Atomic Structure Research Articles

Amorphous MoS2 from a machine learning inter-atomic potential.

Amorphous molybdenum disulfide has shown potential as a hydrogen evolution catalyst, but the origin of its high activity is unclear, as is its atomic structure. Here, we have developed a classical inter-atomic potential using the charge equilibration neural network method, and we have employed it to generate atomic models of amorphous MoS2 by melting and quenching processes. The amorphous phase contains an abundance of molybdenum and sulfur atoms in low coordination. Besides the 6-coordinated molybdenum typical of the crystalline phases, a substantial fraction displays coordinations 4 and 5. The amorphous phase is also characterized by the appearance of direct S-S bonds. Density functional theory shows that the amorphous phase is metallic, with a considerable contribution of the 4-coordinated molybdenum to the density of states at the Fermi level. S-S bonds are related to the reduction of sulfur, with the excess electrons spread over several molybdenum atoms. Moreover, S-S bond formation is associated with a distinctive broadening of the 3s states, which could be exploited for experimental characterization of the amorphous phases. The large variety of local environments and the high density of electronic states at the Fermi level may play a positive role in increasing the electrocatalytic activity of this compound.

Orbital Hybridization Induced Dipole Polarization and Room Temperature Magnetism of Atomic Co‐N4‐C toward Electromagnetic Energy Attenuation

AbstractManipulating the electronic structure and geometric coordination environment of single metal atoms has been considered as promising approach for enhancing dipole polarization and enriching electromagnetic attenuation mechanisms. However, achieving precise control of the dielectric polarization response at atomic scale remains a huge challenge. Herein, a metal‐acetate coordination complexes‐assisted strategy is proposed to prepare spatially isolated cobalt (Co) atoms embedded in accordion‐like nitrogen‐doped carbon (NC) matrix. The interactions between metal atoms and NC matrix are carefully tailored through the successive evolution of dispersion states of Co species, ranging from individual atoms to atomic clusters to nanoparticles. Density functional theory reveals that the orbital hybridization between the d electrons of embedded Co atoms and p electrons of coordinated N atoms induces the electron redistribution at N sites, enabling enhanced electric dipole polarization and robust room temperature magnetism (a saturation magnetization of 0.108 emu g−1 at 300 K). Consequently, Co‐SAs@NC exhibits optimal electromagnetic wave absorption properties with a minimum reflection loss of ‐54.4 dB and an effective absorption bandwidth of 8.4 GHz. This work demonstrates an efficient strategy for modulating electromagnetic response at atomic level and provides a novel insight into the d/p electrons orbital hybridization between single metal atoms and NC species.

Structural pathways for ultrafast melting of optically excited thin polycrystalline Palladium films

Due to its extremely short timescale, the non-equilibrium melting of metals is exceptionally difficult to probe experimentally. The knowledge of melting mechanisms is thus based mainly on the results of theoretical predictions. This work reports on the investigation of ultrafast melting of thin polycrystalline Pd films studied by optical laser pump – X-ray free-electron laser probe experiments and molecular-dynamics simulations. By acquiring X-ray diffraction snapshots with sub-picosecond resolution, we capture the sample's atomic structure during its transition from the crystalline to the liquid state. Bridging the timescales of experiments and simulations allows us to formulate a realistic microscopic picture of the crystal-liquid transition. According to the experimental data, the melting process gradually accelerates with the increasing density of deposited energy. The molecular dynamics simulations reveal that the transition mechanism progressively varies from heterogeneous, initiated inside the material at structurally disordered grain boundaries, to homogenous, proceeding catastrophically in the crystal volume on a picosecond timescale comparable to that of electron-phonon coupling. We demonstrate that the existing models of strongly non-equilibrium melting, developed for systems with relatively weak electron-phonon coupling, remain valid even for ultrafast heating rates achieved in femtosecond laser-excited Pd. Furthermore, we highlight the role of pre-existing and transiently generated crystal defects in the transition to the liquid state.

