructured nanoparticles represent a new class of high-performance nanocatalysts. In this work, we investigated the structural evolution of PtAu tetrahexahedral heterostructured nanoparticles enclosed by {210} facets using molecular dynamics simulations. The surface and interface were specifically addressed. The results show that the PtAu nanoparticle exhibits a heterogeneous melting pattern, leading to solid-liquid coexistence over a wide temperature range. In terms of particle shape evolution, the critical transformation temperature for the surface structure of the PtAu heterostructured nanoparticle is much lower than the melting point of each domain. In comparison, the interface could be basically retained even when the Au domain completely melts. These results extend our fundamental understanding of the thermally driven structural evolution of the surface and interface in bimetallic high-index faceted heterostructured nanoparticles and provide insight into the design and application of metallic nanoparticles with multifunctional performance.

Computational screening of pristine and functionalized ordered TiVC MXenes as highly efficient anode materials for lithium-ion batteries.

With the rapid development of rechargeable lithium-ion batteries, the search for highly efficient electrode materials has become an ever-growing need for high power density and fast charge-discharge rate to meet the future challenges of energy storage. Two-dimensional MXenes exhibit good electrical and electrochemical properties and are very attractive candidates for anode materials. In this article, we addressed ordered double-metal pristine TiVC and functionalized TiVCT2 (T = O, S, F, or OH) MXenes and investigated their electrochemical properties by using density functional theory calculations. Our results reveal that these ordered MXenes all exhibit metallic characteristics with high electronic conductivity. The diffusion barrier of a Li ion is only 15 meV on the Ti surface and 14 meV on the V surface of the pristine TiVC monolayer. However, functional group terminations markedly increase the Li ion diffusion barrier on TiVC monolayers. Among all the group functionalized TiVCT2 monolayers, the TiVCS2 monolayer exhibits the lowest diffusion barrier of a Li ion (0.191 eV on the Ti surface and 0.186 eV on the V surface). Furthermore, the open circuit voltages of Li ions on both TiVC and TiVCS2 monolayers fall in the range of 0-1.0 V, which may prevent the dendrite formation of alkali metals in the charge/discharge process. Therefore, ordered pristine TiVC and functionalized TiVCS2 monolayers should be promising candidates as anode materials for lithium-ion batteries.

Efficacy of probiotics in the treatment of acute diarrhea in children: a systematic review and meta-analysis of clinical trials.

BACKGROUND: If acute diarrhea in children is not treated promptly and effectively, it can lead to severe dehydration and serious sequelae. Due to the imbalance of intestinal bacteria in children with acute diarrhea, the supplementation with probiotics is important, which can improve the intestinal microenvironment, promote immunity, and enhance resistance. This meta-analysis provides further evidence and discussion of the therapeutic effect of probiotics on acute diarrhea in children. METHODS: MEDLINE, EMBASE, PubMed, and the Cochrane Library databases were searched by rapid matching. The input keywords were as follows: (probiotics/synbiotics) and (child/children) and (acute diarrhea/acute gastroenteritis). Articles reporting on randomized controlled trials (RCTs) of probiotics in treating acute diarrhea in children were retrieved. The studies were published from 2010 to 2020. After screening and quality evaluation, Stata 16.0 software was used for the analysis. RESULTS: Twelve articles with 744 patients were included in the study, and the overall quality of the articles was excellent. Meta-analysis showed that the duration of diarrhea in the probiotics group was shorter than that in the control group [standard mean difference (SMD) =-0.74, 95% CI: -1.11 to -0.37, Z=-3.935, P=0.000], the 2-day treatment efficacy for diarrhea in the probiotics group was greater than that in the control group [odds ratio (OR) =2.12, 95% CI: 1.47-3.05, Z=3.998, P=0.000], and the length of hospital stay in the probiotics group was shorter than that of the control group (SMD =-0.60, 95% CI: -0.74 to -0.47, Z=-8.781, P=0.000). In the subgroup analysis, combined probiotics shortened the duration of diarrhea compared with single probiotic use, and Lactobacillus reuteri and Saccharomyces boulardii had a better therapeutic effect than Lactobacillus rhamnosus or Lactobacillus acidophilus. DISCUSSION: In the treatment of acute diarrhea in children, the addition of probiotics can shorten the duration of diarrhea, increase treatment efficacy after 2 days of treatment, and shorten the length of hospital stay. However, because of possible publication bias in the current study, further high-quality RCT studies in clinical settings are needed to verify the current results and continue the exploration of this topic.

Basin Hopping Genetic Algorithm for Global Optimization of PtCo Clusters.

