Optimal Structure Research Articles

An improved meta-heuristic method for optimal optimization of electric parking lots in distribution network

In this study, a stochastic multi-objective structure for optimization of the intelligent electric parking lots (EPLs) is implemented in the distribution network for minimizing the power losses annual costs, power purchased from the main grid, unsupplied energy of subscribers, cost of vehicles to the grid as well as minimizing the network voltage deviations considering battery degradation cost (BDC) and network load uncertainty (NLUn). In this research, the unscented transformation method (UTM) is used for NLUn modeling and this method is easily applicable and has a low computational cost. An improved meta-heuristic algorithm named improved fire hawks optimization (IFHO) is utilized for decision variables finding defined as the site and size of the EPLs in the distribution network. The conventional fire hawks optimization (FHO) algorithm is inspired by the fire hawks foraging behavior and in this research, the Taylor-based neighborhood technique (TBNT) is used to reduce the dependency and the possibility of becoming trapped in local optimal. To evaluate the proposed methodology, the simulations are implemented in three scenarios (1) EPLs optimization without BDC and NLUn based-UTM, (2) EPLs optimization with BDC and without NLUn, and (3) EPLs optimization with BDC and NLUn. The results of the third scenario considering BDC and NLUn showed that the EPLs optimization integrated with a multi-objective framework by finding the EPL's optimal size and capacity in the network via the IFHO has reduced the annual losses, voltage deviations, ENS cost, and substation cost by 21.06%, 12.15%, 70.82%, and 39.10%, respectively compared to the base distribution network. Additionally, the results demonstrated that incorporating the BDC and NLUn, the annual losses, voltage oscillations, ENS cost, grid cost, and EPLs have increased in comparison with the EPLs optimization without BDC and NLUn based-UTM. In addition, the TBNT based-IFHO superiority has been confirmed in different scenarios by achieving better values of the objectives and also obtaining the convergence process with lower convergence tolerance and higher convergence accuracy.

A Study on the Impact of China’s Prefabricated Building Policy on the Carbon Reduction Benefits of China’s Construction Industry Based on a Difference-in-Differences Method

The construction industry is a significant contributor to carbon emissions in China. To effectively meet the “dual carbon” targets, several provincial regions within the country started to implement policies promoting prefabricated buildings. This study examines data from 18 provinces in China over the period from 2012 to 2021, treating the introduction of prefabricated building policies as a quasi-natural experiment. Utilizing the difference-in-differences methodology, this research assesses the impact of these policies on the carbon emission performance of China’s construction sector and evaluates the robustness of the findings. The results indicate that the prefabricated building policies positively influenced the carbon emission efficiency of the construction industry. Specifically, these policies enhance carbon emission efficiency by increasing labor productivity, optimizing the allocation of mechanical resources, and improving the utilization rate of building materials. Additionally, the effectiveness of these policies is positively correlated with the level of regional technological innovation, environmental protection efforts, and the advancement of energy structure optimization. The study concludes with several policy recommendations aimed at further enhancing the effectiveness of prefabricated building policies.

Numerical investigation of the influence of heat-generating components on the heat dissipation in a tower server

Many of today’s servers rely on high-power electronic components. During continuous operation, elevated temperatures can lead to sluggish performance and system instability. Therefore, servers urgently require safe and reliable heat dissipation systems. In this work, we focus on a highly scalable tower server as our research subject, exploring its maximum configuration within the designated range. We aim to enhance the server’s thermal performance through a parametric investigation of factors such as the server air outlet, the FAR in air outlet, and the layout of GPUs. The results demonstrate that narrowing the air outlet can effectively reduce the temperature of GPU-2 by 2.83 °C. Further analysis reveals that an optimal FAR of 0.74 for the air outlet leads to a temperature decrease of 1.67 °C for GPU-2 compared to a FAR of 0.24. Moreover, adjusting the position of GPU-2, specifically employing the VLO-L71.16-1 structure with the air outlet positioned on the GPU-1 side, yields optimal heat dissipation performance, resulting in a remarkable temperature decrease of 16.63 °C for GPU-2. Additionally, it was observed that GPU-2 in the base case approaches its limiting temperature. By optimizing the structure to VLO-L71.16-1, the study managed to reduce fan airflow while maintaining GPU-2 within safe operating temperatures. Specifically, the optimal structure achieves approximately 35 % airflow savings when GPU-2 reaches its limiting temperature. This research provides valuable insights for the exploration and design of novel server cooling systems.

