An accurate viscosity prediction model is essential for the intelligent design and industrial scaling of ionic liquid (IL)-based technologies. This study presents a novel hybrid residual modeling strategy that leverages machine learning to identify and capture systematic deviations in physical modeling. The model was developed using experimental viscosity data for 159 ILs and seven quantum chemical descriptors determined from first-principle. A physics-based viscosity model (COSMO-RS) provides prior knowledge as one example, where systematic deviations follow a power law distribution (n_cosmo = An_exp^B) identified in this work. The proposed model with systematic deviations demonstrates excellent performance compared to the model with random deviations and also outperforms the conventional hybrid and data-driven models, achieving superior predictive accuracy on the test set (R² = 0.993, MAE = 0.04) and reducing the average absolute relative deviation from 52.42 % to 4.49 %. Feature importance results reveal the key descriptors contributing to the systematic deviations: A = f(Polarity), B = f(Sigma, AdE).

The century-old Murray’s law, originally formulated to describe optimal transport in biological vascular systems, continues to inspire the design of hierarchical nanomaterials. However, at the nanoscale, its fundamental assumptions of fluid homogeneity and negligible interfacial slip no longer hold, limiting its validity. In this work, Murray’s law is extended to incorporate nanoscale effects, including slip boundary conditions and confinement-induced variations in fluid density and viscosity. Quantitative calculations reveal a transition from traditional viscous flow dominance at larger scales to interfacial slip-driven transport in microporous channels, leading to significant deviations from the original predictions of Murray’s law. Furthermore, the physical foundation of the nanoscale-adapted Murray’s law, namely minimum energy dissipation in nonequilibrium thermodynamics, is restated as a generalized resistance matching principle, offering a practical framework for designing hierarchical structures. This principle is experimentally validated in two structurally diverse nanosystems─biological-skeleton carbon and zeolite molecular sieves─demonstrating its broad applicability. The work provides a generalizable theoretical foundation and a practical benchmark for the rational engineering of advanced hierarchical nanomaterials. By bridging a century-old biological principle with modern nanofluidics, the proposed resistance-matching principle is expected to influence fields such as heterogeneous catalysis, membrane technology, and energy storage.

Upgrading clean energy fuels, such as biogas, natural gas, and shale gas, requires the capture of CO2 to enhance their heating value. Ionic liquids (ILs) are promising absorbents for this purpose, but the vast number of available ILs necessitates an efficient screening method. The Comparative Absorption Factor (CAF) developed in our previous study can estimate the total annual cost (TAC) of CO2 capture from biogas, which is a key advantage over alternative screening methods. However, CAF does not consider the effects of operating conditions such as CO2 concentration, pressure, and temperature. To address this limitation, a modified CAF (CAFmodified) that incorporates these factors was proposed. Given the linear relationship between the original CAF and TAC, three representative ILs ([C10mpy][DCA], [C1mim][tfo], and [C1py][tfo]) were selected from 490 ILs based on their melting point, viscosity, and original CAF values. Subsequently, process simulations for these ILs were conducted using Aspen Plus, considering a wider range of operating conditions: CO2 concentrations of 30–50 vol%, temperatures of 303.15–318.15 K, and pressures of 7–15 bar. These simulations were used to determine the Aspen Plus-derived TAC, which served as the basis for proposing CAFmodified. Finally, data for Aspen Plus-derived TAC from the previous study and for 6 additional ILs over a broad range of operating conditions were used to compare with the TAC values estimated by CAFmodified. The results showed an average relative deviation of 16%, indicating that CAFmodified is effective for screening ILs for CO2 capture under varying operating conditions.

The hybrid sorbent, combining ionic liquid and activated carbon, offers an innovative pathway for CO₂/CH₄ separation. This study prepared three single-step steam activated bamboo carbons (SBCs), and developed the hybrid sorbents of 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([Hmim][NTf₂])/SBCs/water (H₂O). The gas solubility and sorption rate in the hybrid sorbent were measured, and the Henry's constant, selectivity, and liquid-phase mass-transfer coefficient were calculated. Additionally, a self-developed index was utilized to estimate the CO₂/CH₄ separation cost using the hybrid sorbents. The results showed that the hybrid sorbent containing SBCs prepared by the steam activation at 1073.2 K and 120 min (S812) exhibited the most efficient CO2/CH4 separation performance owing to its optimal microporous structure and oxygen-containing functional groups. Consequently, the hybrid sorbent of [Hmim][NTf₂]/S812-H₂O (w_{[Hmim][NTf2]/S812}=3.0 wt%) demonstrated a 3.2 times intensification on the comprehensive CO₂/CH₄ separation performance as well as a 53.8 % reduction of separation cost compared to the commercial technology. 

