Cluster Configuration Research Articles

Customized Heteronuclear Dual Single‐Atom and Cluster Assemblies via D‐Band Orchestration for Oxygen Reduction Reaction

AbstractAdvanced oxygen reduction reaction (ORR) catalysts, integrating with well‐dispersed single atom (SA) and atomic cluster (AC) sites, showcase potential in bolstering catalytic activity. However, the precise structural modulation and in‐depth investigation of their catalytic mechanisms pose ongoing challenges. Herein, a proactive cluster lockdown strategy is introduced, relying on the confinement of trinuclear clusters with metal atom exchange in the covalent organic polymers, enabling the targeted synthesis of a series of multicomponent ensembles featuring FeCo (Fe or Co) dual‐single‐atom (DSA) and atomic cluster (AC) configurations (FeCo‐DSA/AC) via thermal pyrolysis. The designed FeCo‐DSA/AC surpasses Fe‐ and Co‐derived counterparts by 18 mV and 49 mV in ORR half‐wave potential, whilst exhibiting exemplary performance in Zn‐air batteries. Comprehensive analysis and theoretical simulation elucidate the enhanced activity stems from adeptly orchestrating dz2‐dxz and O 2p orbital hybridization proximate to the Fermi level, fine‐tuning the antibonding states to expedite OH* desorption and OOH* formation, thereby augmenting catalytic activity. This work elucidates the synergistic potentiation of active sites in hybrid electrocatalysts, pioneering innovative targeted design strategies for single‐atom‐cluster electrocatalysts.

Novel design of hollow carbon nanocage modified with nanotubes as a bifunctional electrocatalyst for high performance Zn–air batteries

Microcavities play a crucial role as microreactors in the transport of molecular/ionic guests and the exposure of active sites, thus significantly influencing the electrocatalytic performance. This study prepares Co/N-codoped hollow carbon (HT-CoN/C) with surface-distributed carbon nanotubes by pyrolysis of PDA-coated Zn/Co bimetallic ZIF (BM-ZIF@PDA). Benefiting from the hierarchical porous structure, high specific surface area (307.17 m2 g−1) and abundant Co clusters, the HT-CoN/C exhibits remarkable bifunctional oxygen electrocatalytic activity with an overpotential of the ORR/OER processes (ΔE = 0.703 V). The density functional theory (DFT) calculations also verify that the configuration of C-coated N-coordinated Co clusters (Co4-Nx) affect the electrocatalytic activity of ORR and OER, illustrating the source of the excellent oxygen electrocatalytic activity of HT-CoN/C. The aqueous rechargeable zinc-air battery (RZAB) using HT-CoN/C as the air electrode is characterized by a superior peak power density (175 mW cm−2), a prolonged cycle life (1230 cycles/410 h at 5.0 mA cm−2) and a high open-circuit voltage (1.47 V). Meanwhile, the flexible solid-state RZAB assembled by the HT-CoN/C also exhibits a higher peak power density (117 mW cm−2) and an excellent bending performance. This work is extremely valuable for the design and synthesis of Co/N co-doped carbon electrocatalysts.

An Energy-Efficient Bio-Inspired Mobility-Aware Cluster p-WOA Algorithm for Intelligent Whale Optimization and Fuzzy-Logic-Based Zonal Clustering Algorithm in FANET

The newest research topic is flight ad hoc network (FANET). The primary obstacles faced by unmanned aerial vehicles (UAVs) are their limited flight duration and inefficient routes resulting from their great mobility and low battery power. Compared to MANETs or VANETs, FANETS routing is thought to be more difficult because of these topological restrictions. Artificial intelligence (AI)-based clustering techniques can be applied to resolve intricate routing issues in situations when both static and dynamic routing are ineffective. To overcome these path difficulties, clustering techniques based on evolutionary algorithms, including intelligent, probabilistic, bio-inspired whale optimization algorithms (p-WOAs), we suggest fuzzy-logic-based zonal clustering-based routing algorithms in this study to be used in FANET to build clusters. In addition to requiring fewer cluster heads (CHs) for routing, p-WOA offers good coverage and low energy consumption. The stochastic whale optimization technique, which draws inspiration from nature, is utilized in this paper to build networks and deploy nodes. The next step is to choose cluster heads using a region clustering technique based on fuzzy logic. By selecting the right cluster head, you can decrease routing traffic and increase cluster longevity. Routing overhead is also decreased. The data are then sent to the best path using a reference point group mobility model. The proposed p-WOA was used to test fuzzy integral and fuzzy logic ant optimization, fuzzy integral and neural network interference system, fuzzy integral and whale optimization algorithm (ANFIS-WOA), and fuzzy integral and FL-ALO. An array of indicators, such as cluster count, longevity, cluster configuration time, cluster head consistency, and energy usage, are employed to assess the effectiveness of the suggested methodology. The suggested algorithm works better than the most advanced techniques available today, as demonstrated by the experimental findings presented in this paper.

