Pure Clusters Research Articles

Theoretical investigation of formaldehyde recognition by aluminum nitride nanoclusters(Al12N12): a DFT approach

This study analyses how formaldehyde molecules (H2CO and (H2CO)2) interact with a Al12N12 nanocluster with a specific theoretical approach (B3LYP/6-311++G(d,p)). We use the GAMESS software package for all calculations. Scientists have used the Atoms in Molecules (AIM) theory to better grasp how gases stick to and interact with Al12N12 nanoclusters The Al12N12 nanocluster electronic properties change significantly when exposed to formaldehyde adsorption. Furthermore, the pure Al12N12 cluster can capture up to four single molecules and three pairs of formaldehyde, leading to a decrease in the HOMO–LUMO gap by around 37–54%. The Al12N12 nanocluster can detect formaldehyde because its conductivity changes when formaldehyde molecules are present. The Bader theory of atoms in molecules (AIM) is used to study how formaldehyde interacts with a nanocluster. The pure Al12N12 nanocluster may be a good choice for finding formaldehyde molecules. The results show that Al12N12 could be a good chemical sensor for detecting formaldehyde.

Revealing the adsorption nature of disulfiram on metal clusters (Au, Pt, Ag, Pd, Cu, and Ni): DFT analysis, SERS enhancement and sensor properties

The electrical and vibrational characteristics of disulfiram (DSM) with Au/Pt/Ag/Pd/Cu/Ni metal cages are analyzed using the DFT method. The current study shows that complexes have energy gaps that are distinct from those of pure metal clusters and are surprisingly stable. Reactivity descriptors including hardness, chemical potential and electrophilicity are estimated in order to thoroughly examine the electronic property. Raman modes are enhanced, particularly for complexesI, as a result of SERS effect. The DSM and metal clusters exchange charges, which induces a dipole moment. The change in the FMOs energy of the metal clusters after interaction has a substantial impact on electrical conductivity and work function. The metal clusters for DSM can be used as a work function-based sensor in addition to an electronic sensor. On the other hand, DSM with metal clusters has a longer recovery period, suggesting that it can be stored or taken out of a particular environment.

Spatial and temporal patterns of haemorrhagic fever with renal syndrome (HFRS) and the impact of environmental drivers in a border area of the Russian Far East.

Haemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease transmitted by rodents. The distribution of HFRS in the European part of Russia has been studied quite well; however, much less is known about the endemic area in the Russian Far East. The mutual influence of the epidemic situation in the border regions and the possibility of cross-border transmission of infection remain poorly understood. This study aims to identify the spatiotemporal hot spots of the incidence and the impact of environmental drivers on the HFRS distribution in the Russian Far East. A two-scale study design was performed. Kulldorf's spatial scan statistic was used to conduct spatiotemporal analysis at a regional scale from 2000 to 2020. In addition, an ecological niche model based on maximum entropy was applied to analyse the contribution of various factors and identify spatial favourability at the local scale. One spatiotemporal cluster that existed from 2002 to 2011 and located in the border area and one pure temporal cluster from 2004 to 2007 were revealed. The best suitability for orthohantavirus persistence was found along rivers, including those at the Chinese-Russian border, and was mainly explained by land cover, NDVI (as an indicator of vegetation density and greenness) and elevation. Despite the stable incidence in recent years in, targeted prevention strategies are still needed due to the high potential for HRFS distribution in the southeast of the Russian Far East.

Population genetic structure of Schistosoma bovis and S. curassoni collected from cattle in Mali.

Schistosomiasis is of medical and veterinary importance. Despite the critical situation of schistosomiasis in sub-Saharan Africa, few molecular epidemiological studies have been carried out to determine the role of animals in its transmission. In Mali, it has been over three decades since the last molecular study of animal schistosomes was carried out. It is now urgent to identify circulating strains of the parasite because of potential interactions with other schistosome species, which could complicate disease control. The aim of our work was to study the composition and genetic structure of schistosome populations collected from cattle. The prevalence of schistosome was 23.9%, with the prevalences of Schistosoma bovis (Sb) and S. curassoni (Sc) estimated at 12.6% and 9.8%, respectively. No hybrid strains or S. haematobium were found. The parasites displayed distinct geographical distribution with Sb dominant in Bamako (78.8% and 98% in Central Bamako Slaughterhouse and Sabalibougou Slaughterhouses, respectively) and Sc dominant in Kayes (95.3%). Of the 476 parasites with a complete genetic profile, 60.4% were pure Sc, and were mainly from Kayes. We identified two clusters at the site level (Fst of 0.057 and 0.042 for Sb and Sc, respectively). Cluster 1 was predominantly composed of pure Sb parasites and cluster 2 was mainly composed of pure Sc parasites, from Bamako and Kayes, respectively. Our study shows that cattle schistosomiasis remains endemic in Mali with S. bovis and S. curassoni. A robust genetic structure between the different schistosome populations was identified, which included two clusters based on the geographical distribution of the parasites.

