This study uses density functional theory (DFT) technique to examine the hydrogen molecules (H₂) storage on Li-decorated h-BN monolayer. The results of DFT have proven that Li-doped h-BN system can hold up to 9H₂ with the adsorption energy lying in between −0.31 eV and −0.24 eV/H₂ at ambient condition. However, the calculated average adsorption energy for 9H₂ is −0.240 eV/H₂ with hydrogen storage capacity of 5.96 wt.%, which is according to the United States Department of Energy. Partial density of state was computed for each configuration to provide additional justifications for the H₂ storage on Li-doped h-BN monolayer. The hybridization shows a significant interaction between H₂ and Li atom, and most of their hybrid peaks were observed in the energy range from −7.5 to −1 eV. Moreover, the H₂ desorption simulations achieved via the ab initio molecular dynamics. The computed desorption temperature T_D is 306 °K, which is a suitable operating temperature. Hence, our research demonstrates that Li-doped h-BN is a thermally stable and viable hydrogen storage material for hydrogen storage systems.

This study presents a robust, end-to-end machine learning framework for detecting Non-Technical Losses (NTLs) in smart power grids. The proposed Optimized Bootstrapped Gradient Classifier (OBGC) integrates k-Nearest Neighbor (kNN) imputation for missing data handling, Adaptive Synthetic Sampling (ADASYN) for class imbalance correction and Optuna-based hyperparameter optimization. The framework is evaluated using the State Grid Corporation of China (SGCC) dataset comprising 42,373 consumers over 1035 days (January 2014–October 2016), characterized by 25.6% missing values and a severe class imbalance (91.46% honest vs. 8.54% theft-prone consumers). To ensure robust evaluation, all experiments employ stratified 5-fold cross-validation on the training set, with a held-out 20% test set reserved for final performance assessment. Experimental results show that OBGC achieves an accuracy of 96.61%, precision of 96.18%, recall of 97.13%, and F1-score of 96.65%, substantially outperforming baseline XGBoost (accuracy 92.75%, F1 36.11%) and other state-of-the-art classifiers. An ablation study confirms that ADASYN is the most critical component; its removal causes recall to collapse from 97.13% to 16.87%, demonstrating the severe impact of class imbalance on theft detection. Optuna-based tuning contributes an additional 3.29 percentage-point gain in accuracy over the unoptimized baseline. The framework offers a transparent, reproducible, and operationally feasible solution for real-world NTL detection.

Hydrogen (H ₂ ) has attracted considerable attention as a promising energy carrier due to its high energy content compared to conventional fossil fuels. The continuous growth of the global population is driving an increasing demand for energy, leading to higher consumption of fossil fuels and, consequently, increased greenhouse gas emissions and climate change. This has driven the research community toward renewable energy sources (RESs) such as solar, wind, and tidal energy. Among RES options, hydrogen stands out as one of the most viable alternatives. The significant research has focused on hydrogen production and its applications, comparatively less attention has been given to hydrogen storage. In this context, the hydrogen storage characteristics of alkali metal (AM) and alkaline earth metal (AEM) decorated and defective hexagonal boron nitride (h‐BN) nanosheets were systematically investigated using density functional theory (DFT) calculations. The AM atom (Li) and AEM atom (Be) are found to be uniformly dispersed on h‐BN surfaces containing boron vacancies and divacancy defects, effectively preventing atom clustering. Up to 19 H ₂ molecules can be adsorbed on the surface of Be‐decorated Li‐doped h‐BN, exhibiting an average adsorption energy ranging from −0.23 to −0.42 eV per H ₂ molecule. Electronic structure analysis reveals that the introduction of Li and Be atoms significantly alters the electronic properties of pristine h‐BN, as indicated by the modification of bands near the Fermi level, thereby enhancing conductivity and inducing semiconducting behavior. Furthermore, Be decoration Li doping collectively improves the hydrogen storage capacity (HSC), achieving a theoretical gravimetric density of up to 11.22 wt.%. The thermal stability of the H ₂ ‐adsorbed system was further evaluated using ab initio molecular dynamics (AIMD) simulations and the van’t Hoff equation, confirming its robustness under thermal conditions.