Oxidation behavior of Fe-Ni Invar alloy under high pressure: A ReaxFF molecular dynamics study

The Fe-Ni Invar alloy is often employed under extreme conditions such as high temperatures, high pressures, and corrosive environments, making it susceptible to oxidation and subsequent failure. Hence, a thorough understanding of its oxidation behavior is crucial. We performed ReaxFF-based molecular dynamics (MD) simulations to study the oxidation behaviour of Fe-Ni Invar alloy at the atomic scale under extreme conditions. The initial stage of oxidation involves the preferential adsorption and dissociation of O2, demonstrating its surface-site selectivity. The initial oxidation kinetics follows a logarithmic law, and the whole oxidation process results in dominant low-coordinated clusters configurations in the oxide film. Simultaneously, Fe atoms tend to donate more electrons to O atoms than Ni atoms. Moreover, the O2 consumption rate were found to increase with pressure and amorphous oxides formed more readily under high pressure. Our results indicate that adjusting the pressure may enhance the oxidation resistance of the Fe-Ni alloy, which is significant for the design and application of alloys in extreme conditions.

A global assemblage of tax haven clusters: profit shifting, tax dodging and money laundering

In this paper we explore a selection of tax haven clusters in the US and Europe as diverse but recognisable species of some fifty of the phenomena worldwide that have been seldom studied from an economic geography or spatial planning viewpoint. We treat the objects of study as being almost perfect expressions of the classical, canonical cluster configuration. They are: spatial agglomeration, untraded as well as market dependencies, small and medium-sized enterprise status, associative or agentic relationships, interaction with large firms inside or outside the cluster and knowledge acquisition, advisory, consultancy and knowledge translation services from research and innovation intermediaries - public and/or private. However, we think their characteristics demand further recognition of the interactive and often innovative communication networks by means of which these cluster incumbents interact globally. This is because they are set within a worldwide system that can be conceptualised as an exemplar of the well-known construct known as an ‘assemblage’ (Deleuze and Guattari, 2004a). Unlike more recent treatments from De Landa (2019) and others, we try to concentrate on the motive power of the ‘agentic’ impulses of ‘desire’ that motivate human action (e.g. regarding ‘God, Gold or Glory’ as commonly-rehearsed motivators for colonialism of various kinds). It has been more common to use ‘assemblage theory’ to analyse the interlocking ‘machinic’ elements of complex systems like power networks or laboratory interactions. To unlock the mysteries of system interlocking in our selected tax havens, which comprise Wilmington, Delaware (US), Ireland (EU) and Gibraltar (former EU, now British Overseas Territory) – post-Brexit - occupying a ‘quantum’ space ‘in which both the colonial and post-colonial find expression’ (Perera, 2021). Methodologically, we seek ‘pattern recognition’ to identify the lineaments that explain these clusters and the ‘agentic’ actors that motivate them.

Optimization of the power performance for three hybrid Darrieus-Savonius rotors based on the Taguchi method

Abstract The hybrid vertical-axis wind turbine is a unique design that overcomes the efficiency limitations of Savonius rotors and the start-up challenges of Darrieus rotors. This study uses the Taguchi optimization method to enhance the performance of a cluster of three hybrid Darrieus-Savonius vertical-axis wind turbines. The optimized parameters include distances between adjacent turbine centers, configuration angles, rotational directions, and the pitch angle. The study is the first to investigate the effect of varying the pitch angle of Darrieus airfoil blades on hybrid design performance. The optimal configuration of the three hybrid VAWTs and the isolated rotor is analyzed through flow velocity, pressure, and turbulence kinetic energy contours. The results show that the pitch angles have the greatest effect on the rated power coefficient among other studied influencing parameters. The optimal cluster configuration’s performance improvement is due to the favorable velocity gradient around the blades. Compared to the isolated rotor, the power coefficient enhancement for the optimal case is 46.545% at the rated tip speed ratio of 3.08. The hybrid rotor in the cluster can achieve almost the same power as the isolated rotor up to a tip speed ratio of 4.1 instead of 2.86 for the isolated rotor. However, the decrease in overall efficiency for some cluster configurations is due to wake flow intensity and trapping between the rotors, which causes a stagnation zone.