A variational expectation-maximization framework for balanced multi-scale learning of protein and drug interactions

Protein functions are characterized by interactions with proteins, drugs, and other biomolecules. Understanding these interactions is essential for deciphering the molecular mechanisms underlying biological processes and developing new therapeutic strategies. Current computational methods mostly predict interactions based on either molecular network or structural information, without integrating them within a unified multi-scale framework. While a few multi-view learning methods are devoted to fusing the multi-scale information, these methods tend to rely intensively on a single scale and under-fitting the others, likely attributed to the imbalanced nature and inherent greediness of multi-scale learning. To alleviate the optimization imbalance, we present MUSE, a multi-scale representation learning framework based on a variant expectation maximization to optimize different scales in an alternating procedure over multiple iterations. This strategy efficiently fuses multi-scale information between atomic structure and molecular network scale through mutual supervision and iterative optimization. MUSE outperforms the current state-of-the-art models not only in molecular interaction (protein-protein, drug-protein, and drug-drug) tasks but also in protein interface prediction at the atomic structure scale. More importantly, the multi-scale learning framework shows potential for extension to other scales of computational drug discovery.

Precise Modulation of CO2 Sorption in Ti8Ce2-Oxo Clusters: Elucidating Lewis Acidity of the Ce Metal Sites and Structural Flexibility.

Investigating the structure-property correlation in porous materials is a fundamental and consistent focus in various scientific domains, especially within sorption research. Metal oxide clusters with capping ligands, characterized by intrinsic cavities formed through specific solid-state packing, demonstrate significant potential as versatile platforms for sorption investigations due to their precisely tunable atomic structures and inherent long-range order. This study presents a series of Ti8Ce2-oxo clusters with subtle variations in coordinated linkers and explores their sorption behavior. Notably, Ti8Ce2-BA (BA denotes benzoic acid) manifests a distinctive two-step profile during the CO2 adsorption, accompanied by a hysteresis loop. This observation marks a new instance within the metal oxide cluster field. Of intrigue, the presence of unsaturated Ce(IV) sites was found to be correlated with the stepped sorption property. Moreover, the introduction of an electrophilic fluorine atom, positioned ortho or para to the benzoic acid, facilitated precise control over gate pressure and stepped sorption quantities. Advanced in situ techniques systematically unraveled the underlying mechanism behind this unique sorption behavior. The findings elucidate that robust Lewis base-acid interactions are established between the CO2 molecules and Ce ions, consequently altering the conformation of coordinated linkers. Conversely, the F atoms primarily contribute to gate pressure variation by influencing the Lewis acidity of the Ce sites. This research advances the understanding in fabricating metal-oxo clusters with structural flexibility and provides profound insights into their host-guest interaction motifs. These insights hold substantial promise across diverse fields and offer valuable guidance for future adsorbent designs grounded in fundamental theories of structure-property relationships.

Miracle in "White":Hexagonal Boron Nitride.

The exploration of 2D materials has captured significant attention due to their unique performances, notably focusing on graphene and hexagonal boron nitride (h-BN). Characterized by closely resembling atomic structures arranged in a honeycomb lattice, both graphene and h-BN share comparable traits, including exceptional thermal conductivity, impressive carrier mobility, and robust pi-pi interactions with organic molecules. Notably, h-BN has been extensively examined for its exceptional electrical insulating properties, inert passivation capabilities, and provision of an ideal ultraflat surface devoid of dangling bonds. These distinct attributes, contrasting with those of h-BN, such as its conductive versus insulating behavior, active versus inert nature, and absence of dangling surface bonds versus absorbent tendencies, render it a compelling material with broad application potential. Moreover, the unity of such contradictions endows h-BN with intriguing possibilities for unique applications in specific contexts. This review aims to underscore these key attributes and elucidate the intriguing contradictions inherent in current investigations of h-BN, fostering significant insights into the understanding of material properties.

Changes in Current Transport and Regulation of the Microstructure of Graphene/Polyimide Films under Joule Heating Treatment.