Deep eutectic solvents (DESs) have attracted considerable attention as promising alternatives to conventional solvents for mitigating CO2 emissions due to their tunable structures, low volatility, and promising physicochemical properties. In this work, a series of [Triz]Cl/amine DESs were designed and synthesized and then formulated as 30 wt% aqueous solutions (30 wt% DES + 70 wt% H2O) to systematically investigate how the type of hydrogen bond donor (HBD) affects their physicochemical properties, thermal stability, and CO2 capture performance, and to identify the most effective solvent; their CO2 absorption capacity, absorption rate, thermal stability, and desorption efficiency were determined experimentally, and a novel stepwise evaluation strategy was employed for identification. [Triz]Cl/DETA was identified, exhibiting significantly enhanced performance, with CO2 absorption capacity, absorption rate, thermal stability, and cyclic loading increased by 34%, 12%, 114%, and 39%, respectively, when compared with the conventional monoethanolamine (MEA). Its viscosity (both before and after CO2 absorption), oxidative stability, and corrosion resistance were further studied, confirming the superior performance, and the reaction mechanism was also elucidated. This work provides valuable insights into the structure–property relationships of DESs and establishes [Triz]Cl/DETA-based solvents as promising candidates for efficient and sustainable CO2 capture applications.

The development of advanced absorbents for effectively capturing carbon dioxide is crucial in mitigating greenhouse gas emissions. This study introduced a series of deep eutectic solvents (DESs) for CO2 capture and identified the most promising DESs with the stepwise screening method based on their absorption capacity, absorption rate, thermal stability, desorption efficiency, and apparent activation energy. Consequently, compared to the monoethanolamine (MEA), in the 30 wt% aqueous solutions, [1,2,3-Triazolium chloride][diethylenetriamine] ([TrizCl][DETA]) and [Piperazinium chloride][diethylenetriamine] ([PzCl][DETA]) improved the CO2 absorption capacities by 31% and 34%, absorption rates by 12% and 30%, and the amounts of CO2 desorbed by 42% and 23%, as well as reduced the apparent activation energies by 9% and 28%, respectively. Meanwhile, their thermal stabilities (degradation onset temperatures, Tonset) were enhanced by 101% and 32%, respectively. The FTIR and NMR analyses were conducted to provide deeper insights into the chemical absorption mechanism of CO2 by the DESs. 

Lignin, the most abundant aromatic biopolymer in nature, is composed of phenylpropane units and represents a promising renewable source of aromatic chemicals for industrial applications. The valorization of lignin into bio-based chemicals through electrolyzers and upgrading technologies holds significant potential for developing environmentally and economically sustainable biorefineries. This minireview explores electrochemical hydrogen production coupled with alternative oxidation reactions that can replace the oxygen evolution reaction (OER), alongside discussions of lignin's structure, solubility, analytical methods, and the challenges of electrochemical depolymerization. Among various strategies, the electrocatalytic oxidation of lignin-derived phenolics has emerged as an environmentally benign approach, utilizing renewable electricity to drive reactions under mild and controlled conditions. Key topics include the development of efficient electrocatalysts for phenolic conversion and lignin-assisted proton exchange membrane electrolysis. Emphasis is placed on achieving high electrocatalyst activity, stability, and selectivity for effective lignin oxidation. Furthermore, challenges related to catalyst design, electrode materials, electrocatalytic systems, and process optimization are critically examined, along with potential pathways for improvement. This minireview highlights the opportunities and challenges in advancing electrocatalytic lignin valorization and provides perspectives on future developments in catalyst design and proton exchange membrane electrolysis integration to promote sustainable biomass utilization in accordance with green chemistry principles.

