Efficient synthesis of organosulfur compounds via electrochemical biomass conversion
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Rising greenhouse gas emissions embodied in the global bioeconomy supply chain
The bioeconomy is key to meeting climate targets. Here, we examine greenhouse gas emissions in the global bioeconomy supply chain (1995–2022) using advanced multi-regional input-output analysis and a global land-use change model. Considering agriculture, forestry, land use, and energy, we assess the carbon footprint of biomass production and examine its end-use by provisioning systems. The footprint increased by 3.3 Gt CO2-eq, with 80% driven by international trade, mainly beef and biochemicals (biofuels, bioplastics, rubber). Biochemicals showed the largest relative increase, doubling due to tropical land-use change (feedstock cultivation) and China’s energy-intensive processing. Food from retail contributes most to the total biomass carbon footprint, while food from restaurants and canteens account for >50% of carbon-footprint growth, with three times higher carbon intensity than retail. Our findings emphasize the need for sustainable sourcing strategies and that adopting renewables and halting land-use change could reduce the bioeconomy carbon footprint by almost 60%.
Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning
Designing molecules with desirable properties is a critical endeavor in drug discovery. Because of recent advances in deep learning, molecular generative models have been developed. However, the existing compound exploration models often disregard the important issue of ensuring the feasibility of organic synthesis. To address this issue, we propose TRACER, which is a framework that integrates the optimization of molecular property optimization with synthetic pathway generation. The model can predict the product derived from a given reactant via a conditional transformer under the constraints of a reaction type. The molecular optimization results of an activity prediction model targeting DRD2, AKT1, and CXCR4 revealed that TRACER effectively generated compounds with high scores. The transformer model, which recognizes the entire structures, captures the complexity of the organic synthesis and enables its navigation in a vast chemical space while considering real-world reactivity constraints.
Mechanisms of electrochemical hydrogenation of aromatic compound mixtures over a bimetallic PtRu catalyst
Efficient electrochemical hydrogenation (ECH) of organic compounds is essential for sustainability, promoting chemical feedstock circularity and synthetic fuel production. This study investigates the ECH of benzoic acid, phenol, guaiacol, and their mixtures, key components in upgradeable oils, using a carbon-supported PtRu catalyst under varying initial concentrations, temperatures, and current densities. Phenol achieved the highest conversion (83.17%) with a 60% Faradaic efficiency (FE). In mixtures, benzoic acid + phenol yielded the best performance (64.19% conversion, 74% FE), indicating a synergistic effect. Notably, BA consistently exhibited 100% selectivity for cyclohexane carboxylic acid (CCA) across all conditions. Density functional theory (DFT) calculations revealed that parallel adsorption of BA on the cathode (−1.12 eV) is more stable than perpendicular positioning (-0.58 eV), explaining the high selectivity for CCA. These findings provide a foundation for future developments in ECH of real pyrolysis oil.
Closed-loop enhancement of plant photosynthesis via biomass-derived carbon dots in biohybrids
Improving photosynthetic efficiency is pivotal for biomanufacturing and agriculture. Despite the progress on photosynthetic biohybrids integrating biocatalysts with materials, nanomaterials with increasing energy-efficiency as well as great biocompatibility and cost-effectiveness are needed. Here, we present a closed-loop strategy using biomass-derived carbon dots (CDs) for improving photosynthesis. We demonstrate that the CDs act as both light converters and photosensitizers by converting solar irradiation to red light and supplying light-excited electrons into the photosynthetic electron transfer chain. Biohybrids incorporating CDs and cyanobacteria or plant exhibited increased photosynthetic efficiency, when compared with the photosynthetic organism only. The cyanobacterial CO2-fixation rate and CO2-to-glycerol production were increased 2.4-fold and 2.2-fold, respectively, while Arabidopsis thaliana displayed a 1.8-fold increase in the fresh weight of the plant. Techno-economic analysis showed the competitive advantage of biomass-derived CDs over other nanomaterials. These CDs hold potential applications in future sustainable agriculture and solar-powered biomanufacturing.
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