The excellent electrical properties of graphene have received widespread attention. However, the difficulty of electron transfer between layers still restricts the application of graphene composite materials to a large extent. Therefore, in this study, graphene/polyimide films were subjected to a Joule heating treatment to improve the electrical conductivity of the film by ~76.85%. After multiple Joule thermal cycle treatments, the conductivity of the graphene/polyimide film still gradually increased, but the increase in amplitude tended to slow down. Finally, after eight Joule heat treatments, the conductivity of the graphene/polyimide film was improved by ~93.94%. The Joule heating treatment caused the polyimide to undergo atomic rearrangement near the interface bonded to the graphene, forming a new crystalline phase favourable for electron transport with graphene as a template. Accordingly, a model of the bilayer capacitive microstructure of graphene/polyimide was proposed. The experiment suggests that the Joule heating treatment can effectively reduce the distance between graphene electrode plates in the bilayer capacitive micro-nanostructures of graphene/polyimide and greatly increases the number of charge carriers on the electrode plates. The TEM and WAXS characterisation results imply atomic structure changes at the graphene/polyimide bonding interface.

Crystalline-dependent surface reconstruction at low applied potential region for enhanced oxygen evolution reaction

Alkaline water electrolysis is apreferred technology for large-scale green hydrogen production. For most active transition metal-based catalysts during anodic oxygen evolution reaction (OER), the atomic structure of the anodic catalysts’ surface often undergoes reconstruction to optimize the reaction path and enhance their catalytic activity. The design and maintenance of highly active sites during this reconstruction process remain critical and challenging for most OER catalysts. In this study, we explored the effects of crystal structures in pre-catalysts on surface reconstruction at low applied potential. Through experimental observation and theoretical calculation, we found out that catalysts with specific crystal structures exhibit superior surface remodeling ability, which enables them to better adapt to the conditions of the oxygen evolution reaction and achieve efficient catalysis. The discharge process enables the formation of abundant phosphorus vacancies on the surface, which in turn affects the efficiency of the entire oxygen evolution reaction. The optimized crystal structure of the catalyst results in an increase as high as 58.5 mA/cm2 for Ni5P4, which is twice as high as that observed for Ni2P. These results provide essential theoretical foundations and technical guidance for designing more efficient catalysts for oxygen evolution reactions.

First-principle molecular dynamics and in situ DRIFTS study the stability of the intermediates of CO2 hydrogenation to methanol on ZnZrOx solid solution catalyst

Among the many catalysts used for CO2 hydrogenation to methanol, ZnZrOx solid solution is a highly efficient catalyst. Although the reaction mechanism has been widely explored at 0 K using DFT, critical aspects such as the atomic structure of the solid solution and the stability of reaction intermediates during CO2 reduction at experimental temperatures remain unclear. This study employs first-principle molecular dynamics (MD) simulations, FTIR and DRIFTS characterization to address these important questions. During the MD simulation, oxygen vacancies are formed in the system and same as the doped Zn atoms. The formation of oxygen vacancies was further confirmed by the Transmission FTIR and in situ DRIFTS. Due to the creating of oxygen vacancies, the coordination of Zn and Zr in the bulk is reduced to five and seven, respectively. And on the surface, their coordination is reduced to three、four and six、seven, respectively. Subsequently, the hydrogenation of CO2 to methanol using the formate and CO* pathways was studied. In the formate pathway, all intermediates remained stable at 593 K. However, in the CO* pathway, we observe instability of key intermediates which also confirmed by transmission FTIR and in situ DRIFTS characterization.

Optimization of Lithium Metal Anode Performance: Investigating the Interfacial Dynamics and Reductive Mechanism of Asymmetric Sulfonylimide Salts

Asymmetric lithium salts, such as lithium (difluoromethanesulfonyl)(trifluoromethanesulfonyl)imide (LiDFTFSI), have been demonstrated to surpass traditional symmetric lithium salts with improved Li+ conductivity and the capacity to generate a stable solid electrolyte interphase (SEI) while maintaining compatibility with an aluminum (Al0) current collector. However, the intrinsic reductive mechanism through which LiDFTFSI influences battery performance remains unclear and under debate. Herein, detailed SEI reactions of LiDFTFSI–based electrolytes were investigated by combining density functional theory and molecular dynamics, aiming to clarify the formation process and atomic structure of the SEI. Our results show that asymmetric DFTFSI− weakens the interaction between carbonate solvents and Li+, and substantially alters the solvation structure, exhibiting a well-balanced coordination capacity compared to bis(trifluoromethanesulfonyl)imide (TFSI−). Nanosecond hybrid molecular dynamics simulation further reveals that preferential decomposition of LiDFTFSI produces sufficient LiF and Li2O to facilitate a robust SEI. Moreover, abundant F− generated from LiDFTFSI decomposition accumulates on the Al surface and subsequently combines with Al3+ from the current collector to form AlF3, potentially inhibiting corrosion of the current collector. Overall, these findings elucidate how LiDFTFSI regulates the solvation sheath and SEI structure, advancing the development of high-performance electrolytes compatible with current collectors.