Stretchable Metamaterials with Tunable Infrared Emissivity for Dynamic Thermal Management.

Manipulation of infrared emissivity, which is closely related to surface structure and optical parameters of materials, is a crucial approach for realizing dynamic thermal management. In this study, we design a metamaterial consisting of an array of aluminum disks embedded on a surface of a stretchable elastomeric substrate. Mechanical stretching-induced deformation allows dynamic modification of the surface structure and equivalent optical parameters, thus enabling dynamic control of the emissivity. By utilizing the elastomer polydimethylsiloxane (PDMS) as the substrate, the microstructure interdisk gap can be altered by stretching the PDMS. Through theoretical calculations, the plausibility of this approach is explained by the excitation of plasmon resonance and the variation in the exposed area of highly absorbent PDMS, and the optimal structures for tuning the infrared emissivity are revealed to be 6 μm in diameter and 100 nm in height. Based on this design, we prepare samples with periods of 7 and 7.9 μm and experimentally demonstrate that a change in the period can cause a change in the emissivity and thus tunability in thermal control performance. The temperature difference between the two samples reaches 44.1 °C at a heating power of 0.28 W/cm2 for both samples. Furthermore, we construct a stretching platform that enables in situ mechanical stretching to realize dynamic changes in emissivity. The integral infrared emissivity of the sample increases from 0.32 to 0.5 at a biaxial tensile strain of 13%, achieving a 56% modulation rate of the integral infrared emissivity. The material is expected to enable dynamic thermal management.

A Benchmark Study of DFT-Computed p-Block Element Lewis Pair Formation Enthalpies against Experimental Calorimetric Data.

The quantification of Lewis acidity is of fundamental and applied importance in chemistry. While the computed fluoride ion affinity (FIA) is the most widely accepted thermodynamic metric, only sparse experimental values exist. Accordingly, a benchmark of methods for computing Lewis pair formation enthalpies, also with a broader set of Lewis bases against experimental data, is missing. Herein, we evaluate different density functionals against a set of 112 experimentally determined Lewis acid/base binding enthalpies and gauge influences such as solvation correction in structure optimization. From that, we can recommend r2SCAN-3c for robust quantification of this omnipresent interaction.

The new bridge “Lahnsteg Nauheim”, Wetzlar: slender, elegant, parametrically designed

AbstractThis paper outlines the planning of a bridge in central Germany. Scheduled for construction in mid‐2024, this new bridge is a replacement for a century‐old pedestrian bridge crossing the Lahn river.The proposed bridge will be an airtight‐welded arch bridge, employing steel cross‐sections in both the arch and tension member. Designed as a single‐span, the arches extend 48.0m over the Lahn. The two arches have a flat rise of 4.65m, supporting the roadway through 9 inclined flat steel hangers.This paper delves into the structural engineering aspects, exploring challenges inherent in the design process. An examination of the parametric design process, facilitated through 3‐D modeling in Rhino® and Grasshopper®, will be presented, along with insights into their interface with the finite element modeling software, RFEM®. This process enables an engineering approach to form‐finding and structure optimisation through iterative design checks for various elements and stages of the structural analysis.

Improving the durability and investing failure behavior of TBCs under thermal cycling-CMAS test by Yb2O3 and Y2O3 co-stabilized ZrO2 materials and different processes

Under extremely complex conditions, extending the lifetime of thermal barrier coatings (TBCs) is a challenge. In the present study, optimization of the coating structure and selection of coating materials are beneficial for improving the lifetime of TBCs under thermal cycling-CMAS (calcium-magnesium-alumina-silicate) test. It is efficient to obtain different layer thicknesses of multi-layer coating, including the micro-nano dual-scale layer, the dense YbYSZ layer (4.0 mol % Yb2O3 and 0.5 mol% Y2O3 co-stabilized ZrO2), the porous YbYSZ layer and the laser 3D texturing layer, using the computational model under thermal load. Based on the corresponding coating structure and YbYSZ material, bond strength and thermal cycling-CMAS lifetime are evaluated, and compared with those of YSZ (4.5 mol % Y2O3 stabilized ZrO2) coating. The results reveal that TBCs with porous embedded particle cluster (PEPC) structure is lower than that of YSZ coating. In addition, the original defects in multi-layer coating with grid texture reduce the bond strength. The lifetime of multi-layer coatings with a punctate texture are significantly improved in the thermal cycling-CMAS test, and their failure behavior includes fragmented and bulk-like exfoliation. This study emphasizes that combination of materials modification and structure optimization are a promising strategy to extend lifetime of TBCs.

