Number Of Valence Electrons Research Articles

Machine‐Learned Modeling for Accelerating Organic Solvent Design in Metal‐Ion Batteries

AbstractOrganic solvents offer a promising avenue for enhancing metal‐ion battery performance, for instance, in suppressing dendritic formation. To expedite the discovery of optimal electrolyte formulations, this study integrates density functional theory calculations with machine learning to accurately predict binding energies between metal ions and organic solvents. Leveraging a vast dataset of over 300 organic molecules, an extra trees regressor model is developed and demonstrated to exhibit exceptional predictive capabilities. The model's performance is underscored by its high values on both validation and test sets. Key descriptors contributing to the model's accuracy include the number of valence electrons in the metal ion, the atomic number of the metal ion, and features associated with the van der Waals surface. By applying the trained model to a dataset of up to 20 000 unseen organic molecules, potential high‐performance electrolyte additives are identified. Notably, and emerge as promising candidates for Zn‐ion and Mg‐ion batteries, respectively, outperforming conventional additives. To gain deeper insights into the microscopic behaviour of these identified molecules, molecular dynamics simulations are conducted. This research establishes a robust in silico framework for accelerating the design of advanced metal‐ion batteries through the rational selection of organic solvents.

Ce-Doped Iron Oxide Anticorrosive Coatings: Effect of c(Ce4+):c(Fe3+) Ratio on Structure, Morphology, and Coating Anticorrosion Performance

Utilizing hydrothermal methods, Ce-doped iron oxide nanoparticles were synthesized from precursor solutions under different c(Ce4:c(Fe3+) precursor solutions. The effects of the c(Ce4+):c(Fe3+) ratio in the precursor solutions on the nanoparticle morphology and nanoparticle structure of the Ce-doped iron oxide were investigated using X-Ray diffraction, transmission electron microscopy, and scanning electron microscopy. Fourier transform infrared spectroscopy (FTIR) was used to examine the bond energy strength of the Ce-doped iron oxide nanoparticles. The electrochemical properties of the Ce-doped iron oxide nanoparticles were tested using an electrochemical workstation and a saltwater immersion resistance test. The corrosion resistance of Ce-doped iron oxide coatings at different c(Ce4+):c(Fe3+) ratios was systematically analyzed, uncovering corrosion resistance mechanisms and self-healing capabilities. The results show that as the c(Ce4+):c(Fe3+) ratio decreases, the lattice constants of the samples increase along with the average grain size. Both smaller and larger c(Ce4+):c(Fe3+) ratios are detrimental to lattice distortion in α-Fe2O3. The reduced number of valence electrons provided by cerium ions in Ce-doped iron oxide hinders the generation of holes and exerts a minor influence on the crystal band structure, leading to weaker electrochemical stability. The Ce-doped iron oxide coating prepared at a c(Ce4+):c(Fe3+) ratio of 1:60 readily generates a higher number of reactive hydroxyl radicals during corrosion, thus exhibiting enhanced self-healing capabilities and corrosion resistance.

Valence electron matching law for MXene-based single-atom catalysts

Single-atom catalysts (SACs) have attracted considerable interest in the fields of energy and environmental science due to their adjustable catalytic activity. In this study, we investigated the matching of valence electron numbers between single atoms and adsorbed intermediates (O, N, C, and H) in MXene-anchored SACs (M-Ti2C/M-Ti2CO2). The density functional theory results demonstrated that the sum of the valence electron number (VM) of the interface-doped metal and the valence electron number (VA) of the adsorbed intermediates in M-Ti2C followed the 10-valence electron matching law. Furthermore, based on the 10-valence electron matching law, we deduced that the sum of the valence electron number (k) and VM for the molecular adsorption intermediate interactions in M-Ti2CO2 adhered to the 11-valence electron matching law. Electrostatic repulsion between the interface electrons in M-Ti2CO2 and H2O weakened the adsorption of intermediates. Furthermore, we applied the 11-valence electron matching law to guide the design of catalysts for nitrogen reduction reaction, specifically for N2 → NNH conversion, in the M-Ti2CO2 structure. The sure independence screening and sparsifying operator algorithm was used to fit a simple three-dimensional descriptor of the adsorbate (R2 up to 0.970) for catalyst design. Our study introduced a valence electron matching principle between doped metals (single atoms) and adsorbed intermediates (atomic and molecular) for MXene-based catalysts, providing new insights into the design of high-performance SACs.

