A Meta‐Analysis of Catalytic Hydrogenation of Levulinic Acid to γ‐Valerolactone

Abstract Selective hydrogenation of biomass‐derived levulinic acid (LA) to γ‐valerolactone (GVL) is an important reaction in biomass upgradation to produce valuable fuels and chemicals. Increasing demand for renewable energy sources has stipulated growth in catalytic research and has generated a massive amount of experimental data over the years. Inside this numerous data, fresh insights into property‐performance associations can be found. However, the incomplete existence and unclear structure of these data records have hampered systematic information extraction thus far. This research proposes a meta‐analysis approach for identifying associations between the physico‐chemical properties of a catalyst and its reaction performance. The approach combines data from literature with insights from textbooks and statistical methods. A hypothesis is formulated based on a researcher's intuition and statistical significance is checked against the data. Repetitive hypothesis refining gives robust, clear, and analyzable chemical models. The results can be used to guide future research and catalyst production. The method for catalytic hydrogenation of LA to GVL is shown and validated here.