Coalescence-induced shape transformations in Pd and AuPd clusters.

The coalescence of pure Pd and Pd-rich AuPd nanoparticles is studied by molecular dynamics simulations. The collision of icosahedral nanoparticles with face-centered-cubic truncated octahedral ones is considered. These structures are considered because they have been experimentally shown to be the most stable for AuPd nanoalloys and for pure Pd clusters. The final structures of the coalescence process are determined depending on the composition of the initial colliding units, which heavily influences the structure of the final outcome. The key mechanisms at the atomic level of coalescence processes are analysed, revealing the peculiar types of collective atomic rearrangements that enable the transformation of an icosahedron into a sequence of close packed planes and, conversely, the transformation of a series of close packed planes into icosahedral shells.

Archimedean heterologous helixes in Ti10Cd6-oxo nanoclusters: double-helical self-assembly and therapeutic application in Parkinson's disease

A unique oblate heterologous Ti10Cd6-oxo cluster helix has been synthesized. The exchange with chiral ligands gives a pair of enantiomerically pure clusters, which exhibit markedly different treatment effects in a C. elegans model of Parkinson's disease.

Unusually High-Spin Fe12C12- Metallo-Carbohedrene Clusters.

Ferromagnets constructed from nanometals of atomic precision are important for innovative advances in information storage, energy conversion, and spintronic microdevices. Considerable success has been achieved in designing molecular magnets, which, however, are challenging in preparation and may suffer from drawbacks on the incompatibility of high stability and strong ferromagnetism. Utilizing a state-of-the-art self-developed mass spectrometer and a homemade laser vaporization source, we have achieved a highly efficient preparation of pure iron clusters, and here, we report the finding of a strongly ferromagnetic metal-carbon cluster, Fe12C12-, simply by reacting the Fen- clusters with acetylene in proper conditions. The unique stability of this ferromagnetic Fe12C12- cluster is rooted in a plumb-bob structure pertaining to Jahn-Teller distortion. We classify Fe12C12- as a new member of metallo-carbohedrenes and elucidate its structural stability mechanism as well as its soft-landing deposition and magnetization measurements, providing promise for the exploration of potential applications.

Quantifying plasmonic characteristics of pure and alkali doped aluminium clusters

Study of plasmonic response of molecules and metal nanoclusters have drawn a considerable attention during recent times due to their various practical applications. In this study, the optical properties and the plasmonic response of our recently reported Al13+ cluster [Guin et al. Journal of Molecular Graphics and Modelling, 2020, 97, 107544] and its alkali doped counterparts [Guin et al. Journal of Molecular Modeling, 2021, 27, 235] have been investigated based on Transition dipole moment (TDM), Natural Transition Orbital (NTO) and transition inverse participation ratio (TIPR) indices. Recently these indices have been utilized by various scientists to characterize plasmonic transitions of molecular systems and metal nanoclusters. In TDM analysis, the magnitude of all the contributing TDMs associated with the molecular orbital transitions have been estimated along with the angles the individual dipoles make with the resultant dipole moment vector. A transition having at least two dominating TDM contributions along with phase matching indicate a collective or plasmonic transition. The collectiveness of orbital transitions is also corroborated through NTO and TIPR analysis. The effect of solvent medium on the optical properties and plasmonic transitions have also been studied using time dependent density functional theory in the conductor like polarizable continuum model (TDDFT-CPCM). The solvent has a strong impact on the optical properties as well as the plasmonic response of the clusters. The dielectric environment of the solvent red shifts and broadens the spectra with respect to that in the gas phase. Plasmon like excitations have been found for Li doped Al13+ cluster without solvent and Na doped Al13+ cluster in ethanol and THF.

New Multicomponent Optimization Scheme for Equiatomic Vanadium-Titanium Nanoparticle Study.