Bi Cluster Engineering for Tunable Broadband NIR Optical Response

AbstractNear‐infrared (NIR) broadband active photonic materials play a crucial role in various domains such as optical communication, phototherapy, and medical imaging. However, the construction of NIR photonic materials with tunable optical response still remains a great challenge. This manuscript proposes a topological structure engineering strategy in Bi‐activated glass for the realization of the controllable NIR emission. By manipulating the topological structure of glass, the Bi cluster configuration can be precisely control, with the cluster size from 2.78 to 1.64 nm. Correspondingly, various optical properties including broadband emission, excited state absorption (ESA), and even unsaturable loss (UL) can be rationally switched. Based on the above findings, Bi cluster‐activated bulk glasses, optical fibers, and the derived NIR active devices with notably improved performance can be successfully fabricated. Their application potentials in optical communication and NIR imaging are also demonstrated. The study highlights the promise of Bi cluster‐activated materials in advancing NIR photonic materials and devices. Furthermore, the topological‐mediated cluster regulation strategy may also provide new insights into the fundamental science and cutting technology of other cluster‐activated materials.

Online kernel-based clustering

A novel online joint kernel learning and clustering (OKC) framework is derived which is capable of determining time-varying clustering configurations without the need for training data. To facilitate clustering via sparse kernel factorization, a novel time-dependent metric is devised to quantify closeness of candidate kernel similarity matrices to a block diagonal structure. The task is later performed online as newly acquired data are processed making it appropriate for non-stationary settings. The necessary minimization to carry out kernel learning and clustering is performed via an effective interplay among block coordinate descent, difference of convex functions minimization and projected subgradient descent which results in an online iterative algorithm that updates online the kernel covariance matrix, as well as the associated clustering configuration. The resulting recursive kernel updates are proved to converge to a bounded limit. Detailed numerical examples utilizing both synthetic and real data show the superior clustering accuracy achieved by the novel approach over existing alternatives while requiring considerably less running time.

DEVELOPMENT OF AN EXPRESS ASSESSMENT OF THE RESULTS OF GEOLOGICAL AND TECHNICAL MEASURES TAKEN INTO ACCOUNT OF THE GATHERING SYSTEM

This article provides a rationale for the method of «express» assessment of changes in well flow rate when performing geological and technical measures in an oil field. In view of the cluster configuration of wells that is widespread in Western Siberia, the author identifies two groups of well pads, one of which is influencing, the other is reacting. At the influencing well clusters, as a result of the implementation of geological and technical measures to increase extraction from the productive formation, an increase in the produced fluid occurs. This leads to destabilization of the equilibrium in the “reservoir – well – pipeline” system. The consequence of a violation of this balance is an increase in the load on the reservoir fluid pumped in oil and gas gathering pipelines on individual branches of the field collection system. This leads to a redistribution of wellhead pressures at production wells, which, in turn, also leads to a change in bottomhole pressure and a change in well productivity. The author defines well pads where there is no increase in production, but where there is a change in pressure at the wellheads as reactive. With an increase in linear pressure on the pads, the energy balance in the operating production wells at the reacting well pads shifts towards a decrease in flow rate. Conversely, when wellhead pressure decreases, well productivity increases. These parameters will change until the energy balance of pressures in the wells is achieved. In connection with the above, within the framework of this work, an approach is presented for assessing changes in well operating parameters with increasing production in the field. An example of testing the proposed approach on a complex integrated model is given. To test this approach for adequacy, a comparison was made of theoretical calculations of changes in the operation of real wells with calculations performed on a customized complex integrated model of an oil field. It is worth noting that this type of calculation is characterized as approximate. Its use is advisable exclusively at the stage of preparing programs for performing geological and technical measures to determine reservoir zones in which the negative effect of increasing production will be minimal.