Second order Rayleigh–Schrödinger perturbation theory for the Grasp2018 package: Core–core correlations

GRASP package is based on the relativistic configuration interaction in which accurate calculations, accounting for valence, valence–valence, core–valence, core and core–core electron correlations, often rely on massive CSF expansions. This paper presents a further development of the method based on the second-order perturbation theory for finding the most important CSFs that have the greatest influence on the core–valence, core and core–core correlations. This method is based on a combination of the relativistic configuration interaction method and the stationary second-order Rayleigh–Schrödinger many-body perturbation theory in an irreducible tensorial form [G. Gaigalas, P. Rynkun, and L. Kitovienė, Second-order Rayleigh–Schrödinger perturbation theory for the GRASP2018 package: Core–valence correlations, Lith. J. Phys. 64(1), 20–39 (2024), https://doi.org/10.3952/physics.2024.64.1.3, and G. Gaigalas, P. Rynkun, and L. Kitovienė, Second-order Rayleigh–Schrödinger perturbation theory for the GRASP2018 package: Core correlations, Lith. J. Phys. 64(2), 73–81 (2024), https://doi.org/10.3952/physics.2024.64.2.1]. In this extension, the perturbation theory takes into account electron core–valence, core and core–core correlations, where an atom or ion has any number of valence electrons, for calculation of energy spectra and other properties. Meanwhile, the rest of the correlations are taken into account in a traditional way. This allows a significant reduction of the space of the configuration state function for complex atoms and ions. We also demonstrate how this method works for calculations of the energy structure and E1 transition properties of Fe XV ion.

Data-Driven Design of Single-Atom Electrocatalysts with Intrinsic Descriptors for Carbon Dioxide Reduction Reaction

The strategic manipulation of the interaction between a central metal atom and its coordinating environment in single-atom catalysts (SACs) is crucial for catalyzing the CO2 reduction reaction (CO2RR). However, it remains a major challenge. While density-functional theory calculations serve as a powerful tool for catalyst screening, their time-consuming nature poses limitations. This paper presents a machine learning (ML) model based on easily accessible intrinsic descriptors to enable rapid, cost-effective, and high-throughput screening of efficient SACs in complex systems. Our ML model comprehensively captures the influences of interactions between 3 and 5d metal centers and 8 C, N-based coordination environments on CO2RR activity and selectivity. We reveal the electronic origin of the different activity trends observed in early and late transition metals during coordination with N atoms. The extreme gradient boosting regression model shows optimal performance in predicting binding energy and limiting potential for both HCOOH and CO production. We confirm that the product of the electronegativity and the valence electron number of metals, the radius of metals, and the average electronegativity of neighboring coordination atoms are the critical intrinsic factors determining CO2RR activity. Our developed ML models successfully predict several high-performance SACs beyond the existing database, demonstrating their potential applicability to other systems. This work provides insights into the low-cost and rational design of high-performance SACs.

Unlocking versatile capabilities: Mixed-valence decavanadate aerogels for boosting radar, infrared, and thermal stealth

Multifunctional compatible stealth materials have emerged as the focal point of contemporary protection technology research and vanadium-based nanomaterials play a pivotal role in the development of advanced stealth materials. Here, a compatible stealth aerogel is successfully synthesized by employing mixed-valence decavanadate as the vanadium oxide (VOx) molecular model. Ultralight {VⅣVV9}/MXene aerogel (0.0429 g cm–3) exhibits exceptional radar stealth performance with a minimal reflection loss (RLmin) of −57.74 dB (99.9998% EMW absorption) and a significantly superior radar cross section reduction value of 26.77 dB m2. The aerogel's exceptional properties, including a low infrared (IR) emissivity (0.479) and a low thermal conductivity of (32.30 mW m–1 K–1), are crucial for enabling compatibility with IR and thermal stealth technologies. The presence of a mixed-valence polyoxovanadate cluster leads to an increase in the Schottky barrier and enhances magnetic properties, consequently boosting interfacial polarization and contributing to magnetic losses during electromagnetic wave (EMW) absorption. Consequently, altering the number of valence electrons significantly enhances the compatible stealth capabilities. These findings contribute significantly to our comprehension of how microstructure impacts EMW absorption processes and provide a basis for further research into the development of VOx-based compatible stealth materials.