Structure optimization and contact law study for transmission linkage of manipulator grasping fragile parts

According to the grasping requirements for fragile workpieces with cylindrical inner walls, a manipulator with internal bracing has been designed. The manipulator utilizes a constant-speed push cylinder to drive the linkage mechanism and accomplish the related works. Considering the fragile nature of the workpieces, reducing the impact velocity between the manipulator finger and the workpiece is a primary objective in the mechanism design. To achieve this, an optimization design is carried out, which maintains the overall average speed of the manipulator, while reducing the average speed only during the contact between the finger and the workpiece. The goal of optimization is to minimize the impact velocity at the contact point, using the linkage structure parameters as variables. The genetic algorithm (GA) is employed for the optimization process. The results show that optimization reduces the impact velocity at the contact point by 44.80%. To gain further insight into the influence of the process, a finite element model of a finger grasping a fragile object was created using joint modeling with the SolidWorks, Hyper Mesh, and LS-DYNA software. Simulations reveal that, after optimization, the maximum internal stress of three workpieces with thicknesses of 2.00 mm, 1.00 mm, and 0.50 mm was reduced by 47.42%, 41.53%, and 44.20%, respectively. To study the general law of the mechanical hand grasping fragile workpieces, the relationship between the cylinder driving speed and the impact speed is established. Based on the simulation results of maximum contact impact velocity, workpiece wall thickness, and maximum contact force, a prediction model of workpiece internal force is established using the Kriging prediction model theory. Additionally, the feasible range of grasping parameters under different wall thickness conditions is determined and discussed. The reliability of the designed structure is experimentally verified, providing valuable insights for ensuring the lifting work reliability of manipulators handling fragile workpieces.

Design and implementation of a high-performance miniaturized multi-layer magnetic shielding spherical shell with minimal pores based on target magnetic field

Achieving the spin-exchange relaxation-free (SERF) state in atomic comagnetometers (ACMs) necessitates a stable and weak magnetic environment. This paper presents the design of a miniaturized permalloy magnetic shielding spherical shell (MSSS) with minimal apertures, tailored to meet these requirements. By employing a combination of analytical solutions and finite element analysis (FEA), we achieved superior magnetic shielding while maintaining a compact form factor. The analytical solution for the shielding factor indicated that a four-layer permalloy sphere shell with optimized air gaps was necessary. A numerical analysis model of the MSSS was developed and validated using COMSOL software, confirming the suitability of the air gaps. The size, shape, and orientation of the openings in the perforated sphere shell were meticulously designed and optimized to minimize residual magnetism. The optimal structure was fabricated, resulting in triaxial shielding factors of 47619, 52631, and 21739, meeting the anticipated requirements. A comparison of simulation results with experimental tests demonstrated the efficacy of the design methodology. This study has significant implications for ultra-sensitive magnetic field detection devices requiring weak magnetic field environments, such as atomic gyroscopes, magnetometers, atomic interferometers, and atomic clocks.

Enhancing yield of modern maize (ZeamaysL.) hybrids through the optimization of population photosynthetic capacity and light-nitrogen efficiency under high density

Due to the breeding of dense-resistant and lodging-resistant varieties in maize production, dense planting has become an effective means for achieving high and stable yields, while excellent hybrids are a prerequisite for reasonable dense planting in maize production. Nonetheless, the photosynthetic mechanism of improving plant density tolerance of maize hybrids released at different era in China remains unclear. This study aims to investigate the 40-year breeding effort for enhanced photosynthetic trait at different densities, and elucidate the physiological and ecological mechanisms of improving the density tolerance of maize hybrids. We conducted a 3-year study in 2019, 2020, and 2021. From 1970 to 2009, a comparison was made between the eight major hybrids promoted in China, divided into four decades, under three planting densities (45,000 (D1), 67,500 (D2), and 90,000 (D3) plants ha−1). At high density, modern hybrids had more rational canopy structure and leaf photosynthetic performance compared with old hybrids and specific leaf nitrogen has decreased slightly. Among all treatments, the modern hybrids (2000s) were able to maintain higher net photosynthetic rate and photosynthetic nitrogen utilization efficiency (PNUE) at D3 density, and therefore possessed the highest grain yield (GY), which was 118.47% higher than that of the old hybrids (1970s). Leaf area duration after anthesis, total chlorophyll content, photosynthesis key enzyme activities, and maximum efficiency of PSII photochemistry were all positively correlated with GY, with PNUE was more significantly correlated with GY indeed and is a key indicator for maize hybrids optimization. Based on these results, breeders should continue to conduct hybrid selections under adverse and high-density conditions, focusing on the optimization of population structure and the continuous improvement of photosynthetic capacity, searching for the optimal leaf nitrogen-content status, so as to select and breed high-yielding and density-tolerance hybrids, which resulted in a sustained increase in maize GY.

