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IntroductionHigh-yield and high-quality production of silage maize in cold regions is crucial for ensuring the sustainable development of livestock industry.MethodsThis study first conducted an experiment to select the optimized silage maize varieties and densities using a split-plot design. The tested maize varieties were Xuntian 3171, Xuntian 16, Xunqing 858, and Fengtian 12, with each variety planted at densities of 67,500, 79,500, and 90,000 plants ha-1. Following the variety and density selection, another experiment on optimizing nitrogen management for silage maize was carried out using a completely randomized design: no nitrogen fertilizer (T1), applying urea-N 320 kg ha-1 (T2), applying urea-N 240 kg ha-1 (T3), applying polymer-coated urea-N 240 kg N ha-1 (T4), and ratios of polymer-coated urea-N to urea-N at 9:1 (T5), 8:2 (T6), 7:3 (T7), and 6:4 (T8). T5-T8 all applied 240 kg N ha-1. The yield and quality of silage maize, nitrogen use efficiency and balance, and economic benefits were evaluated.ResultsResults showed that Xunqing 858 had significantly higher plant height (8.7%-22.6% taller than the other three varieties) and leaf area (30.9% larger than Xuntian 3171), resulting in yield 11.5%-51.6% higher than the other three varieties. All varieties achieved maximum yields at a planting density of 79,500 plants ha-1. Integrated management strategy 7 (T7: Xunqing 858, 79,500 plants ha-1, polymer-coated urea-N to urea-N ratio of 7:3) achieved the highest yield of 73.1 t ha-1, a 6.1%-58.1% increase over other treatments. This strategy also produced the highest crude protein (11.1%) and starch (19.1%) contents, and the lowest neutral detergent fiber content (50.6%), with economic benefits improved by 10.3%-97.8% compared to other strategies. Additionally, T7 improved nitrogen use efficiency by 15.4%-94.5%, reduced soil nitrate leaching by 4.4%-36.5%, and decreased nitrogen surplus by 7.0%-46.6%.Conclusion and discussionComprehensive analysis revealed that the integrated management strategy 7 significantly improved silage maize yield and quality in cold regions while enhancing nitrogen use efficiency and reducing the risk of nitrate leaching, aligning with green agriculture development requirements. These findings will provide vital theoretical insights and practical guidance for high-yield and high-quality silage maize production in cold regions worldwide.

The valley index is a promising degree of freedom for information processing in electronic devices. However, the researches on valley polarization are mainly focused on ferromagnetic order, which breaks the time reversal symmetry simultaneously. Here, a novel paradigm for achieving stacking order modulated anomalous valley Hall (AVH) effect is proposed in antiferromagnetic monolayers. The paradigm involves the introduction and reversal of nonuniform potentials by modulating the position of substrate, to break the combined symmetry of spatial inversion and time reversal (PT symmetry) and achieve stacking-dependent valley spin splitting. Based on first-principles calculations, we discover spontaneous valley polarization in antiferromagnetic Cr2CH2 MXene and stacking-dependent valley spin splitting in Cr2CH2/Sc2CO2 heterostructure. Furthermore, switching the ferroelectric polarization of monolayer Sc2CO2 results in a semiconductor-metal transition in Cr2CH2/Sc2CO2, accompanied by the disappearance of valley physics. Our findings provide an alternative way to develop controllable valleytronics devices based on antiferromagnetic monolayers.

Summary: Machine learning interatomic potential (MLIP) overcomes the challenges of high computational costs in density-functional theory and the relatively low accuracy in classical large-scale molecular dynamics, facilitating more efficient and precise simulations in materials research and design. In this review, the current state of the four essential stages of MLIP is discussed, including data generation methods, material structure descriptors, six unique machine learning algorithms, and available software. Furthermore, the applications of MLIP in various fields are investigated, notably in phase-change memory materials, structure searching, material properties predicting, and the pre-trained universal models. Eventually, the future perspectives, consisting of standard datasets, transferability, generalization, and trade-off between accuracy and complexity in MLIPs, are reported.

