The poor oxidation resistance and structural stability of Ti₃C₂(OH)₂ largely limit its wide applications. In this work, the surface adsorption behaviors of oxygen atoms on Ti₃C₂(OH)₂, polyaniline (PANI) and PANI/Ti₃C₂(OH)₂ composite were systematically studied and compared by first-principles calculation method. The simulation results suggest that the existence of -OH functional group can change the active sites on Ti₃C₂ matrix. Thereby the oxidation resistance and the structural stability of Ti₃C₂ matrix can be improved in some extent. Furthermore, after modifying Ti₃C₂(OH)₂ by PANI, the adsorption activity of PANI is much larger. Meanwhile, the adsorption energy of oxygen on the Ti₃C₂(OH)₂ end is significantly decreased, which is caused by the electron transfer from PANI to Ti₃C₂(OH)₂, as confirmed by the Bader charge calculation. Therefore, the oxidation resistance and the structural stability of the PANI modified Ti₃C₂(OH)₂ composite are improved by sacrificing PANI, since oxygen prefers to adsorb and attack PANI firstly. This work provides theoretical guidelines for the improvement of oxidation resistance, structural and chemical stability of MXene.

Sodium-ion batteries are economical and environmentally sustainable energy storage batteries. Among them, β-NaMnO₂, a promising sodium-ion cathode material, is a manganese-based oxide with a corrugated laminar structure, which has attracted significant attention due to its structural robustness and relatively high specific capacity. However, it has short cycle life and poor rate capability. To address these issues, Ti atoms, known for enhancing structural stability, and Cu atoms, which facilitate desodiation, were doped into β-NaMnO₂ by first-principles calculation and crystal orbital Hamilton population (COHP) analysis. β-NaMn_0.8Ti_0.1Cu_0.1O₂ exhibits a notable increase in reversible specific capacity and remarkable rate properties. Operating at a current density of 0.2C (1C = 219 mA·g^-1) and within a voltage range of 1.8-4.0 V, the modified material delivers an initial discharge capacity of 132 mAh·g^-1. After charge/discharge testing at current densities of 0.2C, 0.5C, 1C, 3C, and 0.2C, the material still maintains a capacity of 110 mAh·g^-1. The doping of Ti atoms slows down the changes in the crystal structure, resulting in only minimal variation in the lattice constant c/a during the desodiation process. Mn and Cu engage in reversible redox reactions at voltages below 3.0 V and around 3.5 V, respectively. The extended plateau observed in the discharge curve below 3.0 V signifies that Mn significantly contributes to the overall battery capacity. This study provides insights into modifying β-NaMnO₂ as a cathode material, offering experimental evidence and theoretical guidance for enhancing battery performance in Na-ion batteries.

Platinum (Pt)-based noble metal catalysts (PGMs) are the most widely used commercial catalysts, but they have the problems of high cost, low reserves, and susceptibility to small-molecule toxicity. Transition metal oxides (TMOs) are regarded as potential substitutes for PGMs because of their stability in oxidizing environments and excellent catalytic performance. In this study, comprehensive investigation into the influence of elastic strains on the adsorption energies of carbon (C), hydrogen (H) and oxygen (O) on TMOs was conducted. Based on density functional theory (DFT) calculations, these effects in both tetragonal structures (PtO₂, PdO₂) and hexagonal structures (ZnO, CdO), along with their respective transition metals were systematically explored. It was identified that the optimal adsorption sites on metal oxides pinpointed the top of oxygen or the top of metal atom, while face-centered cubic (FCC) and hexagonal close-packed (HCP) holes were preferred for the transition metals. Furthermore, under the influence of elastic strains, the results demonstrated significant disparities in the adsorption energies of H and O between oxides and transition metals. Despite these differences, the effect of elastic strains on the adsorption energies of C, H and O on TMOs mirrored those on transition metals: adsorption energies increased under compressive strains, indicating weaker adsorption, and decreased under tension strains, indicating stronger adsorption. This behavior was rationalized based on the d-band model for adsorption atop a metallic atom or the p-band model for adsorption atop an oxygen atom. Consequently, elastic strains present a promising avenue for tailoring the catalytic properties of TMOs.