A model for predicting grain-boundary energy of refractory high-entropy alloys based on local element concentration

Refractory high-entropy alloys (RHEAs) exhibit exceptional high-temperature mechanical properties, and their structural stability is primarily influenced by grain boundaries (GBs). However, it remains challenging to accurately quantify the grain boundary energy (GBE) in RHEAs. Herein, we introduce a quantitative descriptor for point-to-point prediction of GBEs in RHEAs based on local element concentration and valence-electron numbers. Our results demonstrate that the role of the constituent elements on GBEs is primarily determined by their valence-electron numbers in RHEAs. These findings are derived from the cohesive energy and atomic structure of the elements within the framework of the broken-bond model, as well as the differential contributions of s-electrons and d-electrons. The model establishes a structure-property relationship between local element concentration and GBEs, with the prediction consistent with experimental and theoretical results, which is crucial for evaluating the GB stability of RHEAs and facilitating the development of high-performance alloys.

Efficient screening and catalytic mechanism of TM@β-Te for nitrogen reduction reaction

At present, nitrogen reduction reaction (NRR) has become one critical method for NH3 production through the single-atom catalyst (SAC). A variety of TM@β-Te SACs, constructed by 28 transition metal (TM) atoms anchoring on monovacant β-Te substrate, are systematically investigated by using DFT calculations. An efficient “six-step” screening scheme is proposed to screen out potential NRR catalysts, during which the implicit and explicit solvent models are involved to evaluate competitive reactions of H2O and H+. The final selected (Ta, W)@β-Te catalysts have limiting potentials (UL) of −0.32 V and −0.37 V, respectively. Three intrinsic descriptors of φ (the ratio of number of valence electrons and electronegativity of TM atom), ΔG∗N(adsorption energy of a single N atom on the substrate) and ICOHP (Crystal orbital Hamiltonian integrals for TM-N bonds) are proposed and their correlations with UL are investigated to expound the catalytic activity and mechanism. The relationships of dN≡N ∼ φ, ΔG∗N2∼ φ, ΔG∗N∼ φ and ICOHP ∼ φ resemble “volcanoes”, where (Ta, W)@β-Te are located near the vertex as potential catalysts, which can be verified by scaling relationship of ICOHP and ΔG∗N. Moreover, the UL ∼ φ, UL ∼ ΔG∗Nand UL ∼ ICOHP can be used to determine the potential catalysts from rough catalyst screening to accurate determination of potential determining step (PDS) in catalytic reaction. The constant potential model is adopted to investigate the influences of electrode potentials on adsorption strength of NRR intermediates. This work is informative for the research of NRR process and catalyst design of monoalkenes, which offers an efficient and dependable approach for screening excellent NRR catalysts and revealing the origin of catalytic activity.

Hydrogen trapping behavior in IVB-VB transition metal carbides

The hydrogen capture mechanism of transition metal carbides is crucial to improve the hydrogen embrittlement resistance of steel materials. Although numerous experimental and theoretical studies have been carried out, the mechanism of hydrogen capture in these carbides has not been fully elucidated. In this paper, the ability of transition metal carbides (TMCs; TM=Ti, Zr, Hf, V, Nb and Ta) to capture hydrogen is studied by first-principles calculations. It is found that there is a strong correlation between the hydrogen solubility energy and the number of valence electrons of IV-VB transition metal carbides. With the increase of the number of valence electrons, the hydrogen solubility energy decreases, which indicates that IVB transition metal carbides have strong hydrogen capture ability. Compared with interstitial sites, the mechanism by which carbon vacancies are more stable hydrogen capture sites is to enhance the capture stability of hydrogen atoms by reducing the effect of chemical and mechanical effects on the dissolution energy of hydrogen atoms. In the interstitial site, hydrogen atoms tend to occupy the triangular site (TMCs-TM) surrounded by three transition metal atoms and one carbon atom. The bonding interaction between the hydrogen atom and the nearest carbon atom is the main factor affecting the stability of hydrogen atom capture.

Suzuki-Miyaura Cross-Coupling Reaction Catalyzed by Al12M (M = Be, Al, C, and P) Superatoms with Different Numbers of Valence Electrons.