Prediction of cluster energy of lithium clusters from codescriptors with application in 2D porous graphene

A lithium metal anode has a high energy density, but its applications face numerous challenges, particularly the irregular deposition of lithium dendrites, which form due to the aggregation of lithium clusters, posing serious safety risks. Research has revealed that small lithium clusters have the potential to enhance the electrode potential in Lithium-ion batteries (LIBs), and cluster energy affects the stability of lithium clusters. Modern computational tools and DFT calculations of lithium clusters can provide invaluable insights into their chemical, physical, and structural properties. However, calculating structural properties through large-scale experiments can be time-consuming and expensive. To overcome the challenges inherent in studying lithium clusters, this study employs a novel approach. We construct molecular graphs for the most stable structures and leverage CoM Polynomial computations to generate codescriptors, enabling efficient and accurate predictions of cluster energy for diverse lithium cluster configurations. The curvilinear regression analysis filters out highly significant regression equations and highly predictive codescriptors. Additionally, we investigated two molecular structures of porous graphene, namely linear and triangular, and obtained topological codescriptors’ analytical expressions by utilizing the CoM Polynomial in each case. A deeper understanding of both lithium clusters and porous graphene properties is essential for optimizing LIBs’ performance and stability.

Customized Heteronuclear Dual Single-Atom and Cluster Assemblies via D-Band Orchestration for Oxygen Reduction Reaction.

Advanced oxygen reduction reaction (ORR) catalysts, integrating with well-dispersed single atom (SA) and atomic cluster (AC) sites, showcase potential in bolstering catalytic activity. However, the precise structural modulation and in-depth investigation of their catalytic mechanisms pose ongoing challenges. Herein, a proactive cluster lockdown strategy is introduced, relying on the confinement of trinuclear clusters with metal atom exchange in the covalent organic polymers, enabling the targeted synthesis of a series of multicomponent ensembles featuring FeCo (Fe or Co) dual-single-atom (DSA) and atomic cluster (AC) configurations (FeCo-DSA/AC) via thermal pyrolysis. The designed FeCo-DSA/AC surpasses Fe- and Co-derived counterparts by 18 mV and 49 mV in ORR half-wave potential, whilst exhibiting exemplary performance in Zn-air batteries. Comprehensive analysis and theoretical simulation elucidate the enhanced activity stems from adeptly orchestrating dz 2-dxz and O 2p orbital hybridization proximate to the Fermi level, fine-tuning the antibonding states to expedite OH* desorption and OOH* formation, thereby augmenting catalytic activity. This work elucidates the synergistic potentiation of active sites in hybrid electrocatalysts, pioneering innovative targeted design strategies for single-atom-cluster electrocatalysts.

Predicting the adsorption configurations of water clusters on –COOH and –OH using DFT calculations

The water in coal causes many negative effects on the processing and utilization of coal. Oxygen-containing functional groups (OFGs) are primary adsorption sites for water molecules on coal surfaces. However, little is known about the adsorption configuration of water clusters on OFGs. In this study, density functional theory (DFT) calculations were used to predict the adsorption configurations of water clusters on –COOH and –OH. The results indicated that water clusters tend to form quadrilateral and cubic shapes on both –COOH and –OH, with quadrilateral water clusters being more stable than cubic water clusters. The cubic water cluster is adsorbed on –COOH through two water molecules that directly form hydrogen bonds with –COOH. In contrast, the cubic water cluster is adsorbed on –OH through a water molecule at one of its vertices. The strong attraction of –COOH to water molecules introduces a minor defect in the cubic water cluster. Because of the synergistic effect of neighboring OFGs on the adsorption of water molecules, the average adsorption energy of water molecules is greater than that of water clusters on a single OFG. These results provide valuable microstructural insights into the adsorption of water on coal.

Spatial Characteristics of Brownfield Clusters and “City-Brown” Patterns: Case Studies of Resource-Exhausted Cities in China

In the post-industrial era, many cities have experienced the decline of heavy industry and traditional manufacturing, leading to the widespread emergence of brownfields. These often cluster geographically, forming “brownfield clusters” characterized by shared spatial and functional traits. Our research examined these phenomena within 10 resource-exhausted cities in China, employing kernel density analysis to explore the spatial dynamics within and among these clusters and their urban contexts. We identified three distinct spatial relationships between brownfield clusters and their host cities (coupling, juxtaposition, and encircling), with a detailed case study in Huangshi City further classifying the clusters into five categories based on their dominant factors, spatial morphologies, types of brownfields, and internal dynamics. The study reveals that the spatial configurations of brownfield clusters are significantly influenced by geographic features, transportation infrastructure, and policy frameworks. Based on these findings, we propose targeted regeneration strategies for each cluster type. This research not only enhances our understanding of brownfield challenges and opportunities in China’s resource-exhausted cities but also serves as a valuable reference for other cities and regions worldwide facing similar challenges.