Bioceramics have attracted extensive attention for bone defect repair due to their excellent bioactivity and degradability. However, challenges remain in matching the rate between bioceramic degradation and new bone formation, necessitating a deeper understanding of their degradation properties. In this study, density functional theory (DFT) calculations was employed to explore the structural and electronic characteristics of silicate bioceramics. These findings reveal a linear correlation between the maximum isosurface value of the valence band maximum (VBM_Fmax) and the degradability of silicate bioceramics. This correlation was subsequently validated through degradation experiments. Furthermore, the investigation on phosphate bioceramics demonstrates the potential of this descriptor in predicting the degradability of a broader range of bioceramics. This discovery offers valuable insights into the degradation mechanism of bioceramics and holds promise for accelerating the design and development of bioceramics with controllable degradation.

Hf_xTa_1-xC is a very promising candidate for thermal protection materials above 2000 ℃ due to its excellent properties such as high melting point, high hardness, high strength, high electrical conductivity, and high thermal conductivity. However, the rules of its mechanical properties and melting temperature varying with the composition remain elusive. Firstly, the mechanism of the variation of mechanical properties of Hf_xTa_1-xC system solid solutions with its components was systematically investigated from the microscopic point of view of covalent bond strength and valence electron concentration (VEC) based on the special quasirandom structures (SQS) method and first-principles calculations. It revealed that among the five components of solid solutions (i.e., HfC, Hf_0.75Ta_0.25C, Hf_0.5Ta_0.5C, Hf_0.25Ta_0.75C and TaC), the Hf_0.25Ta_0.75C solid solution possessed the largest elastic modulus and shear modulus. It was mainly attributed to two reasons: (1) the component possessing the strongest covalent bonding strength among the above ternary compounds; (2) the special bonding states between the p-orbital from C and the d-orbital from Hf or Ta strongly resisting the deformation and being completely filled near VEC=8.75 (for Hf_0.25Ta_0.75C). Secondly, the melting curves of the Hf_xTa_1-xC system solid solutions were calculated using the ab initio molecular dynamics (AIMD)-based molecular dynamics Z method. It showed that there existed indeed the phenomenon for anomalous increase in the melting temprature of Hf_xTa_1-xC system solid solutions, and the highest melting temperature of 4270 K was predicted on Hf_0.5Ta_0.5C, which was mainly attributed to the synergistic effect of the conformational entropy and the strength of the covalent bond. The results provide a theoretical guidance for the experimental selection of the optimal components of high melting temprature and high mechanical properties for Hf_xTa_1-xC system solid solutions in the thermal barrier coating applications, as well as a reference for the study of other transition metal carbides.

Among all options of carbon neutrality, conversion of CO₂ into valuable chemicals by electrocatalytic reduction exhibit outstanding performance. However, due to the numerous products and complex pathways of CO₂ electrocatalytic reduction, the exact factors affecting the activity of CO₂ electrocatalytic reduction have not yet been identified. In addition, the CO₂ electrocatalytic reduction process is often accompanied by hydrogen evolution reaction (HER). Therefore, it is still challenging to design a catalyst with high selectivity and high activity for specific product. Herein, this study systematically investigated the potential of 3d transition metal-based single-atom catalysts (SACs) positioned at graphene single vacancies (TM@C_SV), as well as double vacancies (TM@C_DV), for the CO₂ reduction reaction (CO₂RR) using first-principles. The exploration encompassed substrate stability, CO₂ adsorption, and the HER as the main competing reaction. Through the careful screening of 20 catalysts formed by Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu and Zn doped graphene defects, several promising catalysts were identified: Sc@C_SV situated on graphene single vacancies, Sc@C_DV and Ti@C_DV situated on graphene double vacancies. They could not only effectively adsorb CO₂ molecules, but also inhibit HER, the main competing reaction. In assessing their performance in CO₂RR, all exhibited selectivity toward HCOOH. Notably, Sc@C_DV demonstrated the best selectivity, requiring the lowest ΔG (0.96 eV) for efficient CO₂ conversion to HCOOH. Electronic structure analysis revealed that Sc@C_DV outperforms due to its optimal balance between ΔG of hydrogenation and the product desorption achieved through a moderate number of active electrons.