The exploration of low-cost, efficient, environmentally safe, and selective catalysts for the activation of carbon-halogen bonds has become an important and challenging topic in modern chemistry. With the help of density functional theory (DFT), it is found that phenyl bromide (PhBr) can be efficiently chemisorbed by the Al12M (M = Be, Al, C, and P) superatoms via forming highly polarized Al-Br covalent bonds, where the C-Br bonds of PhBr can be effectively activated through the electron transfer from Al12M. The different electronic structures of these four Al12M superatoms pose a substantial effect on their performances on the activation of PhBr and the catalytic mechanisms of the Suzuki-Miyaura (SM) reaction. Among them, the alkali-metal-like superatom Al12P exhibits the best performance for the activation of PhBr. In particular, Al13 and Al12P with open-shell electronic structures exhibit catalytic performances comparable to those of previously reported catalysts for this coupling reaction. Hence, it is highly expected that Al13 and Al12P could be used as novel superatom catalysts for C-C coupling reactions and, therefore, open up new possibilities to use nonprecious superatoms in catalyzing the activation and transformation of carbon-halogen bonds.

Tuning the electronic and magnetic properties of MoS2 bilayers by transition-metal intercalation

Two dimensional (2D) transition-metal dichalcogenides and their heterostructures are important materials for future electronic device applications. By using the first-principles calculations we investigate how the electronic and magnetic properties of MoS2 bilayer is modified by intercalating transition-metals (Fe, Co, and Ni). The Fe-intercalated MoS2 bilayer is found to be a non-magnetic gapless semimetal. Without spin–orbit coupling it has the Dirac state on the Γ-M line in k space at the Fermi level. The spin degeneracy of the Dirac state is removed by spin–orbit coupling. However, the bottom of the conduction band and the top of the valence band are in contact with the Fermi level making the system a non-magnetic gapless semimetal. The Dirac state is also observed in both Co-intercalated and Ni-intercalated MoS2 bilayers because they have the same symmetry in crystal structure as the Fe-intercalated MoS2 bilayer. The difference in the number of valence electrons in the intercalated atoms drastically change the electronic and magnetic properties. The Co-intercalated MoS2 bilayer is a ferromagnetic metal, where the Dirac state is below the Fermi level. The Ni-intercalated MoS2 bilayer is a non-magnetic narrow gap semiconductor, where the Dirac state is far below the Fermi level. The results revealed the electronic and magnetic properties of the transition-metal-intercalated MoS2 bilayers and will be useful for designing a variety of 2D materials.

Modulating Valence Electrons and Na Occupancy in Layered Cathodes for High-Performance Na-Ion Batteries.

Na-ion batteries (NIBs) hold promise as a leading option for large-scale energy storage. However, their development faces challenges due to the lack of high-performance cathode materials. P2-type layered oxides are seen as potential cathode materials for NIBs due to higher structure stability, yet their commercialization is hindered by limited capacity and subpar phase transitions during Na extraction and insertion at high voltages. In this study, we introduce a new P2-type cathode material, Na0.76Ni0.23Li0.1Ti0.02Mn0.65O1.998F0.02 (NLTMOF), synthesized with ternary Li/Ti/F substitution. This modification of ternary Li/Ti/F substitution significantly tailors the electronic structures, increasing the number of valence electrons near the Fermi energy level. This facilitates the electronic conductivity and their involvement in charge compensation, thereby enhancing reversible capacity. Additionally, ternary doping synergistically adjusts the Na occupancy at the Na layer for favorable Na extraction without P2-O2 phase transitions even under a high voltage of 4.4 V, boosting cycling stability. As a result, NLTMOF demonstrates a reversible capacity of 110.0 and 132.2 mAh g-1 at 2-4.2 and 2-4.4 V, respectively, and maintains greatly enhanced cycling stability over long cycles. This study sheds light on the design of transition metal oxides for advanced cathode materials through the modulation of electronic structure and Na occupancy in cathode materials, thus promoting the development of NIBs.

Nature of C-C coupling and strategy of tuning the catalytic activity of Cu-N-C catalysts for electro-reduction of CO2 to ethanol