We present a new multicomponent structure prediction method named MRS-Swap searching, which is inspired by space symmetry and swap of different atomic species. For the pure titanium cluster, a new ground-state structure of the Ti20 cluster with higher symmetry relative to a previous study was found by our method. Based on the structural analysis of Tin (n = 2k, k = 2-11), Vn (n = 2k, k = 2-11), and TinVm (n = m = 2-11) systems, we found that the lowest energy structures of these three systems are very similar, which indicates that equiatomic vanadium-titanium-mixed clusters do not change their ground-state structure relative to the same size pure vanadium and titanium cluster. According to the structure-activity relationship, we conclude that the yield strength (σ) of macro vanadium-titanium alloy is between pure titanium and pure vanadium metal, and this can be expressed through σ(Ti) > σ(TiV) > σ(V). The X-ray diffraction results show that the V2Nb, TiVNb, and Ti2Nb alloys also have the same BCC structure, which may be related to their microstructure. Our method and results can be helpful for future multicomponent alloy design.

A Holistic View of the Interactions between Electron-Deficient Systems: Clustering of Beryllium and Magnesium Hydrides and Halides.

In the search for common bonding patterns in pure and mixed clusters of beryllium and magnesium derivatives, the most stable dimers and trimers involving BeX2 and MgX2 (X = H, F, Cl) have been studied in the gas phase using B3LYP and M06-2X DFT methods and the G4 ab initio composite procedure. To obtain some insight into their structure, stability, and bonding characteristics, we have used two different energy decomposition formalisms, namely MBIE and LMO-EDA, in parallel with the analysis of the electron density with the help of QTAIM, ELF, NCIPLOT, and AdNDP approaches. Some interesting differences are already observed in the dimers, where the stability sequence observed for the hydrides differs entirely from that of the fluorides and chlorides. Trimers also show some peculiarities associated with the presence of compact trigonal cyclic structures that compete in stability with the more conventional hexagonal and linear forms. As observed for dimers, the stability of the trimers changes significantly from hydrides to fluorides or chlorides. Although some of these clusters were previously explored in the literature, the novelty of this work is to provide a holistic approach to the entire series of compounds by using chemical bonding tools, allowing us to understand the stability trends in detail and providing insights for a significant number of new, unexplored structures.

Probing the effect of magnesium doping on the structural and electronic properties of boron clusters

In this paper, a global search for the lowest energy structure of Mg2Bn0/- (n = 1–12) clusters is performed based on Density functional theory combined with the particle swarm optimization algorithm program CALYPSO. The geometry, stability, charge transfer, and bonding properties of the clusters were analyzed at the B3LYP/def2-tzvp level. Then Mg2B8 with high symmetry D4h was found to be the magic numbers cluster among them. The doped clusters Mg2Bn0/− were compared with the pure boron clusters Bn+20/− (n = 1–12) at the same level. The following results are obtained: as the number of boron atoms increases, the boron clusters doped with Mg atoms change from a two-dimensional planar or quasi-plane structure to a three-dimensional structure. The doped magnesium atoms are always positively charged in the convex capped position. And the doping of Mg atoms drives the overall stabilization of the boron clusters and makes the clusters more compact. There is a large amount of charge transfer between the Mg atom and the B atom, and the main orbitals involved are the S and p orbitals. There are strong interactions between the two atoms of boron and magnesium. Through the analysis of the bonding properties, it was found that the s-p hybridization mode between MgB is the main reason for the enhanced cluster stability.

Study on the Stability of Cu-Ni Cluster Components and the Effect of Strain on Its Structure.

Solute clusters are one of the important mechanisms of irradiation embrittlement of ferritic steels. It is of great significance to study the stability of solute clusters in ferritic steels and their effects on the mechanical properties of the materials. Molecular dynamics was used to study the binding energy, defect energy, and interaction energy of 2 nm-diameter Cu-Ni clusters in the ferritic lattice, which have six categories of Cu-Ni clusters, such as the pure Cu cluster, the core-shell structural cluster with one layer to four layers of Ni atoms and the pure Ni cluster. It was found that Cu-Ni clusters have lower energy advantages than pure Ni clusters. Through shear strain simulation of the three clusters, the structure of 2 nm diameter clusters does not undergo phase transformation. The number of slip systems and the length of dislocation lines in the cluster system are positively correlated with the magnitude of the critical stress of material plastic deformation.