Abstract Perovskite-type lead-free piezoelectric ceramics allow access to illustrious piezoelectric coefficients (d 33) through intricate composition design and experimental modulation. Developing a swift and accurate technology for identifying (K, Na)NbO3 (KNN)-based ceramic compositions with high d 33 in exceedingly large “compositional” space will establish an innovative research paradigm surpassing the traditional empirical trial-and-error method. Herein, we demonstrate an interpretable machine learning (ML) framework for quick evaluation of KNN-based ceramics with high d 33 based on data from published literature. Specifically, a thorough feature construction was carried out from the global and local dimensions to establish tree regression models with d 33 as the target property. Subsequently, the feature-property mapping rules of KNN-based piezoelectric ceramics are further optimized through feature screening. To intuitively understand the correlation mechanisms between ML regression targets and features, the sure independence screening and sparsifying operator (SISSO) method was employed to extract the essential descriptors to explain d 33. A straightforward descriptor, $${\text{e}}^{({{NM}}_{\text{B}}-{{MV}}_{\text{B}})}\cdot {ST}/{(I{D}_{\text{A}})}^{2}$$ e ( NM B − MV B ) ⋅ ST / ( I D A ) 2 , consisting of only four easily accessible parameters, can accelerate the evaluation of a series of novel KNN-based ceramics with high d 33 while exhibiting strong theoretical interpretability. This work not only provides a tool for the rapid discovery of high piezoelectric performance in KNN-based ceramics but also offers a data-driven route for the design of property descriptors in perovskites.

Abstract Despite recent advances in exfoliated vdW ferromagnets, the widespread application of 2D magnetism requires a Curie temperature (Tc) above room temperature as well as a stable and controllable magnetic anisotropy. Here we demonstrate a large-scale iron-based vdW material Fe4GeTe2 with the Tc reaching ~530 K. We confirmed the high-temperature ferromagnetism by multiple characterizations. Theoretical calculations suggested that the interface-induced right shift of the localized states for unpaired Fe d electrons is the reason for the enhanced Tc, which was confirmed by ultraviolet photoelectron spectroscopy. Moreover, by precisely tailoring Fe concentration we achieved arbitrary control of magnetic anisotropy between out-of-plane and in-plane without inducing any phase disorders. Our finding sheds light on the high potential of Fe4GeTe2 in spintronics, which may open opportunities for room-temperature application of all-vdW spintronic devices.

Summary: Background: Ustekinumab and vedolizumab are both effective for treating Crohn’s disease (CD). However, no head-to-head trials have been conducted thus far. We aimed to compare the effectiveness of ustekinumab and vedolizumab in CD patients either naïve or exposed to tumor necrosis factor-alpha inhibitors (TNFi). Methods: Patients treated with vedolizumab or ustekinumab for luminal CD were included from six centers in China from May 2020 to July 2023. Steroid-free remission, clinical remission, objective response, and remission at Weeks 26 and 52 were evaluated in a retrospective multicenter propensity score–weighted cohort. Findings: A total of 536 patients were included (386 ustekinumab, and 150 vedolizumab). After adjustment, ustekinumab showed higher rates of clinical remission (56.4% vs. 47.8%, P = 0.005), steroid-free remission (55.4% vs. 46.1%, P = 0.003), and objective response (67.8% vs. 42.7%, P

MXene is a promising candidate for the next generation of lightweight electromagnetic interference (EMI) materials owing to its low density, excellent conductivity, hydrophilic properties, and adjustable component structure. However, MXene lacks interlayer support and tends to agglomerate, leading to a shorter service life and limiting its development in thin-layer electromagnetic shielding material. In this study, we designed self-assembled TiO2-Ti3C2Tx materials with a ball–plate structure to mitigate agglomeration and obtain a thin-layer and multiple absorption porous materials for high-efficiency EMI shielding. The TiO2-Ti3C2Tx composite with a thickness of 50 μm achieved a shielding efficiency of 72 dB. It was demonstrated that the ball–plate structure generates additional interlayer cavities and internal interface, increasing the propagation path for an electromagnetic wave, which, in turn, raises the capacity of materials to absorb and dissipate the wave. These effects improve the overall EMI shielding performance of MXene and pave the way for the development of the next-generation EMI shielding system.

