Hao Yu^1,*, Mengcheng Huang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011120

Abstract Understanding the competitive adsorption behavior of CO₂ and CH₄ in shale nanopores is crucial for enhancing the recovery of shale gas and sequestration of CO₂, which is determined by both the inherent characteristics of the molecules and external environmental factors such as pore size, temperature, and partial pressures of CO₂ and CH₄. While the competitive adsorption behavior of CO₂/CH₄ has been analyzed by previous studies, a comprehensive understanding from the perspective of molecular kinetic theory and the efficient calculation for competitive adsorption behavior considering various geological situations is still challenging, limited by the huge computation cost of classical… More >

Haitao Hei¹, Jian Wang¹, Yonggang Zheng¹, Hongfei Ye^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011298

Abstract Micro- and nano-scale collisions are widely involved in molecular movement, drug delivery, the actuation of micro-nano devices, etc. They often exhibit extraordinary behaviour relative to the common macroscopic collisions. A deep understanding on the scale reduction-induced novel collision phenomenon and the related mechanism is rather crucial. In this work, the comprehensive impact behaviour of metal projectiles on graphene is investigated on the basis of molecular dynamics simulations. It is found that besides the common penetration and rebound behaviours, the impacting metal projectile can also be captured by the ultrasoft two-dimensional materials, i.e., the adhesion behaviour.… More >

Chaofan Yao, Huanhuan Cao, Zhanyuan Xu^*, Lichun Bai^*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2107-2119, 2024, DOI:10.32604/cmes.2024.055743 - 31 October 2024

Abstract Shear deformation mechanisms of diamond-like carbon (DLC) are commonly unclear since its thickness of several micrometers limits the detailed analysis of its microstructural evolution and mechanical performance, which further influences the improvement of the friction and wear performance of DLC. This study aims to investigate this issue utilizing molecular dynamics simulation and machine learning (ML) techniques. It is indicated that the changes in the mechanical properties of DLC are mainly due to the expansion and reduction of sp³ networks, causing the stick-slip patterns in shear force. In addition, cluster analysis showed that the sp²-sp³ transitions arise… More >

Chentong Zhao¹, Jiming Zhou^1,2,*, Xujiang Chao^1,3, Su Wang¹, Lehua Qi^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2453-2469, 2024, DOI:10.32604/cmes.2024.052723 - 31 October 2024

Abstract The mechanical properties of graphene reinforced composites are often hampered by challenges related to the dispersion and aggregation of graphene within the matrix. This paper explores the mechanism of cooling rate, process temperature, and process pressure’s influence on the agglomeration behavior of graphene and the tensile response of composites from a computer simulation technology, namely molecular dynamics. Our findings reveal that the cooling rate exerts minimal influence on the tensile response of composites. Conversely, processing temperature significantly affects the degree of graphene aggregation, with higher temperatures leading to the formation of larger-sized graphene clusters. In More >

Jian Wang^1,*, Haitao Hei¹, Yonggang Zheng¹, Hongwu Zhang¹, Hongfei Ye¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010916

Abstract Icing is a ubiquitous phenomenon in nature and widely observed in the micro/nanoconfinement, e.g., two-dimensional ice growth on Au surface, nanoconfinement-induced phase change, nanodroplet freezing on surface, etc. These complicated and abstruse processes and behaviours demand deep understanding from the microscale level by the aid of molecular dynamics (MD) simulation [1]. However, it is still a great challenge to accurately describe the ice and liquid water simultaneously with the present water models [1,2]. In response to this, we propose a series-parallel machine learning (ML) approach consisting of classification back-propagation neural network (BPNN), parallel regression BPNNs… More >

Qiang Ma^1,2,3, Tuan Tran^2,*, Xiaodong Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.011051

Abstract Controlling dynamics of impacting droplets on meshes is significantly important, which attracted a lot of attention because of its great potential applications in liquid separation, self-cleaning, and water harvesting [1-3], yet the underlying physical mechanisms are not entirely revealed. Here, the impact dynamics of a nanodroplet on mesh surfaces with different wettability are studied through molecular dynamics (MD) simulations. Due to scale effects between the nano and macroscale, the impacting nanodroplets exhibit some unique dynamic characteristics [4-7]. On a superhydrophobic mesh surface, when varying the impact conditions of nanodroplets, different outcomes can occur: (i) at… More >

Ankitkumar Patel¹, Srivathsan Vasudevan^1,*, Satya Bulusu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3803-3818, 2024, DOI:10.32604/cmc.2024.052851 - 12 September 2024

Abstract Molecular Dynamics (MD) simulation for computing Interatomic Potential (IAP) is a very important High-Performance Computing (HPC) application. MD simulation on particles of experimental relevance takes huge computation time, despite using an expensive high-end server. Heterogeneous computing, a combination of the Field Programmable Gate Array (FPGA) and a computer, is proposed as a solution to compute MD simulation efficiently. In such heterogeneous computation, communication between FPGA and Computer is necessary. One such MD simulation, explained in the paper, is the (Artificial Neural Network) ANN-based IAP computation of gold (Au₁₄₇ & Au₃₀₉) nanoparticles. MD simulation calculates the forces… More >

Haowei Hu^1,2,*, Qi Wang¹, Xinnuo Chen¹, Qin Li³, Mu Du⁴, Dong Niu^5,*

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1245-1259, 2024, DOI:10.32604/fhmt.2024.054223 - 30 August 2024

Abstract To investigate the microscopic mechanism underlying the influence of surface-chemical gradient on heat and mass recovery, a molecular dynamics model including droplet condensation and transport process has been developed to examine heat and mass recovery performance. This work aimed at identify optimal conditions for enhancing heat and mass recovery through the combination of wettability gradient and nanopore transport. For comprehensive analysis, the structure in the simulation was categorized into three distinct groups: a homogeneous structure, a small wettability gradient, and a large wettability gradient. The homogeneous surface demonstrated low efficiency in heat and mass transfer, More >

Haowei Hu^1,2,*, Xinnuo Chen¹, Qi Wang¹, Qin Li³, Dong Niu⁴, Mu Du^5,*

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1071-1085, 2024, DOI:10.32604/fhmt.2024.054218 - 30 August 2024

Abstract The self-driven behavior of droplets on a functionalized surface, coupled with wetting gradient and wedge patterns, is systematically investigated using molecular dynamics (MD) simulations. The effects of key factors, including wedge angle, wettability, and wetting gradient, on the droplet self-driving effect is revealed from the nanoscale. Results indicate that the maximum velocity of droplets on hydrophobic wedge-shaped surfaces increases with the wedge angle, accompanied by a rapid attenuation of driving force; however, the average velocity decreases with the increased wedge angle. Conversely, droplet movement on hydrophilic wedge-shaped surfaces follows the opposite trend, particularly in terms… More >

Zhenzhen Liu, Hua Zhang^*, Zilong Wang, Yugang Zhao

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1087-1105, 2024, DOI:10.32604/fhmt.2024.053851 - 30 August 2024

Abstract The exploration of performance and prediction of environmentally friendly refrigerant physical properties represents a critical endeavor. Equilibrium molecular dynamics simulations were employed to investigate the density and transport properties of propane and ethane at ultra-low temperatures under evaporative pressure conditions. The results of the density simulation of the evaporation conditions of the blends proved the validity of the simulation method. Under identical temperature and pressure conditions, increasing the proportion of R170 in the refrigerant blends leads to a density decrease while the temperature range in which the gas-liquid phase transition occurs is lower. The analysis More >