Regulating crystal phase of TiO2 to enhance catalytic activity of Ni/TiO2 for solar-driven dry reforming of methane

Ni/TiO2 catalyst is widely employed for photo-driven DRM reaction while the influence of crystal structure of TiO2 remains unclear. In this work, the rutile/anatase ratio in supports was successfully controlled by varying the calcination temperature of anatase-TiO2. Structural characterizations revealed that a distinct TiOx coating on the Ni nanoparticles (NPs) was evident for Ni/TiO2-700 catalyst due to strong metal-support interaction. It is observed that the TiOx overlayer gradually disappeared as the ratio of rutile/anatase increased, thereby enhancing the exposure of Ni active sites. The exposed Ni sites enhanced visible light absorption and boosted the dissociation capability of CH4, which led to the much elevated catalytic activity for Ni/ TiO2-950 in which rutile dominated. Therefore, the catalytic activity of solar-driven DRM reaction was significantly influenced by the rutile/anatase ratio. Ni/TiO2-950, characterized by a predominant rutile phase, exhibited the highest DRM reactivity, with remarkable H2 and CO production rates reaching as high as 87.4 and 220.2 mmol/(g·h), respectively. These rates were approximately 257 and 130 times higher, respectively, compared to those obtained on Ni/TiO2-700 with anatase. This study suggests that the optimization of crystal structure of TiO2 support can effectively enhance the performance of photothermal DRM reaction.

The Relationship among Environmental, Social and Governance (ESG) Factors

As the global economy slows down, enterprise development enters a new stage. In addition to scale expansion, more emphasis is placed on external factors that focus on sustainable development, such as environmental, social and governance (ESG). ESG represents the concept of green economy, emphasizing that enterprises should not develop at the cost of the environment, but should take the initiative to fulfill social responsibilities and protect the rights and interests of stakeholders. In this paper, the comprehensive impact of ESG dimensions on corporate governance is deeply studied. Through the systematic review and analysis of several domestic and international literatures, this paper reveals the key role of strong governance structures in promoting the development and implementation of corporate environmental policies, as well as their central position in enhancing social responsibility and corporate social image. Research shows that good governance can not only improve a company's environmental performance, but also further enhance its financial performance and market competitiveness by improving social interaction and meeting stakeholder needs. This paper emphasizes that the optimization of governance structure is an important strategy for enterprises to achieve sustainable development and increase shareholder

Study on Optimization of Land Use Structure in Fujian Province Based on Low-Carbon Perspective

Carbon peaking and carbon neutrality strategies are pivotal in addressing climate change. Optimizing land use structure is a fundamental approach to achieving low-carbon development within a given territory. This study focuses on Fujian Province as the research subject, predicting carbon emissions for the next decade by analyzing the correlation between land use types and carbon emissions using the gray model. This analysis is based on land use panel data spanning from 2007 to 2021. The study applies the FLUS-Markov model to simulate Fujian’s land use in 2030. A multi-objective optimization model is developed from a low-carbon perspective, integrating carbon emissions, economic, and ecological factors. The study explores land use under three scenarios: natural development scenario (NS), low carbon scenario (LCS), and comprehensive scenario (CS). Findings highlight the relationship between land use-related carbon emissions, urbanization, and relevant policies in Fujian. The FLUS-Markov simulations suggest that under the NS scenario, carbon emissions in 2030 will reach 77.829 million tons, an increase of 11.013 million tons from 2020. In contrast, the LCS demonstrates that optimizing land use structures can effectively balance carbon reduction, economic growth, and ecological preservation. Under the CS, 2030 emissions could be reduced by 7.2854 million tons while maintaining economic and ecological benefits. Despite variations in construction land expansion across these scenarios, all follow a “one belt, one core” development pattern. The study concludes with policy recommendations, including industrial layout optimization and clean energy promotion. These findings support the alignment of land use optimization with Fujian’s future development needs, offering guidance for land-use planning and policies focused on low-carbon objectives.