Accurate prediction of antibody function and structure using bio-inspired antibody language model.

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% nonredundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials. The BALMFold structure prediction server is freely available at https://beamlab-sh.com/models/BALMFold.

Multi-Scale Traditional and Non-Traditional Machining of Bulk Metallic Glasses (BMGs)-Review of Challenges, Recent Advances, and Future Directions.

Bulk metallic glasses (BMGs) are growing in popularity prominently due to their potential in micro-electromechanical systems (MEMSs) and aerospace applications. BMGs have unique mechanical properties, i.e., high strength, hardness, modulus of elasticity, and wear resistance, due to their disordered atomic structure. Due to their unique mechanical properties and amorphous structures, machining of BMGs remains a challenge. This paper aims to carry out a detailed literature review on various aspects of the machining of bulk metallic glasses using both conventional and non-conventional processes, including experimental approaches, modeling, statistical findings, challenges, and guidelines for machining this difficult-to-machine material. Conventional machining processes were found to be challenging for machining bulk metallic glasses due to their high hardness, brittleness, and tendency to convert their amorphous structure into a crystalline structure, especially at the machined surface and sub-surface. Although their high electrical conductivity makes them suitable for machining by non-conventional processes, they impose new challenges such as heat-affected zones and crystallization. Therefore, the successful machining of BMGs requires more in-depth analysis of cutting forces, tool wear, burr formation, surface finish, recast layers or heat-affected zones, crystallization, and mechanical property changes among different varieties of BMGs. This review paper provides guidelines emerging from in-depth analysis of previous studies, as well as offering directions for future research in the machining of BMGs.

Effect of Strain Rate on Mechanical Deformation Behavior in CuZr Metallic Glass.

Tensile tests were performed on Cu64Zr36 metallic glass at strain rates of 107/s, 108/s, and 109/s via classical molecular dynamics simulations to explore the underlying mechanism by which strain rate affects deformation behavior. It was found that strain rate has a great impact on the deformation behavior of metallic glass. The higher the strain rate is, the larger the yield strength. We also found that the strain rate changes the atomic structure evolution during deformation, but that the difference in the atomic structure evolution induced by different strain rates is not significant. However, the mechanical response under deformation conditions is found to be significantly different with the change in strain rate. The average von Mises strain of a system in the case of 107/s is much larger than that of 109/s. In contrast, more atoms tend to participate in deformation with increasing strain rate, indicating that the strain localization degree is more significant in cases of lower strain rates. Therefore, increasing the strain rate reduces the degree of deformation heterogeneity, leading to an increase in yield strength. Further analysis shows that the structural features of atomic clusters faded out during deformation as the strain rate increased, benefiting more homogeneous deformation behavior. Our findings provide more useful insights into the deformation mechanisms of metallic glass.

Temperature dependence of tribological properties in NiTi shape memory alloy: A nanoscratching study

The molecular dynamics method was used to simulate nanoscratching of a monocrystalline NiTi shape memory alloy (SMA) under various temperatures. Parameters, including the normal force, tangential force, friction coefficient, contact area, scratching hardness, atomic displacement, atomic structure, and surface morphology, were comprehensively studied to understand the friction mechanism of the NiTi SMA during operation. It was verified that the temperature dependence of the tribological properties of the NiTi SMA is mainly attributed to the temperature dependence of the tangential force.The beginning temperature of the reverse martensitic transition (As) is the critical temperature for the transition of tribological properties. Below this temperature, the sliding contact region exhibits good normal/tangential projection symmetry, with the atoms on the contact surface arranged in order. A wide range of martensitic strain coordination occurs in the contact region, leading to a low friction coefficient and minimal wear. When the temperature exceeds this threshold, the asymmetry of the contact surface projection gradually increases. The atoms on the contact surface exhibit amorphous atomic characteristics, causing the influence domain of martensitic transformation of scratches to gradually decrease and the friction coefficient to increase. This study offers insights into the atomic-scale perspective for analyzing the temperature-dependent friction behavior of NiTi SMA induced by phase transition.