The electrocatalytic nitrogen reduction reaction (NRR) is currently constrained by sluggish reaction kinetics and poor selectivity because of the difficulties in activating inert N≡N triple bonds and the existence of competing hydrogen evolution reaction (HER). Therefore, electrocatalysts with high activity, selectivity, and stability are highly desired. Herein, by means of first-principles calculations, we investigated the electrocatalytic NRR performance of a series of transition metal atoms (e.g., 3d, 4d, and 5d) embedded in defective hexagonal MBene nanosheets [h-Zr(Hf)2B2O2] and identified that h-Zr(Hf)2B2O2 could be an excellent platform for electrocatalytic NRR. On the basis of our proposed screening criteria, 16 candidates are efficiently selected out from 50 systems, among which, Zr2B2O2-Cr stands out with high selectivity to NRR against HER and the ultralow limiting potential (−0.10 V). The value is much lower than that of the well-established stepped Ru(0001) surface (−0.43 V). The origin of the high activity toward NRR is attributed to the synergistic effect of the single atom (SA) and the M atoms in the substrate. More impressively, a composition descriptor is further proposed on the basis of the inherent characteristics of the catalysts [number of valence electrons of SA and electronegativity of the SA and Zr(Hf) atoms], which helps to better predict the catalytic performance. Our work not only contributes to the development of highly efficient NRR electrocatalysts but also extend the application of h-MBenes in electrocatalysis.

Phosphorus (P) leaching from excessive P application is the primary pathway of P losses in agricultural soils. Different P fertilizer practices have mixed effects on P leaching. We conducted a meta-analysis of the relevant literature regarding the response of crop yields, soil-available P (AP), and total P (TP) leaching to reduced P input (RP) and an inorganic-organic combination fertilizer (NPKM) for different agricultural land-use types. Compared to conventional P application (CP), RP (10~90% reduction) did not reduce crop yields in vegetable fields (experiments were 1~4 years) but significantly reduced cereal yields by 4.57%. Compared to chemical fertilizer (NPK), NPKM significantly increased cereal yields by 12.73%. Compared to CP, RP significantly reduced AP at 0~60 cm in vegetable and cereal fields. The greatest reduction occurred at 20~40 cm in vegetable fields (40.29%) and 0~20 cm in cereal fields (34.45%). Compared to NPK, NPKM significantly increased the AP at 0~60 cm in vegetable fields, with the greatest increase (52.44%) at 20~40 cm. The AP at 0~40 cm in cereal fields significantly increased under the NPKM treatment, with the greatest increase at 0~20 cm (76.72%). Compared to CP, RP significantly decreased TP leaching by 16.02% and 31.50% in vegetable and cereal fields, respectively. Compared to NPK, NPKM significantly increased TP leaching in vegetable fields (30.43%); no significant difference in leaching occurred in cereal fields. P leaching, in response to RP, was influenced by the P amounts applied (34.49%); soil organic matter (14.49%); and TP (12.12%). P leaching in response to NPKM was influenced by multiple factors: rainfall (16.05%); soil organic matter (12.37%); soil bulk density (12.07%); TP (11.65%); pH (11.41%). NPKM was more beneficial for improving yields in cereal fields with low soil fertility and lower P-leaching risks.

Melatonin application has obvious improving effects on alleviating the drought-induced inhibition of plant growth. However, the root phenotypic dynamics in wheat treated with melatonin remain unknown. This study was conducted using RhizoPot, a novel and improvised in situ root observation device, with three treatments, including normal water condition (CK), drought condition (Ds, relative water content 45–50%), and 100 µM melatonin treatment under drought condition (MT). Results showed that MT application effectively improves root morphological indicators, including root (specific root) length, surface area, and volume; root length density; and the average root diameter of wheat plants. Also, the inhibitory effect of drought on shoot morphology, including plant height, dry weight, net photosynthesis, and stomatal aperture of leaves, were improved significantly through MT under drought condition. Life span and percent survival of fine root, lateral root, and root hair at different segments were also effectively improved under MT treatment. Compared with those shown under CK and Ds, the melatonin contents in leaves and roots were increased, and the expression levels of melatonin-synthesis-related genes (TaCOMT and TaTDC) were upregulated significantly under MT treatment. The findings of this study may clarify the drought resistance mechanism of wheat treated with melatonin under drought stress.

Abstract Layered IV-V-VI semiconductors have immense potential for thermoelectric (TE) applications due to their intrinsically ultralow lattice thermal conductivity. However, it is extremely difficult to assess their TE performance via experimental trial-and-error methods. Here, we present a machine-learning-based approach to accelerate the discovery of promising thermoelectric candidates in this chalcogenide family. Based on a dataset generated from high-throughput ab initio calculations, we develop two highly accurate-and-efficient neural network models to predict the maximum ZT (ZT max) and corresponding doping type, respectively. The top candidate, n-type Pb2Sb2S5, is successfully identified, with the ZT max over 1.0 at 650 K, owing to its ultralow thermal conductivity and decent power factor. Besides, we find that n-type Te-based compounds exhibit a combination of high Seebeck coefficient and electrical conductivity, thereby leading to better TE performance under electron doping than hole doping. Whereas p-type TE performance of Se-based semiconductors is superior to n-type, resulting from large Seebeck coefficient induced by high density-of-states near valence band edges.

