The prime objective of this computational study was to develop a highly accurate potential for the use of molecular dynamics (MD) simulations of carbon nanotubes (CNTs). This potential was generated using ab initio MD (AIMD) simulations based on density functional theory (DFT). Subsequently, we constructed machine-learned interatomic potentials (MLIPs) based on moment tensor potential (MTP) descriptors using AIMD trajectories as training data. The performance of the developed MLIPs was evaluated by conducting the MD simulations of the stress–strain responses of single-walled CNTs (SWCNTs) and defected SWCNTs (D-SWCNTs) under tensile loading. Furthermore, this work includes extensive MLIP-based MD simulations to examine the influence of diameter and chirality, temperature, and defect concentration on the fracture characteristics and Young’s modulus of SWCNTs. The findings demonstrate the computational reliability and transferability of the MLIPs in predicting the mechanical properties of SWCNTs through MD simulations performed over a temperature range of 1 K to 2000 K. The observed stiffnesses correspond to Young’s modulus ranging from 1.61–0.53 TPa with a mean value of 0.936 TPa for different SWCNTs with diameters ranging from 1.1–2.89 nm and temperatures spanning from 1 to 2000 K, exhibiting a noticeable dependence on chirality.

The adsorption of molecular hydrogen on the monolayer graphene sheet under varied temperature and pressure was studied using molecular dynamics simulations (MDS). A novel method for obtaining potential energy distributions (PEDs) of systems was developed to estimate the gravimetric density or weight percentage of hydrogen. The Tersoff and Lennard–Jones (LJ) potentials were used to describe interatomic interactions of carbon–carbon atoms in the graphene sheet and the interactions between graphene and hydrogen molecules, respectively. The results estimated by the use of novel method in conjunction with MDS developed herein were found to be in excellent agreement with the existing experimental results. The effect of pressure and temperature was studied on the adsorption energy and gravimetric density for hydrogen storage. In particular, we focused on hydrogen adsorption on graphene layer considering the respective low temperature and pressure in the range of 77–300 K and 1–10 MPa for gas storage purpose which indicate the combination of optimal extreme conditions. Adsorption isotherms were plotted at 77 K, 100 K, 200 K, and 300 K temperatures and up to 10 MPa pressure. The simulation results indicate that the reduction in temperature and increase in pressure favor the gravimetric density and adsorption energies. At 77 K and 10 MPa, the maximum gravimetric density of 6.71% was observed. Adsorption isotherms were also analyzed using Langmuir, Freundlich, Sips, Toth, and Fritz–Schlunder equations. Error analysis was performed for the determination of isotherm parameters using the sum of the squares of errors (SSE), the hybrid fractional error function (HYBRID), the average relative error (ARE), the Marquardt’s percent standard deviation (MPSD), and the sum of the absolute errors (SAE).