Rational optimization of substituted α‐MnO2 cathode for aqueous zinc‐ion battery

AbstractDensity functional theory (DFT) is utilized to explore the effects of increasing concentrations of vanadium (V) and chromium (Cr) substitution on the discharge of α‐MnO2 cathode in hydrated zinc‐ion batteries (ZIBs). During H+‐intercalation and Zn2+‐intercalation, Cr‐substitution proves to be more effective than V‐substitution in promoting discharge behaviors. Transitioning from Mn0.875Cr0.125O2, Mn0.75Cr0.25O2 to Mn0.625Cr0.375O2 is found to consistently enhance the discharge voltage, along with improved tunnel structure retention and volume expansion suppression. In comparison, the promoting effect of increasing V‐substitution is relatively small at initial discharge stages and leads to degradation at later stages, primarily due to an increased concentration of unstable Mn2+ ion. The superior effect of Cr‐substitution is attributed to the unique atomic and electronic structures of substituted Cr4+ and reduced Cr3+ ions during discharge. These ions serve as active electron acceptors to limit the formation of Mn3+ and Mn2+ ions, and as anchors to stabilize the α‐MnO2 framework and intercalated H+/Zn2+ ions, respectively. Our study highlights fine‐tuning through substitution to enhance the performance of α‐MnO2‐based cathode materials in ZIBs.

Crystal structure and shape selection in the growth of 3D metallic crystallites on layered materials: Fe on MoS2

Nucleation and growth of supported 3D metal clusters or crystallites during deposition on MoS2, or on other weakly-adhering layered materials, can potentially produce diverse growth shapes, and even crystal structures differing from the bulk metal. For Fe deposition on MoS2, SEM and AFM observations reveal three distinct crystallite shapes. By comparison with atomistic structure models incorporating realistic Fe-MoS2 interface structures, we conclude that these are: triangular fcc(111) pyramids with sloped {100} side facets; bcc(110) A-frame tents with sloped {100} side facets; and bcc(110) mesas with vertical {100} and {110} side facets. The following picture is proposed for the competitive formation of clusters and crystallites with different structures: (i) small nanoclusters formed at the onset of deposition exhibit facile fluxional dynamics allowing sampling of different crystal structures and shapes; (ii) sufficient fluxionality implies a Boltzmann distribution of sampled structures, and thus coexistence of different structures follows from the demonstrated similar energies for those structures; (iii) growing clusters reach a threshold size above which the characteristic time scale for restructuring exceeds that for cluster growth. Thereafter, clusters are locked-in to a specific crystal structure and shape as revealed by imaging of larger crystallites. Despite a penalty for fcc(111) over bcc(111) pyramids based on bulk energetics, favorable surface and interface energies makes them preferable for smaller sizes.

A numerical code for the analysis of magnetic white-dwarf spectra that includes field effects on the chemical equilibrium

We present a new magnetic-atmosphere model code for obtaining synthetic spectral fluxes of hydrogen-rich magnetic white dwarfs. To date, observed spectra have been analyzed with models that neglect the magnetic field's effects on the atomic populations. In this work, we incorporate state-of-art theory in the evaluation of numerical densities of atoms, free electrons, and ions in local thermodynamical equilibrium under the action of a magnetic field. The energy distribution of atoms is rigorously evaluated for arbitrary field strength. This energy pattern includes going from tightly bound states to metastable or truly bound, highly excited states embedded in the continuum, that is, over the first Landau level. Finite nuclear mass effects and the coupling between the internal atomic structure and the motion of the atom across the magnetic field are also considered. Synthetic fluxes are generated with integrations of numerical solutions of polarized radiative transfer over the visible stellar disk using a spherical $t$-design method. The atmosphere code is tested with observations from the Sloan Digital Sky Survey for a group of known magnetic white dwarfs. Physical stellar parameters are obtained from least-squares fits to the observed energy distribution and compared with results of previous works. We show that the use of zerofield ionization equilibrium in spectral analyses can lead to underestimated effective temperatures for highly magnetic white dwarfs.