The measurement of crop nutrition is considerably significant in agricultural practices, especially in the application of mechanized variable rate fertilization. Feature extraction and model building are two important links in crop nutrition measurement by digital image. In this paper, a feature set of fusion multi-colour space in field prototype is extracted and an evaluation approach using stepwise-based ridge regression (SBRR) that uses correlation-based evaluation method is employed. First the image features of three known colour spaces are extracted, meanwhile a new colour space named rgb is constructed according to the characteristics that RGB colour space easily affected by light. Then the SBRR with nested cross validation is used to find the best evaluation model. By performance evaluation, the optimal SBRR model is obtained (R2 = 0.718 RMSE = 5.111). Additionally, compared with two other nutritional evaluation approach named back-propagation artificial neural network (BP-ANN) and k-nearest neighbors (KNN), SBRR achieves better performance in both R2 and RMSE. Furthermore the proposed model’s reliability is verified using the image dataset taken from the same wheat field in the next year. The R2 and RMSE values are 0.794 and 4.304, respectively. The comparisons and verification show that our proposed SBRR approach can achieve better experimental results and can be considered a reliable and low-cost alternative for estimating the chlorophyll content of wheat leaves in field.

MXene-supported single-atom catalysts (SACs) for water splitting has attracted extensive attention. However, the easy aggregation of individual metal atoms used as catalytic active centers usually leads to the relatively low loading of synthetic SACs, which limits the development and application of SACs. Herein, by performing first-principles calculations for Pt and 3d transition metal single atoms immobilized on a two-dimensional (2D) Mo2TiC2O2 MXene surface, we systematically studied the performance of heterogeneous dual-atom catalysts (h-DACs) in hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Significantly, h-DACs exhibit higher metal atom loading and more flexible active sites compared to SACs. Benefiting from these features, we found that Pt/Cu@Mo2TiC2O2 heterogeneous DACs exhibits excellent HER activity with ultra-low overpotential |ΔGH∗| (0.04 eV), lower than the corresponding Pt@Mo2TiC2O2 (0.14 eV) and Cu@Mo2TiC2O2 (0.33 eV) SACs, and even lower than that of Pt (0.09 eV). Meanwhile, Pt/Ni@Mo2TiC2O2 exhibits superior OER activity with ultra-low overpotential ηOER (0.38 V), lower than that of Pt@Mo2TiC2O2 (1.11 V) and Ni@Mo2TiC2O2 (0.57 V) SACs, and even lower than that of RuO2 (0.42 V) and IrO2 (0.56 V). Our finding paves the way for the rational design of h-DACs for HER and OER with excellent activity, which provides guidance for other catalytic reactions.

Soil nutrient testing is an effective way to uncover soil nutrient status. However, the conventional testing method (CT method) and Mehlich 3 method (M3 method) demand long-time consumption, tedious testing steps, high testing cost, dangerous chemicals contained in extractant, etc. Therefore, it is important to develop a new rapid test method or improve the existing rapid test method of soil available nutrients. In this study, an improved Mehlich3 method (IM3 method) with the new combined extractant were developed and evaluated on the testing feasibility, precision, efficiency, and cost. The results showed that: (1) IM3 method avoided the usage of two hazardous chemicals, i.e., ammonium nitrate and nitric acid, which were difficult in purchase and storage but contained in the combined extractant of M3 method. (2) The correlation coefficients of available P, K, Fe, Mn, Cu and Zn in calcareous soil between M3 and CT, and between IM3 and CT methods all reached highly significant level. The correlation coefficient of available Zn between IM3 and CT method was significantly higher than that between M3 and CT method, and those of the other elements had not obviously changed. (3) The variation coefficients of available P, K, Fe and Cu determined by M3 and IM3 methods were all lower than those determined by CT method. The variation coefficients of available Mn and Zn determined by IM3 were 3.67% and 6.43%, which were slightly higher than those determined by CT method with 2.72% and 5.29%, but were lower than those determined by M3 method. (4) Under the premise of ensuring testing precision, IM3 method took only 6.3 min/piece for determining six elements, reducing testing time by 70.7% and 3.08% compared with CT (21.5 min/piece) and M3 (6.5 min/piece) methods, respectively. The testing cost of IM3 method was reduced by 26% and 61.2% compared with M3 and CT methods, respectively. In conclusion, IM3 method is an ideal rapid measurement method for the simultaneous determination of available soil nutrients in calcareous soil.