The electrical conductivities of 1-hexyl-3-methylimidazolium halides ([Hmim][halide], halide = Cl–, Br–, I–) were measured in methanol (MeOH) and dimethyl sulfoxide (DMSO) at dilute concentrations from 293.15 to 313.15 K, alongside liquid density measurements for parametrization. Molar conductivity (Λ) decreased with increasing IL concentration and decreasing temperature, with solvent effects predominating over those of anion size. Λ was higher in MeOH than in DMSO due to lower viscosity and greater ion dissociation of MeOH. Comparison with a previous study involving H2O, MeOH, DMSO, and isopropanol confirmed that solvent viscosity is the dominant factor influencing Λ at infinite dilution. At higher IL concentrations, Λ in MeOH fell below that in H2O, likely due to a reduced number of free ions and the formation of larger solvated ion complexes.To analyze conductivity behavior, the Debye-Huckel-Onsager model was employed to determine the limiting molar conductivity (Λ0), which was subsequently used in the Shedlovsky equation to calculate the association constant (KA). For comparison, simultaneous regression of Λ0 and KA was also performed. The results indicated that, within the same solvent, Λ0 increased with temperature, while KA exhibited irregular trends. Across different solvents, Λ0 correlated with solvent viscosity, and KA was influenced by dielectric constant and polarity. Solvent effects on both Λ0 and KA were more pronounced than those of anion size, suggesting the dominant role of the solvent environment. Positive Eyring activation enthalpies showed the endothermic ion-pairing process. Additionally, the Walden product suggested stronger ion-solvent interactions and larger solvated ions in MeOH compared to DMSO. These findings provide deeper insight into IL conductivity in diverse solvent environments.

Hypothesis

We hypothesize that the large uncertainty of slip length in conventional approaches for Newtonian fluids under creeping flow and lubrication approximation conditions arises from the assumed ideal velocity distribution, and an alternative approach that does not require assuming an exact velocity distribution is of great value under the same conditions.

Methodology

In this study, we developed a new methodology to quantitatively and accurately determine slip length by converting the AFM-measured hydrodynamic forces and approach rates into mass flow and velocity-independent resistances and by using the Stribeck curve to identify the appropriate data interval. To prove the concept, we employed high-precision colloidal probe atomic force microscopy (CP-AFM) technology to study water on hydrophilic, less-wetting, and unmodified silicon surfaces across six driving velocities (6.0–36.6 μm/s), and their slip length values were then obtained, compared with conventional methods combined with further discussions.

Findings

The resulting slip lengths show no dependence on the driving velocity. We further introduce an analysis of extended uncertainty, demonstrating that our method exhibits an extended uncertainty less than one-third of that from the conventional approaches. Subsequently, we quantitatively assessed the contribution of friction resistance (RFriction, directly linked to slip) in the total resistance (RTotal). The results show that, as the separation increases, the contribution of RFriction decreases significantly, which explains why the slip length is so difficult to measure precisely. This study reveals that the large uncertainty of slip length obtained with the conventional methods stems from underestimating the contribution of RFriction, and this work provides a novel and reliable methodology for achieving high-precision slip length by precisely decoupling the viscous and friction flow components.

Composite solid electrolytes (CSEs) combine the flexibility of polymers with the stability of inorganic electrolytes, making them promising candidates for next-generation solid-state lithium-metal batteries (LMBs). However, their practical application is limited by low room-temperature ionic conductivity, primarily due to poor polymer-inorganic interfacial compatibility that hinders Li+ transport. In this work, we introduce a polymer-compatible ionic liquid (IL) to mediate the interphase between the polymer and ceramic components, simultaneously preventing ceramic particle aggregation for uniform dispersion and activating ceramic-polymer interfaces to construct continuous Li+ transport pathways across ceramic domains and interfacial boundaries. The interfacial engineered CSEs exhibit a substantial enhancement in room-temperature ionic conductivity to 1.64 × 10−3 S cm−1. At the ambient temperature, the Li||Li symmetric cells demonstrate stable and reversible lithium plating/stripping for 4000 h, and the Li||LiFePO4 cell delivers an initial specific capacity of 172.1 mAh g−1 at 0.5C with 90.4% capacity retention after 300 cycles. Furthermore, the Li||LiNi0.8Co0.1Mn0.1O2 cells demonstrate stable performance even under high-voltage operation (4.5 V). This work provides a practical interfacial design strategy for developing high-performance CSEs in the next-generation solid-state LMBs.