With high atomic utilization and remarkable catalytic activity, Cu-N-C type catalysts display great potential for electro-catalysis in CO2 reduction. However, the relationship between the active moiety and catalytic activity of generating high-value C2 products is still unclear, and the explicit screening criteria is scarcity. Herein, based on the first-principle simulation, the structure-performance relationship on Cu-N-C type catalysts has been investigated by modulating the CO2 reduction process as the number of Cu atom (Cu1, Cu2, Cu3) and the ligand environment (B, C, N, O, P, S) changed. We find the adsorption strength of intermediate *CO strongly affect the possibility of C-C coupling, which can be determined by Bader charge on Cu atom, mainly depending on the number of loaded atomic Cu on Cu-N-C catalysts. Furthermore, the Bader charge can be refined by adjusting the coordination atom of Cu, thus optimizing catalytic activity for the CO2 to ethanol. The moderate Bader charge value, between +0.35 and +0.45, enables the catalyst to behave as a potentially excellent activity with low limiting potential for generating ethanol. More importantly, an intrinsic descriptor, composed of the radius, electronegativity, and number of valence electrons of coordination atoms (φ=∑χ∑r*∑np), was established to characterize the catalytic activity of Cu-N(X)-C catalysts for producing ethanol. Two excellent catalysts, Cu3-N2O2 (-0.51 V) and Cu3-N3S (-0.64 V), are screened out for the CO2RR to generate ethanol. This work discloses theoretical basis for catalytic selectivity of C2 products on Cu-N-C catalysts and provides a regulating and screening principle for high performance catalysts to ethanol.

Pressurization, intercalation, doping, and elements: An empirical study of superconductivity near perturbation onsets

Superconductivity is a phenomenon arising from cooperative electron behavior. However, correlations among (1) the minimum tuning parameter required for emergence, (2) the superconducting transition temperature resulting from minimal tuning, and (3) the host’s physical/chemical properties still elude the scientific community. Recent empirical investigations, such as those revealing ideal gas-like correlations at the onset of superconductivity in intercalated superconductors, motivate this study. Our investigation reports similar findings in systems (>170 compounds) exhibiting superconductivity through other perturbative means, such as single-element doping. In general, statistical measures, including distance correlation analyses (≠ linear regression fit) of thermodynamic variables, indicate the presence of empirical relationships near the superconducting onset of systematically tuned compounds. These relations involve unit cell volume (V), the number of valence electrons (N), and the superconducting transition temperature (Tc). Note: The author’s primary aim is not to validate or challenge BCS theory; it is instead to focus on leveraging methodology led by available data to enhance the exploration and development of innovative and cost-effective superconductors.

Structure Sensitivity of Metal Catalysts Revealed by Interpretable Machine Learning and First-Principles Calculations.

The nature of the active sites and their structure sensitivity are the keys to rational design of efficient catalysts but have been debated for almost one century in heterogeneous catalysis. Though the Brønsted-Evans-Polanyi (BEP) relationship along with linear scaling relation has long been used to study the reactivity, explicit geometry, and composition properties are absent in this relationship, a fact that prevents its exploration in structure sensitivity of supported catalysts. In this work, based on interpretable multitask symbolic regression and a comprehensive first-principles data set, we discovered a structure descriptor, the topological under-coordinated number mediated by number of valence electrons and the lattice constant, to successfully address the structure sensitivity of metal catalysts. The database used for training, testing, and transferability investigation includes bond-breaking barriers of 20 distinct chemical bonds over 10 transition metals, two metal crystallographic phases, and 17 different facets. The resulting 2D descriptor composing the structure term and the reaction energy term shows great accuracy to predict the reaction barriers and generalizability over the data set with diverse chemical bonds in symmetry, bond order, and steric hindrance. The theory is physical and concise, providing a constructive strategy not only to understand the structure sensitivity but also to decipher the entangled geometric and electronic effects of metal catalysts. The insights revealed are valuable for the rational design of the site-specific metal catalysts.

Alkaline Earth Metal Superatom of W@Si16: Characterization of Group 6 Metal Encapsulating Si16 Cage on Organic Substrates.

Transition metal atom (M)-encapsulating silicon cage nanoclusters (M@Si16) exhibit a superatomic nature, depending on the central M atom owing to the number of valence electrons and charge state on organic substrates. Since M@Si16 superatom featuring group 4 and 5 transition metal atoms exhibit rare-gas-like and alkali-like characteristics, respectively, group 6 transition metal atoms are expected to show alkaline earth-like behavior. In this study, M@Si16, comprising a central atom from group 6 (MVI = Cr, Mo, and W) were deposited on C60 substrates, and their electronic and chemical stabilities were investigated in terms of their charge state and chemical reactivity against oxygen exposures. In comparison to alkali-like Ta@Si16, the extent of charge transfer to the C60 substrate is approximately doubled, while the oxidative reactivity is subdued for MVI@Si16 on C60, especially for W@Si16. The results show that a divalent state of MVI@Si162+ appears on the C60 substrate, which is consistently calculated to be a symmetrical cage structure of W@Si162+ in C3v, revealing insights into the "periodic law" of M@Si16 superatoms pertaining to the characteristics of alkaline earth metals.

