This study proposes an efficient in-silico adsorbent material selection strategy for clean fuel combustion by leveraging Density Functional Theory (DFT) calculated reactivity parameters to optimize material configurations for enhanced dibenzothiophene (DBT) adsorption from model fuel oil (n-octane). A DFT screening identified TiO2 as the optimal material for DBT adsorption from biochar and four metal oxide (MOx) based on calculated adsorption energies (Eads). Further DFT optimization identified a 10 % TiO2 composition with biochar (TBC10) as the optimal material. This composite exhibited the strongest DBT interaction (−370.3 kcal mol−1) and a remarkably short sulfur-titanium bond (2.64 Å), indicative of an ideal adsorption geometry. Notably, TBC10 features a unique composite structure: TiO2 connected to BC via van der Waals forces, while DBT directly interacts with AC through π-π stacking and covalent sulfur-titanium bonds. To validate theoretical predictions, the designed composites were synthesized and experimentally evaluated. The excellent alignment between experimental adsorption performance and DFT-calculated adsorption energies corroborated TBC10′s superior DBT adsorption capacity. Employing a systematic optimization process, the most effective parameters for TBC10′s DBT removal from a 150 mL solution containing an initial DBT concentration of 45 mg L-1 were established as: a 30 min contact time, an adsorbent dosage of 13 mg, and a temperature of 25 °C. Under these conditions, TBC10 achieved a remarkable removal efficiency (RRDBT) of 99.82 % and a maximum DBT uptake capacity (qDBT) of 31.1 mg g−1. Kinetic and statistical physics modeling revealed a multi-molecular adsorption process with distinct binding sites, characterized by spontaneous endothermic interactions and involving both physical and chemical mechanisms. The in-silico methodology for adsorbent design reduces experimentation time, cost and identifies optimal candidates for DBT removal, enhancing fuel desulfurization and promoting sustainable combustion. This novel in-silico design paradigm holds immense potential for the development of next-generation adsorbents for various environmental remediation and industrial separation processes.