In the industrial landscape, the well-established Haber-Bosch method is employed for the catalytic synthesis of ammonia (NH₃) from hydrogen and nitrogen gases, necessitating elevated temperatures (400-600 ℃) and high pressures (150-300 atm, 1 atm= 0.101325 MPa). In response to the imperative to reduce energy consumption and environment impact imposed by this synthetic process, significant research efforts have converged on realizing NH₃ synthesis under ambient conditions. This study delves into the realm of N₂ electrocatalytic reduction to NH₃, using density functional theory (DFT) calculations to explore the feasibility of employing graphene co-doped with a combination of transition metal elements (e.g., Fe, Nb, Mo, W, and Ru) and non-metal elements (e.g., B, P, and S) as catalyst for ammonia synthesis. The findings underscore that Mo and S co-doped graphene (Mo/S graphene) demonstrates an exceptionally low electrode potential of 0.47 V for NH₃ synthesis, with the key rate-controlling step centered around the formation of the intermediate *NNH. Especially, the ammonia synthesis potential is found to be lower than the hydrogen evolution potential (0.51 V), conclusively affirming the selectivity of nitrogen reduction to ammonia. Furthermore, through ab initio molecular dynamics calculations, the study attests to the remarkable thermodynamic stability of the Mo/S co-doped graphene system under room temperature conditions. Notably, electronic structure analysis validates that the ability of electron communication of the transition metal plays a pivotal role in dictating the efficiency of N₂ electrocatalytic reduction. It can be tactically optimized through controlled modulation of the influence of the non-metal element on the coordination environment of the transition metal, thus substantially enhancing catalytic performance.

Activated carbon's porous nature and high specific surface area make it an effective tool for adsobing waste gas containing styrene. However, the mechanism by which oxygen-containing functional groups adsorb weak-polar styrene remains unclear. This study described the preparation of the modified activated carbon materials AC-S and AC-N using the acid leaching method. The pore structure and specific surface area of modified activated carbon, the evolution of oxygen-containing functional groups, and their impact on the styrene-adsorbing performance were investigated. The results demonstrated that acid modification significantly improved the styrene-adsorbing capacity of activated carbon. Physical and chemical adsorption impacted both modified and unmodified activated carbon materials, as determined by the adsorption kinetics studies and isotherm fitting analyses. Monolayer adsorption was more likely to occur on modified activated carbon. HNO₃-modified activated carbon (AC-N) maintained its effective styrene adsorption pore size range. The increasing number of oxygen-containing functional groups on the surface improved the styrene adsorption performance of AC-N. Study of oxygen-containing functional groups on the surface revealed that lactone group was a key factor in improving the modified activated carbon's ability to adsorb styrene. Density functional theory (DFT) calculations showed that lactone group on AC-N strongly interacted with the vinyl group in styrene, thereby enhancing the styrene adsorption performance of modified activated carbon.

Nowadays, artificial intelligence (AI) is playing an increasingly important role in human society. Running AI algorithms represented by deep learning places great demands on computational power of hardware. However, with Moore's Law approaching physical limitations, the traditional Von Neumann computing architecture cannot meet the urgent demand for promoting hardware computational power. The brain-inspired neuromorphic computing (NC) employing an integrated processing-memory architecture is expected to provide an important hardware basis for developing novel AI technologies with low energy consumption and high computational power. Under this conception, artificial neurons and synapses, as the core components of NC systems, have become a research hotspot. This paper aims to provide a comprehensive review on the development of oxide neuron devices. Firstly, several mathematical models of neurons are described. Then, recent progress of Hodgkin-Huxley neurons, leaky integrate-and-fire neurons and oscillatory neurons based on oxide electronic devices is introduced in detail. The effects of device structures and working mechanisms on neuronal performance are systematically analyzed. Next, the hardware implementation of spiking neural networks and oscillatory neural networks based on oxide artificial neurons is demonstrated. Finally, the challenges of oxide neuron devices, arrays and networks, as well as prospect for their applications are pointed out.