Phase Transformation Temperature Prediction in Steels via Machine Learning.

The phase transformation temperature plays an important role in the design, production and heat treatment process of steels. In the present work, an improved version of the gradient-boosting method LightGBM has been utilized to study the influencing factors of the four phase transformation temperatures, namely Ac1, Ac3, the martensite transformation start (MS) temperature and the bainitic transformation start (BS) temperature. The effects of the alloying element were discussed in detail by comparing their influencing mechanisms on different phase transformation temperatures. The training accuracy was significantly improved by further introducing appropriate features related to atomic parameters. The melting temperature and coefficient of linear thermal expansion of the pure metals corresponding to the alloying elements, atomic Waber-Cromer pseudopotential radii and valence electron number were the top four among the eighteen atomic parameters used to improve the trained model performance. The training and prediction processes were analyzed using a partial dependence plot (PDP) and Shapley additive explanation (SHAP) methods to reveal the relationships between the features and phase transformation temperature.

Constructing diatomic catalyst on MoSSe achieves ultra-low overpotential for nitrogen fixation: First-principles study

The collaborative interaction between the diatoms can enhance the catalytic activity of the transition metal atoms and facilitate the activation of nitrogen molecules. Based on first-principles calculations, the feasibility of electrocatalytic nitrogen fixation as a diatomic catalyst (TMs@MoSSe) formed by transition metal dimers (V, Cr, Mn, Fe, Co, and Ni) dispersed on a two-dimensional Janus MoSSe monolayer is systematically investigated. The results demonstrate that the MoSSe monolayer loaded with double chromium atoms (Cr2@MoSSe) exhibits exceptional catalytic activity, showcasing an extremely low overpotential of 0.17 V in the enzymatic mechanism. Specifically, this research elucidates the nitrogen reduction capacity of the electrocatalyst by considering its magnetic moment and work function, concluding that a lower work function corresponds to enhanced catalytic activity. Additionally, the product of the magnetic moment and valence electron numbers of the transition metal atoms (μTM⋅dTM) exhibits an inverted volcano relationship with the overpotential. These findings can provide valuable insights for the design of diatomic catalysts.

Second-order Rayleigh–Schrödinger perturbation theory for the GRASP2018 package: Core–valence correlations

The General Relativistic Atomic Structure package [GRASP2018, C. Froese Fischer, G. Gaigalas, P. Jönsson, and J. Bieroń, Comput. Phys. Commun. (2019), DOI: 10.1016/j.cpc.2018.10.032] is based on multiconfiguration Dirac– Hartree–Fock and relativistic configuration interaction (RCI) methods for energy structure calculations. The atomic state function used in the program is built from the set of configuration state functions (CSFs). The valence–valence, core–valence and core–core correlations are explicitly included through expansions over CSFs in RCI. We present a combination of RCI and the stationary second-order Rayleigh–Schrödinger many-body perturbation theory in an irreducible tensorial form to account for electron core–valence correlations when an atom or ion has any number of valence electrons. This newly developed method, which offers two ways of use, allows a significant reduction of the CSF space for complex atoms and ions. We also demonstrate how the method and program works for the energy structure calculation of Cl III ion.

The potential energy surface and superatomic properties of the octahedral PtSn5 cluster

Zintl (group IV elements) clusters with a special number of valence electrons often exhibit extraordinary structures and chemical bonding patterns, and the stability of them is rationalised by the Wade-Mingos rule. However, this rule is still limited for some Zintl clusters. Here, we find that the potential energy surface of PtSn5 has a single deep funnel, which leads down to the octahedron of the global minimum. The AIMD simulations demonstrate that the octahedral PtSn5 still has a good thermal stability at 1000 K. The molecular orbitals and AdNDP analyses reveal that the 20 valence electrons from five Sn atoms of the PtSn5 fill superatomic shells resulting in an electronic configuration of 1S21P61D102S2, and the electronic structure of the Pt atom is d10, well following the magic number of the Jellium model. The result is further confirmed by the density of states and the localised orbital locator. After the CO molecule is adsorbed on the PtSn5, it prefers to be located at the Pt atom. Due to the charge-transfer effect, the C–O bond length and stretching frequency appear to change significantly. Our work opens up the study on the Jellium model for Zintl clusters.