Potassium (K) is the second most important plant nutritional element and is used for numerous physiological processes. We established an eight-year experiment comparing the effects of five K fertilization treatments (0, 48, 84, 120 and 156 kg K ha−1) on crop yield, K use efficiency and soil apparent K balance under the maize–wheat rotation system in the North China Plain. The highest maize and wheat yields were achieved in the K120 treatment, increasing by up to 16.7% and 25.1%, respectively. The increase in grain yield and K agronomic efficiency (AEK) with K application was greater in wheat than in maize. The K recovery efficiency (REK) and K accumulative recovery efficiency (ARE) significantly decreased with the increase in K fertilization in the maize and wheat seasons. However, the soil apparent K balance and soil available K content increased; the former was deficiency (−24.3 kg ha−1 yr−1) in the K0 treatment, but the latter did not decrease significantly compared with that in the initial year of the experiment. The soil available K content increased by 10.9 mg kg−1 per 100 kg ha−1. In conclusion, the yield response to K fertilization was greater in wheat than in maize and alleviated soil K depletion, but the K fertilizer efficiency was lower. We believed that K fertilizer can be increased moderately in the wheat season and decreased in the maize season.

Negative pressure irrigation (NPI) is an important water management strategy that can improve crop yields and water use efficiency (WUE). However, because NPI is affected by vital factors, such as negative pressure values, soil properties, and fertilization dosages, there is a lack of systematic analyses of the application effects of NPI on various crops. Hence, this study collected the results of 44 published studies and established the validity of 142 crop yields, 121 WUEs, 138 crop qualities, and 138 crop nutrient statuses in a database for NPI systems. The meta-analysis method was used to analyze NPI in comparison to conventional irrigation (CI) conditions. The results showed that the NPI yields and WUEs significantly improved by 17% and 63% compared to those of CI, respectively. Meanwhile, the negative pressure values were −2~−5 kPa; the improvement effects on yields were the best; and the WUEs exhibited the highest performance with negative pressure values of −6~−10 kPa. NPI promoted crop quality and plant nutrient uptakes under the appropriate NPI conditions. The synergistic impacts for sandy loam, alkalescent soils, and leafy vegetables were greater than for clay loam, neutral soils, and fruit vegetables under NPI conditions. Simultaneously, it was shown that the soil available phosphorus content and application of P fertilizer have a greater impact on NPI and CI crop yields. Therefore, the meta-analysis demonstrated the impacts of NPI on crop yields, WUEs, quality, and nutrient absorption, and quantified the effects of NPI on crop growth under various conditions, which provides an important water-saving technology for greenhouse production.

As the world faces great challenges from climate change, carbon reduction has become China’s basic national policy. However, as the main model for carbon reduction in China, the non-cooperative carbon reduction model (NCCRM) is a simple regulation mode, which is not beneficial for optimization of electricity generation capacity structure and cannot effectively motivate carbon reduction at the provincial level. Therefore, we propose an interprovincial cooperative carbon reduction model (CCRM) from the perspective of electricity generation, which provides a mechanism integrating two fundamental principles of efficiency and fairness. The CCRM consists of two parts: (1) an optimal model of carbon reduction with the object of minimizing the carbon emission of the cooperation union to determine the optimal annual electricity generation for each participating province and (2) a model that distributes the economic benefits of the cooperation among the provinces in the cooperation based on the Shapley value method. We applied the CCRM to the case of an interprovincial union of Shanghai, Sichuan, Shanxi, and Gansu in China. The results, based on the data from 2014 to 2017, show that cooperation can significantly reduce the carbon emission of the union by 425.78 × 108 kg, 11.06%; meanwhile, Shanghai, Sichuan, Shanxi, and Gansu can, respectively, get 2.79 × 108, 11.11 × 108, 4.07 × 108, and 3.19 × 108 CNY of extra benefits from carbon reduction. To test the impact of different parameter values on the results of the CCRM, a sensitivity analysis was conducted. Some policy recommendations are proposed to promote the implementation of the CCRM.