Heteroepitaxy provides an effective path for the synthesis of diamond wafers. After more than 20 years of development, the diamond nucleation and growth technology on iridium substrates has enabled to prepare crystals with a maximum diameter of 3.5 inches, which opens a door to application diamond as ultimate semiconductor in the future chip industry. However, a series of problems that occur on heterogeneous substrates, such as surface nucleation, bias process window, and diamond epitaxial growth, need to overcome from the perspective of growth thermodynamics. In this study, aiming at the key issue how diamond can achieve epitaxial nucleation and growth in chemical vapor deposition atmosphere, a simulation study was carried out on the nucleation and growth process of diamond at the atomic scale based on the first-principle calculation. The results show that the adsorption of C atoms on the surface of the Ir substrate is more stable than that on the bulk phase, which indicates that diamond nucleation can only occur on the substrate surface. The number of C atoms of sp³ hybridization in the amorphous hydrogenated carbon layer increases firstly and then decreases with the increase of ion kinetic energy under ion bombardment, confirming the existence of the ion kinetic energy or bias voltage window in the high-density nucleation of diamond. The interfacial binding energy is the lowest (about -0.58 eV/C) when diamond is epitaxially grown along the Ir substrate, meaning that the interface binding energy is the decisive thermodynamic factor for the epitaxial growth. In conclusion, this study clarifies the thermodynamic mechanism of single crystal diamond epitaxial growth under the bias-assisted ion bombardment, and points out a great significant guidance for the growth of diamond and other carbon based semiconductors.

As a fundamental light source and a good window for atmospheric transmission, the mid-infrared 3 μm lasers have led many promising applications. The rare earth doped crystalline materials, such as erbium doped crystals, are some of the most important routes for generation of the lasers. However, they have an intrinsic shortcoming of self-termination because of their short lifetime of ⁴I_11/2 and longer lifetime of ⁴I_13/2. To eliminate this effect, a high concentration doping method is usually adopted to change the energy transfer process to decrease ⁴I_13/2 lifetime. The efficiency and output power of Er³⁺-doped crystals were thus limited due to their degraded thermal properties. Trivalent erbium ions are easily clustering in fluoride crystals. Distances among the ions are short and therefore energy transfer processes could be significantly improved in the crystals even doping with low concentrations. Low doping concentrations could also alleviate the thermal effect in laser operations, which enable the erbium doped fluorides to be promising candidates for high power and high efficiency mid-infrared lasers. However, connection of spectral properties and erbium clusters is unknown. Here, the first principles calculation is utilized to model the erbium ion clusters in CaF₂, SrF₂ and PbF₂ crystals, concerning the absorption and photoluminescence properties. The results reveal that spectral properties and structures of the erbium clusters, evolve gradually with matrix crystals. Relationship between spectral properties and optical erbium clusters is determined qualitatively, which could be used to design new erbium doped mid-infrared lasers.

Zr₂SB, Hf₂SB, Zr₂SeB, Hf₂SeB, and Hf₂TeB are all recently discovered S-group elements containing MAX-phase borides, which attract much attention since the MAX phase borides are significantly unlike the typical MAX phases. Here, the phase stability, mechanical properties and thermal properties of MAX phase borides (M = Zr, Hf, A = S, Se, Te) were studied by using first principles and "linear optimization method", bond stiffness model and quasi-simple harmonic approximation. The results of the theoretical analysis were consistent with the currently available experimental results. Only M₂AB was found to be stable after thermodynamic and intrinsic stability analysis. The shorter M−A bond and M−B bond lengths cause bond stiffness of Hf lineage higher than that of Zr, which also leads to the higher hardness of Hf lineage compound than that of Zr. the A site element goes from S to Se and to Te, the bond lengths of M−B and M−A are gradually increased, which lead to decrease in the elastic modulus. Moreover, the bulk modulus of these compounds is determined by their average chemical bond stiffness. Importantly, the high k_min/k_max (stiffness ratio of the weakest and the strongest bonds) shows that these MAX phases are inherently brittle, different from conventional MAX phase. Including the contribution of lattice vibration (phonon) and electron excitation, the isobaric heat capacity and heat expansion coefficient of M₂AB increase rapidly with increasing the temperature below 300 K and then the rise rate gradually decreases, similar to other MAX phases. Lower bond stiffness results in an overall higher TEC of MAX phase borides in the Zr lineage than in the Hf lineage. The TEC values of these compounds in the 300−1300 K interval are consistent with most of the MAX and MAB phases.