Formation of hydroxide anions in amorphous astrophysical ices and recombination with protons: a quantum chemical study

ABSTRACT Quantum chemical cluster calculations employing density functional theory and correlation consistent basis sets reveal the following pathways by which hydroxide anions (OH–) may form in amorphous astrophysical ices: (1) hydroxyl radicals (OH), which may arise in ice via ultraviolet photolysis, can capture electrons; (2) adsorbed hydrogen atoms can capture electrons to form H–, which reacts with water to yield H2 and OH–; (3) NaOH deposited on ice dissociates into Na+ and OH–; (4) NaH deposited on ice dissociates into Na+ and H–; H– then reacts with water to yield H2 and OH– as above. The IR spectrum of ice-bound OH– is presented, based on nine clusters containing up to 31H2O and 1–2 OH– anions. The interaction of OH– in ice with cations is also explored. Prior work shows that when HCO+ is deposited on pure amorphous water clusters, it reacts with H2O to form formic acid (HCOOH) and the hydronium (H3O+). When HCO+ is deposited on a cluster containing OH–, the reaction proceeds in almost the same manner, but the H3O+ and OH– charge centres migrate through the water network toward each other and tend to neutralize one another by forming H2O. This occurred in all but one of seven cases considered; migration occurred even when the oxygen atom attacked by HCO+ is over 10 Å from the oxygen atom in OH–. Cations and anions can interact in ice via pathways not present in the gas phase or incorporated in current models.

Structural evolution, stability, electronic and bonding properties of sodium-doped magnesium cluster cations

Bimetallic sodium-doped magnesium cluster cations, NaMg n + (n= 2–12), have been investigated through a synergetic combination of the CALYPSO code and DFT calculations. The results reveal that the lowest-energy structures of NaMg n + exhibit linear, planar, triangular pyramid, pentagonal pyramid, and triangular prism topologies. The structures can be described as a substituted geometry of pure Mg clusters at the small size. Starting from n = 9, the dominant structures transform into a triangular prism-based configuration. Like anionic and neutral NaMg n clusters, the Na atom prefers the peripheral regions of the Mg n framework. Stability studies indicate NaMg4 + and NaMg10 + to be the~most stable clusters, which may benefit from their closed-shell electron structures. Analysis of the bonding nature shows stronger Mg-Mg interaction than the Na-Mg interaction in the NaMg4 + and NaMg10 + clusters. The reason is that covalent bonds are formed in the Mg-Mg regions, while there is no aggregation of electron density in the Na-Mg regions.

First principle study of enhanced CO adsorption on divacancy graphene-supported TM7 (TM = Fe, Co, Ni, Cu, Ag, and Au) clusters

The adsorption of CO on transition metal clusters TM7 (TM = Fe, Co, Ni, Cu, Ag, and Au) and their corresponding divacancy graphene-supported clusters has been investigated using plane-wave density functional theory with van der Waals D3 correction. The results reveal that all divacancy graphene-supported TM7 clusters show a stronger adsorption capacity for CO compared to the pure TM7 clusters. Orbital-resolved bonding interactions indicate, while the d-p orbital coupling between the substrate and CO dominates the magnitude of the absolute adsorption energy, the enhanced s-p orbital coupling between the substrate and CO determines the increase in the adsorption energy of CO on the divacancy graphene-supported TM7 clusters. On the other hand, the enhanced CO chemisorption energies on the divacancy graphene-supported TM7 clusters are caused by the induced electrostatic interaction between the positively charged TM7 on divacancy graphene and CO.

Printed Circuit Boards Leaching Followed by Synthesis of Gold Nanoparticle Clusters Using Plant Extracts

This work investigates the potential of 70% ethanolic leaf extracts of Rubus idaeus L., Cistus ladanifer L. and Erica andevalensis in the metal separation from synthetic unimetallic solutions of different metals and a leachate obtained from the leaching of PCBs. Results from the experiments with unimetallic solutions revealed R. idaeus and E. andevalensis extracts induced separation of more than 95% of the initial Au(III), while C. ladanifer separated ~78% of this metal. Thereafter, application of three plant extracts to real Au bearing leachate obtained from PCBs leaching, revealed about 96, 95 and 90% Au recovery with R. idaeus, C. ladanifer and E. andevalensis extracts, respectively with 15–60% co-removal of Pb and less than 15% of other metals. The reduction of Au(III) ions into Au(0) nanoparticles by R. idaeus extract was confirmed by molecular UV–Visible, and FT-IR analysis showed the involvement of plant secondary metabolites in Au bio-reduction and bio-stabilization. Particles obtained from the application of R. idaeus extract to the leachate were initially analyzed with XRD and results confirmed the presence of Au(0) with contamination of PbSO4, which was completely removed by washing with 1 M HCl. Thereafter, results from STEM-EDS analysis showed the presence of Au particles conjugated with organic material and other metals. Consequently, particles were subjected to another washing step with acetone. Afterwards, STEM-EDS showed pure Au microparticle clusters (~0.8 μm) with flower-shaped or apparently cubic morphologies, and HRSTEM showed the tiny nanoparticles (~20 nm), which form the clusters.Graphical

