Dhirendra Kumar Mishra

Efficient lignin valorization requires not only catalytic depolymerization but also a scalable, aqueous separation route that isolates bioavailable low‐molecular‐weight (LMW) products from recalcitrant oligomers/polymers. Here, oxidative depolymerization of poplar lignin was coupled with cross‐flow nanofiltration using reduced‐graphene‐oxide (rGO) membranes (molecular‐weight cut‐off or MWCO ≈ 470 Da). Across six depolymerization liquors spanning pH 2.5–9.2 and distinct catalytic histories (of polyoxometalate (POM), NaOH, graphene oxide, and control), rGO membranes consistently rejected ≥90% of the >1.6 kDa fraction, while feed pH governed LMW partitioning. Acidic liquors favored a steric‐sieving regime that enriched aliphatic and aromatic monomers in the permeate (separation factors ≈5–6 relative to the high‐MW fraction), whereas alkaline conditions induced electrostatic exclusion, co‐retaining anionic acids with oligomers and suppressing monomer enrichment. Mechanistic studies with model mixtures showed that dilution sharpened selectivity by mitigating concentration polarization and ionic‐strength screening and that aromatics can modulate charge‐based exclusion through competitive interactions within graphitic nanochannels. Continuous diafiltration of the monomer‐rich liquor for 250 h sustained stable flux (~11 ± 1 L m ⁻² h ⁻¹ ) and selectivity, enabling complete recovery of aliphatic and aromatic monomers and LMW fractions while concentrating high‐MW fractions. These results establish rGO membranes as a robust, water‐based separation platform for MW‐resolved lignin fractionation.

Lignin valorization is restricted by the stability of its methoxy groups, creating a critical need for efficient demethylation strategies. Here, density functional theory (DFT) is employed to dissect the mechanistic pathways of demethylation in lignin model compounds, guaiacol and syringol, using protic ionic liquids (PILs) that act as both solvent and catalyst. Conductor‐like Screening Model for Real Solvents (COSMO‐RS) analysis identifies monoethanolammonium acetate ([MEOA][Ace]) as the most promising medium, attributed to its strong hydrogen bonding network and solvation ability. By integrating implicit and explicit solvation models, it is revealed that an acid‐catalyzed hydrolytic mechanism governs demethylation, with PILs stabilizing crucial transition states and intermediates. Complementary electronic structure evaluations, including highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO‐LUMO) gap analysis, charge distribution, and electrostatic potential mapping, demonstrate how PILs lower energetic barriers and enhance reactivity. To simulate realistic environments, this study is extended to lignin dimer complexes with varying water content, uncovering how water‐bridged solvation reverses demethylation preference from guaiacyl to syringyl units. This mechanistic shift aligns with experimental observations showing faster S‐unit reactivity in hydrated systems. Together, these findings provide atomic‐level insight into lignin demethylation dynamics and highlight how tuning acid concentration in PILs can accelerate kinetics, enabling a rational pathway toward next‐generation biomass conversion technologies.

Biorefineries, which process biomass feedstocks into valuable (bio)products, aim to replace fossil fuel-based refineries to produce energy and chemicals, reducing environmental and health hazards, including climate change, and supporting a sustainable economy. In particular, lignocellulose-based biorefineries, utilizing the most abundant renewable feedstock on Earth, have significant potential to supply sustainable energy, chemicals and materials. Ionic liquids (ILs, organic salts with low melting temperatures) and deep eutectic solvents (DESs, mixtures with eutectic points lower than the ideal mixture) are capable of dissolving some of the key lignocellulose polymers, and even the whole biomass. Furthermore, they have intrinsic advantages over molecular solvents, including safer usage profiles and high tunability, which allow tailored physicochemical properties. Such properties provide unique opportunities for the development of new processes that could unlock the full potential of future biorefineries. Here, we review the current state of lignocellulosic biomass processing with ILs and DESs, with a specific focus on the pretreatment chemistry, process flow and products from each component; followed by discussions on sustainability assessments and technological challenges. We aim to inform the research community about the opportunities, challenges and perspectives in developing truly sustainable lignocellulose-based biorefineries.

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

Deep eutectic solvents (DESs) based on metal halide salts are highly catalytic, low toxic, reusable, cost-effective, and have higher thermal stability than their analogue ionic liquids (ILs). In this work, we have reported the formation mechanism of metal salt-based DESs at the molecular level along with their charge-transfer analysis and thermodynamics associated with their formation using density functional theory. The DES systems analyzed in the present work were choline chloride and tin(II)chloride (DES1) and choline chloride and zinc(II)chloride (DES2), both in a molar ratio of 1:2, respectively. An excellent correlation is obtained between the theoretically calculated IR spectra of the DES systems and the previously reported experimental findings for the formation of the complex systems. The DESs were found to be stable systems due to traditional hydrogen bonding and electrostatic interactions resulting in the ionic species [Sn₂Cl₅]⁻ and [Zn₂Cl₅]⁻ and are elucidated with the help of electronic structure calculations. CHELPG partial charge analysis and natural bond orbital analysis suggest a charge transfer from Cl^– (chloride) to Ch⁺ (choline) and metal salts in the DES structures. The atom-in-molecules and noncovalent interaction (NCI) analysis suggest a strong electrostatic interaction within the DES2 system as compared to DES1. Higher stability and reactivity are observed in the DES2 system based on the frontier molecular orbital analysis. Our analysis offers important insights into the formation mechanism of these economic IL analogues.