In a high vacuum environment, some organic molecular pollutants such as hydrocarbon and siloxane are released by spacecraft materials and deposited on the surface of the sensitive parts of spacecraft devices, which has become an important adverse factor restricting the development of long-life and high-performance spacecraft. Zeolite molecular adsorber coating can effectively collect spatial contaminations in real time, but the adsorption mechanism is not clear. To deeply analyze the adsorption mechanism of zeolite on the spatial contaminations, the adsorption behaviors of NaY zeolite including adsorption isotherms, adsorption heat curves and density distributions on three typical contaminations, toluene(C₇H₈), dimethyl phthalate (C₁₀H₁₀O₄), octamethyl cyclotetrasiloxane (C₈H₂₄O₄Si₄), were calculated by the Grand Canonical Monte Carlo method in this work. The NaY zeolites and pollutant models were successfully constructed, and the rationality of the models was verified by comparing simulated data with experimental ones. These results indicated that all three classic molecules can be adsorbed by NaY zeolite in the ultra-high vacuum condition. The saturated adsorption capacity decreases in the order of C₇H₈>C₁₀H₁₀O₄>C₈H₂₄O₄Si₄, which is significantly related to the molecule sizes and structures of contaminations. The saturated adsorption amount of C₈H₂₄O₄Si₄ is relatively low (8 per cell) when that of C₇H₈ is 36 per cell. In addition, the density distributions indicates that different contaminations are preferentially adsorbed inside the super-cage of NaY zeolite. Overall, this work analyzes the adsorption mechanism of NaY zeolite on typical contaminations, and can provide basic insights for the development of zeolite molecular adsorber coating with high adsorption capacity.

Due to the characteristics of small samples, high dimensions, and much noise, materials data often produce inconsistent results with those obtained from domain experts when used for machine learning modeling. For the whole process of machine learning, developing machine learning models embedding materials domain knowledge is a solution to this problem. The accuracy of materials data directly affects the reliability of data-driven materials performance prediction. Here, a data accuracy detection method incorporating materials domain knowledge is proposed by focusing on the data preprocessing stage in the machine learning application process. Firstly, a materials domain knowledge database is constructed based on the knowledge from materials experts. Secondly, it is coordinated with the data-driven data accuracy detection method to perform single-dimensional data accuracy detection based on the rule for value of descriptors, multi-dimensional data correlation detection based on the rule for correlation of descriptors, and full-dimensional data reliable detection based on multi-dimensional similar sample identification strategy from both data and domain knowledge perspectives. For the anomalous data identified at each stage, they are corrected by incorporating the materials domain knowledge. Furthermore, domain knowledge is incorporated into the whole process of the data accuracy detection method to ensure high accuracy of the dataset from the initial stage. Finally, experiments on the NASICON-type solid electrolyte activation energy prediction dataset demonstrate that this method can effectively identify anomalous data and make reasonable corrections. Compared with the original dataset, the prediction accuracy of all six machine learning models based on the revised dataset is improved to different degrees, among which R² achieves a 33% improvement on the optimal model.

Density functional theory calculations play an important role in the study of defects in halide perovskites. Although the traditional semi-local functionals (such as PBE) can obtain the band gaps close to the experiments, they fail to accurately describe the positions of the band edges. Utilizing more accurate hybrid functionals combined with the spin-orbit coupling (SOC) effect with full structure relaxation is considered to be necessary for the prediction of defect properties. There are two types of hybrid functionals in the literature, namely the screened HSE and the unscreened PBE0. In this study, taking the orthorhombic phase CsPbI₃ as an example, these methods were compared for the calculation of defect properties. The results show that there is no obvious difference between two methods for bulk properties, but qualitative differences appear for the defect properties. Most of the shallow-level defects predicted in the HSE calculations become deep-level defects in the PBE0 calculations. Meanwhile, there are qualitative differences between the defect transition levels and the Kohn-Sham levels. The origin of above differences lies in the fact that the Hartree-Fock exchange potential has long-range interaction. Therefore, in unscreened hybrid functionals, such as PBE0, it is more difficult to obtain convergent results with a manageable supercell size. In contrast, HSE exhibits a screening effect on the Hartree-Fock exchange potential and can obtain accurate defect energy levels using relatively small supercell sizes. Therefore, all results here demonstrate that the HSE hybrid functional owns a significant advantage in dealing with this problem even though a large Hartree-Fock mixing parameter (about 0.43) is needed.