YOLO–CL: Galaxy cluster detection in the SDSS with deep machine learning

Galaxy clusters are powerful probes for cosmological models. Next-generation, large-scale optical and infrared surveys are poised to reach unprecedented depths and, thus, they require highly complete and pure cluster catalogs, with a well-defined selection function. We have developed a new cluster detection algorithm named YOLO for CLuster detection (YOLO–CL), which is a modified version of the state-of-the-art object detection deep convolutional network named You only look once (YOLO) that has been optimized for the detection of galaxy clusters. We trained YOLO–CL on the red-sequence Matched-filter Probabilistic Percolation (redMaPPer) cluster catalog, based on Sloan Digital Sky Survey (SDSS) color images. We find that YOLO–CL detects 95–98% of the redMaPPer clusters, with a purity of 95–98%, that is calculated by applying the network to SDSS blank fields. When compared to the Meta-Catalog of X-Ray Detected Clusters of Galaxies 2021 (MCXC2021) X-ray catalog in the SDSS footprint, YOLO–CL recovers all clusters at LX ≳ 2–3 × 1044 erg s−1, M500 ≳ 2–3 × 1014M⊙, R500≳0.75–0.8 Mpc and 0.4 ≲ z ≲ 0.6. When compared to the redMaPPer detection of the same MCXC2021 clusters, we find that YOLO–CL is more complete than redMaPPer, which means that the neural network has indeed improved the cluster detection efficiency of its training sample. In fact, YOLO–CL detects ~98% of the MCXC2021 clusters with an X-ray surface brightness of IX,500 ≳ 20 × 10−15 erg s−1 cm−2 arcmin−2 at 0.2 ≲ z ≲ 0.6 and ~100% of the MCXC2021 clusters with IX,500 ≳ 30 × 10−15 erg s−1 cm−2 arcmin−2 at 0.3 ≲ z ≲ 0.6; while redMaPPer detects ~98% of the MCXC2021 clusters with IX,500 ≳ 55 × 10−15 erg s−1 cm−2 arcmin−2 at 0.2 ≲ z ≲ 0.6 and ~100% of the MCXC2021 clusters with IX,500 ≳ 20 × 10−15 erg s−1 cm−2 arcmin−2 at 0.5 ≲ z ≲ 0.6. The YOLO–CL selection function is approximately constant with redshift, with respect to the MCXC2021 cluster X-ray surface brightness. YOLO–CL exhibits a high level of performance when compared to traditional detection algorithms applied to SDSS. Deep learning networks display a strong advantage over traditional galaxy cluster detection techniques because they do not require the galaxy’s photometric and photometric redshift catalogs. This eliminates systematic uncertainties that may be introduced during source detections and photometry, as well as photometric redshift measurements. Our results show that YOLO–CL is an efficient alternative to traditional cluster detection methods. In general, this work shows that it is worth exploring the performance of deep convolution networks for future cosmological cluster surveys, such as the Rubin/Legacy Survey of Space and Time (Rubin/LSST), Euclid, and Roman Space Telescope surveys.

Synthesis and Characterization of Thiol-Protected Silver Nanoclusters for Photodynamic Therapy Applications