WITHDRAWN: The impact of renewable energy development on regional carbon emission reduction: Based on the spatio-temporal analysis of 30 provinces in China

The development of renewable energy has become an important means for the world to cope with climate change, ensure energy security and protect the ecological environment. Using the panel data of 30 provinces in China from 2013 to 2021, this paper used the mediating effect model and the spatial Durbin model (SDM) to explore the mechanism and spatial effects of renewable energy development on carbon emission reduction. The results show that: (1) The results of mechanism analysis show that renewable energy development reduces carbon intensity by improving energy structure, promoting industrial structure optimization and industrial structure upgrading. (2) Renewable energy development can not only reduce the local carbon intensity, but also have a positive spillover effect on the carbon intensity of neighboring regions. (3) Further analysis shows that renewable energy development has a dynamic effect on carbon emissions. The heterogeneity analysis shows that compared with the Yellow River basin, renewable energy development significantly influences carbon emission reduction in the Yangtze River Economic Belt region. Energy-rich areas fall into the "resource curse", which makes renewable energy development’s carbon emission reduction effect not significant. This paper has certain reference significance for promoting reasonable decomposition between regions and formulating renewable energy development policies.

Performance enhancement of SAW based hydrogen sensor employing Pd/Ni alloy thin film

Abstract This study focuses on determining the optimized design parameters of palladium/nickel (Pd/Ni) thin film coated surface acoustic wave (SAW) hydrogen (H2) sensors with high sensitivity and fast response by modulating the ratio and thickness of Pd/Ni thin film. The Pd/Ni thin films deposited on the wave propagation path of delay-line patterned SAW sensors had Ni content ranging from 0 to 30 at% and thickness ranging from 20 to 400 nm. A phase discrimination circuit was used to collect the signal of SAW H2 sensor. The experimental results indicated that the response sensitivity of the sensor decreased with the increase of Ni content, while the response time gradually accelerated. Besides, the stability of the sensor deteriorated with increasing thickness, and there existed a non-linear relationship between sensitivity and thickness, and the response time slowed down as the thickness increased. To analyze the SAW sensing mechanism, a theoretical simulation model of the Pd/Ni thin film coated SAW H2 sensor was established using perturbation theory, which was well-validated by experimental results. Considering the requirements of fast response, high sensitivity, and stability of the H2 sensor, the optimal thin film structure parameters were determined as Pd9Ni1 thin film with the thickness of 40 nm.

Activation and Zr precursor influence on UiO-66-NH2 composites for efficient cationic and anionic dye removal

This study investigates the synthesis of UiO-66-NH2@HTC composites, focusing on the control of surface charge, textural properties, and crystallinity. Surface charge modification was achieved through activation processes to enhance affinity for specific pollutants. By utilizing ZrCl4 and ZrOCl2⋅8H2O precursors, the textural properties were optimized, leading to higher mesopore content and improved crystallinity with the ZrOCl2⋅8H2O precursor. The UiO-66-NH2(ZrCl4)@HTC composite exhibited a crystallinity of 51.7 %, with 40 % mesopores and 57 % micropores, while the UiO-66-NH2(ZrOCl2)@HTC composite showed a crystallinity of 60 %, consisting of 60 % mesopores and 37 % micropores. Adsorption followed the Langmuir isotherm model, with maximum adsorption capacities of 263.1 mg/g for methylene blue (MB) and 277.77 mg/g for Congo red (CR), driven by hydrogen bonding and electrostatic interactions. The activated UiO-66-NH2@HTC composites demonstrated remarkable reusability. These findings emphasize the significant role of surface charge modification, pore structure optimization, and crystallinity enhancement in developing high-performance adsorbents.

Y9, a Gboxin analog, displays anti-tumor effect in non-small cell lung cancer by inducing lysosomal dysfunction and apoptosis

Non-small cell lung cancer (NSCLC) ranks among the most prevalent malignancies globally. Gboxin, a novel inhibitor of mitochondrial complex V that exerts unique anti-tumor effects via oxidative phosphorylation inhibition, but shows no efficacy against NSCLC in vivo. Through chemical structure optimization, we designed and synthesized Gboxin analog Y9, which demonstrates significantly enhanced potency over its predecessor. Specifically, Y9 inhibited NSCLC significantly more strongly than Gboxin and possessed the ability to inhibit cell cycle progression and induce oxidative stress similar to Gboxin. Further investigation revealed that unlike Gboxin, Y9 selectively acidifies lysosomes and induces lysosomal dysfunction. This leads to hyperactive autophagy with impaired substrate clearance, and ultimately resulting in apoptosis. Animal studies confirmed the efficacy of Y9 in suppressing tumor growth in a xenograft mouse model. Collectively, Y9 is a distinctive Gboxin analog that outperforms its prototype by inducing lysosomal dysfunction and apoptosis, and has the potential to be developed as a novel anti-NSCLC lead compound.