Heterocyclic nitrogen compounds containing two adjacent nitrogen atoms generally have a significant effect on soil nitrification inhibition, and 3,5-dimethylpyrazole (DMP) is a typical representative of this structure. However, the inhibitory effect and the regulatory mechanism of DMP on soil N transformation are unclear. In this study, a microcosm with different concentrations of DMP was carried out in brown soil to detect the dynamic changes of soil NH4+–N, NO3–N and related soil enzyme activities. Results showed that DMP inhibited soil nitrification effectively and decreased soil nitrate reductase activity, while increasing nitrite reductase and dehydrogenase activities. The inhibition effects were dose dependent, and DMP at the rate of 0.025 g kg−1 dry soil showed the strongest inhibitory effect on N transformation in brown soil. The soil dehydrogenase activity was increased with an increasing DMP application rate. The changes in the soil’s chemical and biological properties caused by DMP application provided a new idea for systematically explaining how DMP participated in the soil N transformation process. This study further implied that DMP would play positive roles in alleviating environmental pressure by delaying nitrate-N formation and decreasing the activity of nitrate reductase.

Using atomistic simulations, we present a systematic investigation of the shear mechanisms of three {111} bimetal interfaces, focusing on the influence of the dislocation spacing and bonding scheme across the interface. The evolution of interface sliding process reveals that all the initial shearings are nucleated at the regions of dislocations and their nodes. The interface with small lattice misfit could accommodate the shear strain via the dislocation loops gliding into neighboring massive coherent regions, exhibiting a comparatively low shear strength. However, at the interface with dense dislocation network, the adjacent gliding dislocation loops interact with each other and prohibit further interface sliding. Considering the γ surfaces of three {111} interfaces, it is found that the miscellaneous bonding scheme across the interface can vary the preferred sliding directions and prevent the necessary transformation of the incipient sliding directions, which eventually increase the shear resistance. The shear strength of the Ni/Al {111} interface is increased by six times after alloying, verifying the cooperative strengthening effect contributed by the dense interfacial dislocations and miscellaneous bonding scheme. Keywords: MD simulation, Interface, Shear strength, Dislocation spacing, Metallic bonding scheme

Density functional theory with Hubbard U correction is employed to study the polaron in rutile under external electric fields. It is found that electric-field-induced displacements of the ions enhance the sampling of the polaron configurations, which is helpful to find the most stable structure among local minima. More importantly, we demonstrate that with increasing electric field, the polaron may vanish, i.e. the excess electron can dissociate from the bounded Ti3+, and this process is reversible with the opposite electric field. The present findings shed light on more complex mechanisms for the polaron-related conductivity in oxides and corresponding devices. Impact statement The first ab initio demonstration of the polaron dynamics under electric fields provides a complete picture of the polaron in rutile, deepening the understanding of the conductivity in the oxides.

Phase-change memory (PCM) utilizes the fast reversible phase transition between crystalline and amorphous chalcogenide phase-change materials to achieve the data storage. The rather large density difference between crystalline and amorphous phases will induce device failure with repeated switching. Further, the melting-quenching process induced amorphous-crystalline phase-change needs high energy consumption. In this work, reversible resistance switching is observed in crystalline Ge1Sb4Te7 ribbons driven by voltage polarity, without amorphous-crystalline phase-change. Consequently, the large density variation and the high energy consumption are avoided, which overcomes those two restrictions of PCM. Moreover, on the basis of ab initio calculations, the underlying mechanism is further analyzed and it is concluded that this switching is induced by the reversible swapping of antimony between its lattice site and the center of the Te-Te van der Waals bilayers.

The vibrational density of states (VDOS) of solids in the low-energy regime controls the thermal and transport properties of materials, such as heat capacity, heat conduction, free energy and entropy. In α-Cristobalite, the low-frequency part of vibration density of states (VDOS) has many common features with the Boson peak in silica glass of matched densities. Recent theoretical work reported that anharmonic phonon–phonon interactions were critical for the low-frequency part of VDOS in α-Cristobalite. Therefore, it is urgent to identify the role of different anharmonic interactions from first principles. In this paper, we focus on the main peak of the low-frequency part of VDOS in α-Cristobalite. Calculated by our own developed codes and first principles, we find that the quartic anharmonic interaction can increase the frequency of the peak, while the cubic anharmonic can reduce the frequency and change the shape of the peak. Meanwhile, the anharmonic interactions are critical for the temperature effect. Therefore, we calculated the temperature-dependent property of the peak. We find that the frequency of the peak is directly proportional to the temperature. The atomic displacement patterns of different temperatures also confirm the above conclusion. All our calculations converged well. Moreover, our basic results agree well with other published results. Finally, we highlight that our codes offer a general and reliable way to calculate the VDOS with temperature.