Evaluating effectiveness of clustering algorithms in multiple target stereotactic radiosurgery

Objective. Single-isocenter-multiple-target technique for stereotactic radiosurgery (SRS) can reduce treatment duration but risks compromised dose coverage due to potential rotational errors. Clustering targets into two groups can reduce isocenter-target distances, mitigating the impact of rotational uncertainty. However, a comprehensive evaluation of clustering algorithms for SRS is absent. This study addresses this gap by introducing the SRS Target Clustering Framework (Framework), a comprehensive tool that utilizes commonly used clustering algorithms to generate efficient cluster configurations. Approach. The Framework incorporates four distinct optimization objectives based on two key metrics: the isocenter-target distance and the ratio of this distance to the target radius. Agglomerative and weighted agglomerative clustering are employed for minimax and weighted minimax objectives, respectively. K-means and weighted k-means are utilized for sum-of-squares and weighted sum-of-squares objectives. We applied the Framework to 126 SRS plans, comparing results to ground truth solutions obtained through a brute force algorithm. Main results. For the minimax objective, the average maximum isocenter-target distance from agglomerative clustering (4.8 cm) was slightly higher than the ground truth (4.6 cm). Similarly, the weighted agglomerative clustering achieved an average maximum ratio of 15.1 compared to the ground truth of 14.6. Notably, both k-means and weighted k-means clustering showed close agreement (within a precision of 0.1) with the ground truth for average root-mean-square target-isocenter distance and ratio (3.6 cm and 11.1, respectively). Significance. These results demonstrate the Framework’s effectiveness in generating clusters for SRS targets. The proposed approach has the potential to become a valuable tool in SRS treatment planning. Furthermore, this study is the first to investigate clustering algorithms for both minimizing maximum and sum-of-squares uncertainty in SRS.

Solvent effects on the structures of the hydrated copper dication clusters

Understanding the solvation process requires an understanding of how the solvent affects the molecular cluster configurations. The current study examined the impact of solvents on the structures of the hydrated Cu2+ cation, as well as the temperature dependence, and the energetics of the hydrated Cu2+ cation clusters from sizes n=1 from n=10 (Cu2+(H2O)n=1−10). The potential energy surfaces (PESs) in the solvent phase (represented by a dielectric continuum medium) at the MP2/6-31++G(d,p) level of computation have been comprehensively investigated. We employed the integral equation formalism polarized continuum model (IEF-PCM) to describe the dielectric continuum medium. It is pointed out that changes in PESs of hydrated copper dication isomers and structural morphologies occur in the continuum medium. Thus, the relative energies are smallest at T=0 K and for the cluster populations of Cu2+(H2O)n=1−10 are modified. Thus, in the solvent phase, the competition between the conformers is more severe than in the gas phase. Furthermore, highly coordinated conformers are more favorable, and favored conformers in the gas phase are disfavored in the solvent phase. The structural investigations are validated by the analysis of Wiberg Bond Index (WBI) at 300 K. In the solvent phase, the WBIs of the most stable isomers are the smallest and the WBIs of axial bonds are lower than those of equatorial bonds. Concerning the energy analysis, the binding energies were predicted for enormous sizes (at saturation) using a fit function. Thus, the new values of the binding energies obtained are -5467.8 and ▪ in the gas and solvent phases respectively. All these observed differences are due to the effects of the implicit solvent.

Enhancing Legal Protection of Children's Rights in the “Internet Plus”

In the contemporary era of the internet, safeguarding children's rights emerges as a critical concern necessitating immediate attention. Given children's heightened vulnerability within society, the legal framework must prioritize their protection, reinforcing their agency and safeguarding their rights through legislative measures. This study proposes an innovative differential clustering algorithm specifically designed to uphold children's rights. Through rigorous experimentation, the algorithm achieves an Adjusted Rand Index (ARI) approaching 2, showcasing its effectiveness in offering targeted differential protection for children's rights while maintaining high clustering precision. The paper emphasizes the importance of noise reduction through iterative central point optimization to stabilize cluster configurations, with the fusion of multiple clusters serving to mitigate noise impacts on data points and yield robust clustering outcomes. Consequently, this research delivers reliable clustering results while preserving the confidentiality of children's rights information.