Structural, magnetic, optical, and electronic properties of vanadium-doped barium hexaferrite nanoparticles: Experimental and DFT approaches

Vanadium-doped barium hexaferrite with a nanostructure is a highly valuable material in various technological fields, such as electronics, permanent magnets, and sensors. The Ba1-xFe12-xVxO19 (x = 0, 0.02, 0.04, 0.06, 0.08, and 0.1) nanoparticles derived from the aqueous solutions containing Fe:Ba molar ratio of 10:1 through the sol-gel auto-combustion method. Computational study was also performed using the first-principles density functional theory (DFT) approach. Crystal structure optimization, band structure, and density of states (DOS) calculations were conducted by CASTEP code. The variation of the structural, magnetic, optical, morphological, and electronic properties of V5+-doped barium hexaferrite was investigated. The XRD analysis combined with the Rietveld refinement showed the hexagonal structure of M-type barium ferrite (BaM), confirmed by the FT-IR analysis. The morphology of BaM nanoparticles was studied by the FE-SEM and TEM micrographs. In addition, magnetic and optical properties were analyzed through VSM and UV–Vis analysis. Crystallite size was found to be highly effective in tuning the coercivity and optical band gap of barium hexaferrites, which varied, respectively, from 3.24 to 4.83 kOe, and 2.69–3.69 eV. Magnetic results showed that several variables like cations distribution, lattice strain, and hematite secondary phase affected the nanoparticles’ magnetization. The DFT simulation results showed a sharp reduction of electronic band gap energy whether V takes the position of Ba or Fe (from 1.10 eV in undoped to 0.64 and 0.14 eV in doped structures). The projected density of states (PDOS) calculations demonstrated that the d orbitals of V and Ba mainly contribute to the valence band maximum (VBM) and conduction band minimum (CBM), respectively.

Megacity pathways in China under the dual carbon goal: The case of Shanghai

The pathways to achieving carbon neutrality at the city level are diverse due to varying energy supply and demand conditions. Shanghai faces obstacles such as limited land resources, high costs of renewable energy technologies, and instability of renewable energy. These challenges hinder the city’s efforts to achieve carbon peak and carbon neutrality (dual carbon). Therefore, Shanghai must identify and optimize its development path for renewable energy under the dual carbon goal. We employed the Low Emissions Analysis Platform-Shanghai (LEAP-SH) model to simulate the impact of policies, such as industrial upgrading, energy efficiency improvement, energy structure optimization, increased technical innovation on energy, and ecological restoration, on the carbon emission pathways from 2022 to 2060 using five different scenarios. Our results indicate that Shanghai has the potential to achieve carbon neutrality in 2059 by promoting carbon reduction, pollution control, and green expansion. Moreover, we determined that the manufacturing industry; power generation industry; and transportation, storage, and mail services are the three major sectors for emission reduction under the dual carbon goal. Furthermore, the capacity and output of coal-fired power plants will be gradually replaced by offshore wind power in the dual carbon pathway. Finally, this study proposes countermeasures and suggestions for Shanghai to attain the dual carbon goal and high-quality development.

GPTFF: A high-accuracy out-of-the-box universal AI force field for arbitrary inorganic materials

This study introduces a novel artificial intelligence (AI) force field, namely a graph-based pre-trained transformer force field (GPTFF), which can simulate arbitrary inorganic systems with good precision and generalizability. Harnessing a large trove of the data and the attention mechanism of transformer algorithms, the model can accurately predict energy, atomic force, and stress with mean absolute error (MAE) values of 32 meV/atom, 71 meV/Å, and 0.365 GPa, respectively. The dataset used to train the model includes 37.8 million single-point energies, 11.7 billion force pairs, and 340.2 million stresses. We also demonstrated that the GPTFF can be universally used to simulate various physical systems, such as crystal structure optimization, phase transition simulations, and mass transport. The model is publicly released with this paper, enabling anyone to use it immediately without needing to train it.