Aqueous metal nanoclusters have emerged as versatile tools in biomedical applications, particularly in the scope of imaging and cancer therapeutics. This research paper investigates a thiol-protected silver nanocluster (AgNC), focusing on establishing a reproducible synthesis method to obtain a pure cluster species for use in biological stability studies. Conventionally, nanocluster synthesis employs reducing agents, like NaBH4, which often poses challenges in reaction control and product purity. This study adopts an alternative approach, utilizing a Norrish Type I reaction to enhance synthesis. This light-activated reaction leverages the regulated concentration of alpha-hydroxy radicals from a photoinitiator (Omnirad 2959) achieved through UVA-induced homolytic bond cleavage. Monitoring AgNC formation through ultraviolet-visible (UV-Vis) and fluorescence emission-excitation matrix (EEM) spectroscopy and confirming product purity via parallel factor analysis (PARAFAC), this work offers insight into the influence of parameters such as light intensity, reactant concentration, irradiation wavelength, and oxygen presence on consistency and reproducibility of the AgNC syntheses. Methods like Polyacrylamide Gel Electrophoresis (PAGE) and centrifugation are also employed to facilitate separation and purification, preparing the AgNC for subsequent evaluation within biologically significant contexts (tumor microenvironments and phosphate buffer solutions). Although diverse reaction conditions yielded an array of nanocluster species, characterization of the AgNCs reveals challenges in reproducing a pure cluster species consistently. EEM and PARAFAC analyses underscore similarities across synthesized clusters, yet significant variations in reaction conditions persist. The primary application envisioned for these AgNCs is in Photodynamic Therapy (PDT), a form of radiative therapy that exploits the optical properties of metal nanoclusters to induce reactive oxygen species, thus eliciting cancer cell death. It is evident that further investigation is necessary to deepen the comprehension of AgNCs and validate their potential use in PDT. Future research should focus on refining reaction conditions, and effective separation, of AgNC, allowing for advancement in therapeutic interventions such as PDT.

Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach

BackgroundFunctional gastrointestinal disorders (FGIDs), as a group of syndromes with no identified structural or pathophysiological biomarkers, are currently classified by Rome criteria based on gastrointestinal symptoms (GI). However, the high overlap among FGIDs in patients makes treatment and identifying underlying mechanisms challenging. Furthermore, disregarding psychological factors in the current classification, despite their approved relationship with GI symptoms, underlines the necessity of more investigation into grouping FGID patients. We aimed to provide more homogenous and well-separated clusters based on both GI and psychological characteristics for patients with FGIDs using an unsupervised machine learning algorithm.MethodsBased on a cross-sectional study, 3765 (79%) patients with at least one FGID were included in the current study. In the first step, the clustering utilizing a machine learning algorithm was merely executed based on GI symptoms. In the second step, considering the previous step's results and focusing on the clusters with a diverse combination of GI symptoms, the clustering was re-conducted based on both GI symptoms and psychological factors.ResultsThe first phase clustering of all participants based on GI symptoms resulted in the formation of pure and non-pure clusters. Pure clusters exactly illustrated the properties of most pure Rome syndromes. Re-clustering the members of the non-pure clusters based on GI and psychological factors (i.e., the second clustering step) resulted in eight new clusters, indicating the dominance of multiple factors but well-discriminated from other clusters. The results of the second step especially highlight the impact of psychological factors in grouping FGIDs.ConclusionsIn the current study, the existence of Rome disorders, which were previously defined by expert opinion-based consensus, was approved, and, eight new clusters with multiple dominant symptoms based on GI and psychological factors were also introduced. The more homogeneous clusters of patients could lead to the design of more precise clinical experiments and further targeted patient care.

Polynitrogen clusters interaction with water: experimental and theoretical perspectives

Polynitrogen clusters are of great interest as potential high-energy-density materials (HEDMs). However, it is still a challenge to effectively manufacture pure nitrogen clusters. Here, we present a method to produce all-nitrogen clusters ranging in size from 3 to 10 using a self-developed apparatus consisting of a laser vaporization cluster source and a mass spectrometer. The results indicate that the mass peak of the N4 + cluster is dominant, and the cooling of the cluster source with liquid nitrogen effectively enhanced the intensities of larger nitrogen clusters. The trace amounts of water in the carrier gas affects the relative signal intensities of nitrogen clusters, suggesting that water molecules can affect their stabilities. The geometrical structures of the N(n = 3–10) clusters are determined by CALYPSO cluster structural search method and density functional theory calculations. A series of promising polynitrogen clusters, such as Z-shaped N clusters and bicyclic N clusters, are identified. The molecular dynamics simulations indicate the decomposition energy barrier of (N4–H2O)+ cluster is lower than that of N4 + cluster by 2.3 kcal mol−1, while the decomposition energy barrier of (N8–H2O)+ cluster is higher than that of N8 + cluster by 1.4 kcal mol−1. These findings provide useful information for the generation and stabilization of polynitrogen clusters, which are valuable for the design and synthesis of HEDMs.