MAX/MAB phases are a series of non-van der Waals ternary layered ceramic materials with a hexagonal structure, rich in elemental composition and crystal structure, and embody physical properties of both ceramics and metals. They exhibit great potential for applications in extreme environments such as high temperature, strong corrosion, and irradiation. In recent years, two-dimensional (2D) materials derived from the MAX/MAB phase (MXene and MBene) have attracted enormous interest in the fields of materials physics and materials chemistry and become a new 2D van der Waals material after graphene and transition metal dichalcogenides. Therefore, structural modulation of MAX/MAB phase materials is essential for understanding the intrinsic properties of this broad class of layered ceramics and for investigating the functional properties of their derived structures. In this paper, we summarize new developments in MAX/MAB phases in recent years in terms of structural modulation, theoretical calculation, and fundamental application research and provide an outlook on the key challenges and prospects for the future development of these layered materials.

Ultraviolet (UV) nonlinear optical (NLO) crystals play an irreplaceable role as the key materials to realize the frequency conversion for all solid state lasers. To date, it is still difficult to design UV NLO crystals with large second harmonic generation (SHG) coefficients, moderate birefringences and wide band gaps. Benefiting from the large band gap, sulfate has become an important research direction of UV NLO crystals. However, since SO₄ is isotropic tetrahedral building units with nearly nonpolar T_d symmetry, it exhibits small microscopic second order polarizability and polarizability anisotropy, which tends to result in a weak SHG effect and small birefringence. In this work, we introduced Hg²⁺ ions that are easy to form distorted polyhedrons into the sulfates, resulting in a new NLO material, Rb₃Hg₂(SO₄)₃Cl. It crystallizes in a monoclinic space group (P2₁) with the lattice parameters a=0.78653(2) nm, b=0.97901(2) nm, c=1.00104(3) nm, and β=110.95(3) (Z=2). Structure of Rb₃Hg₂(SO₄)₃Cl consists of [SO₄] tetrahedra, [HgO₅] and [HgO₄Cl] polyhedral, which connected by a common corner to form a spatial 3D network. All the Rb atoms reside in the cavity of 3D network. The powder SHG measurement proposed by Kurtz and Perry indicates that Rb₃Hg₂(SO₄)₃Cl is a phase-matchable material in the visible region and exhibits a moderate SHG response about 1.5 times that of KH₂PO₄ (KDP). In addition, the UV-Vis-NIR diffuse reflectance spectral measurement indicates that Rb₃Hg₂(SO₄)₃Cl has a short UV cut-off edge of 251 nm, corresponding to the band gap of 4.94 eV. Its polarizing microscope measurement reveals that Rb₃Hg₂(SO₄)₃Cl has a moderate birefringence (The birefringence of Rb₃Hg₂(SO₄)₃Cl crystal at 546.1 nm is 0.04). Moreover, first-principles calculations uncover that the distorted [HgO₅], [HgO₄Cl] and [SO₄] polyhedral are responsible for its SHG effect. Our study shows that Rb₃Hg₂(SO₄)₃Cl may have potential applications as a UV NLO crystal.