Structural evolution and electronic properties of anionic plutonium-doped oxygen clusters

Plutonium oxides are important in actinide chemistry and nuclear industry activities, and the demand and interest in enriching knowledge of plutonium chemistry is growing increasingly significant. However, unlike uranium oxide clusters, few studies related to the geometry and bonding properties of anionic plutonium oxide clusters have been reported. Here we explored the geometries, photoelectron spectra, and electronic properties of anionic plutonium oxide clusters by means of unbiased structural searches coupled with density-functional theory (DFT). The results show that the PuO6− cluster with a high D2h symmetry formed by a linear O-Pu-O plutonyl unit with two O2 units exhibits excellent stability. In addition, the HOMO–LUMO gap value of PuO6− cluster are 4.35 eV and 3.41 eV for the α- and β-orbitals, respectively, as well as the vertical detachment energy (VDE) of 4.20 eV. In the analysis of molecular orbitals and adaptive natural density partitioning in oxygen-rich systems, the σ bonds between plutonium atom and oxygen ligands, primarily from the Pu-5f and O-2p orbitals, are responsible for the goodish stability of PuO6− cluster. We hope that the current work can enrich the geometrical configuration of plutonium oxide oxygen clusters and provide reference information for the subsequent research work.

Probing the geometric and electronic structure of rhodium oxide clusters (RhO)n− (n = 2–4) by anion photoelectron spectroscopy and theoretical calculations

The cluster configurations of (RhO)n− (n = 2–4) have been examined using photoelectron (PE) velocity-map imaging combined with density functional theory calculations. The PE spectra have provided the anion detachment energies (ADEs) information of three ground states, determined to be 2.40, 2.86, and 2.94 eV for n = 2–4, respectively. The geometric structures have been identified by comparing the density of states (DOS) spectra of several low-lying isomers with the PE spectra. The three cluster configurations consist of a Rhn (n = 2–4) core with isolated O atoms bonded to the core, exhibiting planar or quasi-planar geometries. The analysis of magnetic moments and spin densities indicated that the most stable three anions have high spin multiplicities of 4, 5, and 4 for n = 2–4, respectively, with the unpaired electrons delocalized on each of the Rh and O atoms.

Disturbance observer‐based matrix‐weighted consensus

AbstractIn this paper, we proposed several disturbance observer‐based matrix‐weighted consensus algorithms. A new disturbance observer is firstly designed for linear systems with unknown matched or mismatched disturbances representable as the multiplication of a known time‐varying matrix with a unknown constant vector. Under some assumptions on the boundedness and persistent excitation of the regression matrix, the disturbances can be estimated at an exponential rate. Then, a suitable compensation input is provided to compensate the unknown disturbances. Second, disturbance‐observer based consensus algorithms are proposed for matrix‐weighted networks of single‐ and double‐integrators with matched or mismatched disturbances. We show that both matched and mismatched disturbances can be estimated and actively compensated, and the consensus system uniformly globally asymptotically converges to a fixed point in the kernel of the matrix‐weighted Laplacian. Depending on the network connectivity, the system can asymptotically achieve a consensus or a cluster configuration. The disturbance‐observer based consensus design is further extended for a network of higher‐order integrators subjected to disturbances. Finally, simulation results are provided to support the mathematical analysis.

Adsorption configuration, electronic structure and spectra of the harmful NH3, NO, and NO2 molecules on a bilayer boron cluster

Density functional theory (DFT) calculations were performed to investigate the adsorption configuration, electronic structure and spectra of a bilayer B48 cluster with NH3, NO, and NO2 adsorptions. The B48 shows a high affinity for NH3 and NO2 molecules and a medium adsorption ability for NO. The high binding strength of the B48 cluster for these gases originates from the direct B–N bonds corresponding to partially covalent characters. The energy gap changes are in the order of NO2 > NH3 > NO. The recovery time of the B48 for different gases can be adjusted to a reasonable range by increasing the temperature. Infrared (IR) and ultraviolet–visible (UV–vis) spectra were in detail analyzed before and after gas adsorptions for the identification of the adsorption structures in further experiments. Along with gas adsorption, the B48 cluster exhibits vastly different spectral characteristics. Our results indicate that the B48 shows promising sensor performance for studied gases, in particular for NO molecules, and can be considered as potential gas sensor candidates.