Imaging surface structure and premelting of ice Ih with atomic resolution.

Ice surfaces are closely relevant to many physical and chemical properties, such as melting, freezing, friction, gas uptake and atmospheric reaction1-8. Despite extensive experimental and theoretical investigations9-17, the exact atomic structures of ice interfaces remain elusive owing to the vulnerable hydrogen-bonding network and the complicated premelting process. Here we realize atomic-resolution imaging of the basal (0001) surface structure of hexagonal water ice (ice Ih) by using qPlus-based cryogenic atomic force microscopy with a carbonmonoxide-functionalized tip. We find that the crystalline ice-Ih surface consists of mixed Ih- and cubic (Ic)-stacking nanodomains, forming periodic superstructures. Density functional theory reveals that this reconstructed surface is stabilized over the ideal ice surface mainly by minimizing the electrostatic repulsion between dangling OH bonds. Moreover, we observe that the ice surface gradually becomes disordered with increasing temperature (above 120 Kelvin), indicating the onset of the premelting process. The surface premelting occurs from the defective boundaries between the Ih and Ic domains and can be promoted by the formation of a planar local structure. These results put an end to the longstanding debate on ice surface structures and shed light on the molecular origin of ice premelting, which may lead to a paradigm shift in the understanding of ice physics and chemistry.

Relativistic atomic structure calculations of Li-like ions used for plasma diagnostic studies

We have carried out atomic structure calculations using systematically enlarged multiconfiguration Dirac-Fock wavefunctions of Li-like ions of the most prominent plasma impurities (Ar, Ti, Fe, Ni, Kr and W) found in presently working tokamaks. Relativistic Breit interaction and quantum electrodynamic (QED) corrections such as vacuum polarization and self-energy corrections are also included in the calculations prior to the evaluation of low lying energy levels, transition probabilities, oscillator strengths and line strengths. Selective radiative data for electric dipole and magnetic quadrupole transitions are also reported. Special emphasis is given in the computations of fundamental quantities such as oscillator strengths as they are widely used in atomic data and analysis structure (ADAS) databases to evaluate quantities such as effective collision strengths. Present computed values are compared with existing available results on NIST database and few similar earlier computations and a good agreement has been found. We believe that the detailed atomic data with the relativistic and QED corrections will assist in spectroscopic studies such as accurate line identification and plasma modelling work in tokamak plasma, laser induced breakdown spectroscopy (LIBS), highly charged ions clocks and astrophysical observations.

2D Vanadium Sulfides: Synthesis, Atomic Structure Engineering, and Charge Density Waves.

Two ultimately thin vanadium-rich 2D materials based on VS2 are created via molecular beam epitaxy and investigated using scanning tunneling microscopy, X-ray photoemission spectroscopy, and density functional theory (DFT) calculations. The controlled synthesis of stoichiometric single-layer VS2 or either of the two vanadium-rich materials is achieved by varying the sample coverage and sulfur pressure during annealing. Through annealing of small stoichiometric single-layer VS2 islands without S pressure, S-vacancies spontaneously order in 1D arrays, giving rise to patterned adsorption. Via the comparison of DFT calculations with scanning tunneling microscopy data, the atomic structure of the S-depleted phase, with a stoichiometry of V4S7, is determined. By depositing larger amounts of vanadium and sulfur, which are subsequently annealed in a S-rich atmosphere, self-intercalated ultimately thin V5S8-derived layers are obtained, which host 2 × 2 V-layers between sheets of VS2. We provide atomic models for the thinnest V5S8-derived structures. Finally, we use scanning tunneling spectroscopy to investigate the charge density wave observed in the 2D V5S8-derived islands.