In general, searching the lowest-energy structures is considerably more time-consuming for bimetallic clusters than for monometallic ones because of the presence of an increasing number of homotops and geometrical isomers. In this article, a basin hopping genetic algorithm (BHGA), in which the genetic algorithm is implanted into the basin hopping (BH) method, is proposed to search the lowest-energy structures of 13-, 38-, and 55-atom PtCo bimetallic clusters. The results reveal that the proposed BHGA, as compared with the standard BH method, can markedly improve the convergent speed for global optimization and the possibility for finding the global minima on the potential energy surface. Meanwhile, referencing the monometallic structures in initializations may further raise the searching efficiency. For all the optimized clusters, both the excess energy and the second difference of the energy are calculated to examine their relative stabilities at different atomic ratios. The bond order parameter, the similarity function, and the shape factor are also adopted to quantitatively characterize the cluster structures. The results indicate that the 13- and the 55-atom systems tend to be icosahedral despite different degrees of lattice distortions. In contrast, for the 38-atom system, Pt10Co28, Pt11Co27, Pt17Co21, Pt19Co19, Pt20Co18, and Pt30Co8 tend to be disordered, while Pt21Co17 presents a defected face-centered cubic (fcc) structure, and the remaining clusters are perfect fcc. The methodology and results of this work have referential significance to the exploration of other alloy clusters.

Shape Stability of Metallic Nanoplates: A Molecular Dynamics Study.

Metallic nanoplates have attracted widespread interests owing to their functional versatility, which relies heavily on their morphologies. In this study, the shape stability of several metallic nanoplates with body-centered-cubic (bcc) lattices is investigated by employing molecular dynamics simulations. It is found that the nanoplate with (110) surface planes is the most stable compared to the ones with (111) and (001) surfaces, and their shapes evolve with different patterns as the temperature increases. The formation of differently orientated facets is observed in the (001) nanoplates, which leads to the accumulation of shear stress and thus results in the subsequent formation of saddle shape. The associated shape evolution is quantitatively characterized. Further simulations suggest that the shape stability could be tuned by facet orientations, nanoplate sizes (including diameter and thickness), and components.

Chemically initiated liquid-like behavior and fabrication of periodic wavy Cu/CuAu nanocables with enhanced catalytic properties.

Solid crystalline materials have long range order in their atomic arrangement while liquids have short range order, and the transition between them is usually caused by heat and/or pressure. Herein, we report the finding that chemical processes may play a similar role as heat and initiate liquid-like behavior of crystalline nanomaterials at a temperature far below their melting points. When the straight Cu/CuAu crystalline nanocables are dispersed in organic amine at 80 °C under ambient conditions, the continuous oxidation of Cu atoms on the surface and diffusion of Cu atoms from the core to the surface would break up the long-range ordered arrangement of atoms and lead to the transformation of an anisotropic crystal into an isotropic liquid-like state, which resulted in the evolution of the straight morphology of the nanocables into periodic wavy structures following the Rayleigh instability. It was also demonstrated that periodic wavy Cu@CuAu nanocables exhibit much better catalytic activity than straight Cu@CuAu nanocables towards the reduction of p-nitrophenol into p-aminophenol by NaBH4. Our results not only provide new insights into the transition between a solid crystal and a liquid-like state at the nanoscale, but also facilitate the development of new strategies for the synthesis of functional nanomaterials.

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles.

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Thermal Stability of Co-Pt and Co-Au Core-Shell Structured Nanoparticles: Insights from Molecular Dynamics Simulations.

Co-Pt and Co-Au core-shell nanoparticles were heated by molecular dynamics simulations to investigate their thermal stability. Two core structures, that is, hcp Co and fcc Co, have been addressed. The results demonstrate that the hcp-fcc phase transition happens in the hcp-Co-core/fcc-Pt-shell nanoparticle, while it is absent in the hcp-Co-core/fcc-Au-shell one. The stacking faults appear in both Pt and Au shells despite different structures of the Co core. The Co core and Pt shell concurrently melt and present an identical melting point in both Co-Pt core-shell nanoparticles. However, typical two-stage melting occurs in both Co-Au core-shell nanoparticles. Furthermore, the Au shell in the hcp-Co-core/fcc-Au-shell nanoparticle exhibits a lower melting point than that in the fcc-Co-core/fcc-Au-shell one, while the melting points are closely equal for both hcp and fcc Co cores. All of these observations suggest that their thermal stability strongly depends on the structure of the core and the element of the shell.

Thermal Stability of Platinum-Cobalt Bimetallic Nanoparticles: Chemically Disordered Alloys, Ordered Intermetallics, and Core-Shell Structures.

Pt-Co bimetallic nanoparticles are promising candidates for Pt-based nanocatalysts and magnetic-storage materials. By using molecular dynamics simulations, we here present a detailed examination on the thermal stabilities of Pt-Co bimetallic nanoparticles with three configurations including chemically disordered alloy, ordered intermetallics, and core-shell structures. It has been revealed that ordered intermetallic nanoparticles possess better structural and thermal stability than disordered alloyed ones for both Pt3Co and PtCo systems, and Pt3Co-Pt core-shell nanoparticles exhibit the highest melting points and the best thermal stability among Pt-Co bimetallic nanoparticles, although their meltings all initiate at the surface and evolve inward with increasing temperatures. In contrast, Co-Pt core-shell nanoparticles display the worst thermal stability compared with the aforementioned nanoparticles. Furthermore, their melting initiates in the core and extends outward surface, showing a typical two-stage melting mode. The solid-solid phase transition is discovered in Co core before its melting. This work demonstrates the importance of composition distribution to tuning the properties of binary nanoparticles.