Wide band gap γ-CuI is a p-type transparent semiconductor with excellent optoelectronic and thermoelectric property, which has recently attracted worldwide attention. However, as an emerging material, its luminescence mechanism that is impacted by defects is rarely reported and remains obscure, limiting its further applications. In this work, Cl-doped CuI film was prepared by gas-phase reaction method. Using cathodoluminescence spectroscopy, effects of Cl doping on the surface morphology and cathodoluminescence property of CuI films were investigated in detail, and main defects of Cl presence in CuI films were explored by combining first-principle calculations, revealing relationship between structure and luminescent property of Cl-doped CuI films. These data showed Cl-doped region had a smoother surface than that of the undoped region with granular morphology, which clearly demonstrated that Cl dopant altered surface structure of the undoped region. Compared with the undoped region, the Cl dopant induced doubled fluorescence signal of band-edge emission at 410 nm, but reduced the defect peak at 720 nm, indicating that a small amount of Cl dopant brought a great luminescent improvement to CuI. The formation energy calculations of various crystal defects suggest that Cl can inhibit the formation of deep-level defects such as I vacancy in CuI and reduce the probability of non-radiative transition of excitons, which is consistent with the cathodoluminescence results. The full width at half maximum of the band-edge luminescence peak of Cl-doped CuI film is as small as 7 nm, showing extremely high luminescence monochromaticity. Therefore, the present findings deepen our understanding on how halogen doping boosts the luminescence performance of CuI-based materials.

High energy particle bombardment of silicon carbide can lead to the accumulation of defects and lattice disorder, which can negatively affect physical property and reduce lifetime of SiC devices. Thus, it is essential to systematically study the damage of SiC in different radiation environment. Herein, 6H-SiC was irradiated by neutrons at the fluence of 5.74×10¹⁸, 1.74×10¹⁹, 2.58×10²⁰ and 1.27×10²¹ n/cm², and then annealed. Changes in lattice parameters from post-irradiation isochronal annealing for 30 min in the range of 500-1650 ℃ were measured using X-ray single crystal diffraction. The results showed that the lattice swelling and recovery behavior were isotropic. Based on the swelling data, it was concluded that the neutron irradiation-induced defects in 6H-SiC were primarity point defects. Both intrinsic and irradiation defects can introduce defect energy levels, which were mainly caused by vacancies and led to the absorption band edge redshift and band gap narrowing of SiC. The defect energy levels of these vacancies and vacancy-associated defects were determined by absorption spectra, luminescence spectra and Raman spectra. Experiments and first principles calculation showed that the silicon vacancies introduced defect levels above the valence band, while the carbon vacancies introduced levels below the conduction band. The infrared absorption at 1382 nm and 1685 nm and the emission at 550 nm of unirradiated 6H-SiC were mainly due to the intrinsic carbon vacancies. The luminescence of post-irradiated SiC at 415, 440 and 470 nm was mainly due to the silicon vacancy produced by irradiation and its related defect configuration. All above data revealed the luminescence mechanism of SiC based on the charge state and the defect energy level distribution.

Large-sized crystalline materials are the basic raw materials in semiconductors, lasers, and communications. Preparation of large-scale, high-quality crystalline materials has become a bottleneck restricting the development of related industries. Breaking through the preparation theory and technology of large-sized crystal materials is the key to obtaining high-quality large-sized crystals. Preparation process of crystal materials often undergoes nucleation and growth stages, including multiple processes at spatiotemporal scale: from atom/molecules, through clusters and nuclei, to bulk crystals. To further explore and accurately understand the crystal growth mechanism, we need intensively study the multiscale process,multi-scale in situ characterization techniques, and computational simulation methods. Among them, the latest in situ characterization methods for crystal growth includes optical microscopy, electron microscopy, vibration spectra, synchrotron radiation, neutron technology, and especially, machine learning method. Thus, the multi-scale computational simulation techniques for crystallization is introduced, for example, first principles calculation at atom/molecular scale, molecular dynamics simulation, Monte Carlo simulation, phase field simulation at mesoscopic scale, and finite element simulation at macroscopic scale. A single in situ characterization or simulation technique can only explore crystallization information over a specific time and space scale. To accurately and fully reflect the crystallization process, a combination of multi-scale methods is introduced. It can be speculated that the establishment of in situ characterization technology and computational simulation methods for the actual large-sized crystal growth environment will be the future development trend, which provides an important experimental and theoretical basis for developing crystallization theory and controlling crystal quality. Furthermore, it can be deduced that the combination of in situ characterization technology with machine learning and big data technology will be the trend for large-sized crystal growth.