Frontiers of Chemical Science and Engineering最新文献

Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.

To obtain high-performance flame-retardant epoxy resin (EP), diglycidyl ether of (2,5-dihydroxyphenyl) diphenyl phosphine oxide (DPO-HQ-EP) was synthesized. EP/DPO-HQ-EP samples with varying phosphorus contents were prepared by curing a mixture of DPO-HQ-EP and diglycidyl ether of bisphenol A. The incorporation of DPO-HQ-EP significantly enhanced the flame retardancy of EP without compromising its glass transition temperature. The EP/DPO-HQ-EP/0.6 exhibited a limited oxygen index of 31.7% and achieved a V-0 rating in the vertical burning test. In the cone calorimeter test, due to the incorporation of DPO-HQ-EP, the peak of heat release rate and total heat release of EP/DPO-HQ-EP/0.6 decreased by 39.4% and 15.9% compared with the values for pure EP. A detailed investigation of the flame-retardant mechanism revealed that the improved flame retardancy of EP/DPO-HQ-EP samples was attributed to the release of phosphorus-containing free radicals and non-flammable gases in the gas phase, as well as the formation of a continuous and dense char layer in the condensed phase. Moreover, the dielectric constant and dielectric loss factor of EP/DPO-HQ-EP samples were lower than those of EP/0. The water absorptivity and transparency of EP were effectively preserved with the incorporation of DPO-HQ-EP. These findings highlighted the potential of EP/DPO-HQ-EP for industrial applications in an electrical field.

The rapid accumulation of plastic waste poses severe environmental challenges. Cold plasma-driven degradation offers a promising route to convert plastic waste into high-value chemicals. In this study, a single-stage plasma reactor coupling cold plasma (dielectric barrier discharge) with Hβ zeolites was developed for polyethylene degradation under relatively mild conditions, without external thermal input or participation of noble metals. The effects of zeolite pore structure and acidity toward product distribution were investigated, revealing that Hβ-25 exhibited the highest C₁–C₆ yield (76 wt %) and a space-time yield of 103.8 mmol·g_cat⁻¹·h⁻¹ compared to other zeolite catalysts during the plasma-catalytic process. Meanwhile, it was revealed that efficient pre-cracking initiated by plasma activation and the optimal structural compatibility between Hβ-zeolite pore channels and primary cracking products were the key factors enabling the selective conversion of polyethylene into C₁–C₆ hydrocarbons. Additionally, metal incorporation significantly enhanced C–H bond cleavage compared to Hβ-25 support. Especially, 10Ni/Hβ-25 exhibited the highest hydrogen yield (7.87 mmol·g_plastic⁻¹) under plasma-assisted mode, markedly surpassing its yield under thermal-cracking conditions, demonstrating the significant potential of plasma-catalytic degradation for hydrogen production from polyethylene.

Alkaline metal salt-promoted MgO sorbents are effective for CO₂ capture, but they face challenges with decreased CO₂ capture performance and powder elutriation in practical applications, arising due to the loss of pore structures and poor mechanical strength of alkaline metal salt-promoted MgO sorbent powder. Herein, granulation technology was employed to resolve the above problem. The optimized alkaline metal salt-promoted MgO sorbent pellets exhibited a CO₂ capture capacity of 11.46 mmol·g⁻¹ and a mechanical strength of 11.14 MPa. This mechanical strength was nearly three times greater than that of alkaline metal salt-promoted MgO sorbent pellets without granulation promoters. After 20 cycles, CO₂ capture capacity stabilized at 8.71 mmol·g⁻¹, while mechanical strength was maintained at 8.92 MPa. Through characterization, it was revealed that the pore structure generated by the pyrolysis of the granulation promoters notably increased the specific surface area, leading to high CO₂ capture capacity. Meanwhile, the strengthened mechanical strength of the alkaline metal salt-promoted MgO sorbent pellets was primarily due to the in situ formation of a γ-AlOOH sol-gel cluster skeleton. Thus, this study provides an effective technological pathway to enhance the performance of the alkaline metal salt-promoted MgO sorbent pellets for industrial applications.

5-Hydroxymethylfurfural (5-HMF) is a versatile platform chemical that can be derived from renewable biomass using homogeneous or heterogeneous acid catalysts. However, efficiently separating and purifying 5-HMF from reaction mixtures remains a critical challenge for its high-value conversion from renewable biomass. To address this challenge, various separation methods have been developed, including distillation, adsorption, liquid-liquid extraction, supercritical carbon dioxide extraction, and integrated separation processes. This review summarizes and discusses recent advancements in the separation and purification of 5-HMF from reaction solutions. It evaluates key parameters such as adsorption capacity, separation selectivity, recovery efficiency, and their influencing factors. The liquid-liquid extraction using biphasic solvents has proven to be a simple, cost-effective, and efficient approach. The ionic liquid extraction, deep eutectic solvent extraction, supercritical carbon dioxide extraction, and integrated separation technologies (e.g., liquid-liquid extraction combined with vacuum distillation, distillation integrated with adsorption) are discussed. This review also provides insight into the mechanisms of different separation methods, which may contribute to the development of new processes for the purification of 5-HMF. This review aims to provide a theoretical basis for the future large-scale, efficient, and economic production of high-purity 5-HMF.

The selective oxidation of ethylene glycol to glycolic acid on the Pt₄, Pt₁₃, Pt₃₈, and Pt₅₅ clusters was investigated by using density-functional theory calculations. The calculated results imply that glycolic acid is preferentially generated through the dehydrogenation of ethylene glycol by OH to form HOCH₂CH₂O on the Pt₄, Pt₁₃, and Pt₃₈ surfaces, but that this process occurs directly without OH participation on the Pt₅₅ surface. The observed effect likely arises from the addition of OH, which modulates the electron density in the O atom of ethylene glycol, thereby affecting the cleavage of the O–H bond. Furthermore, the glycolic acid formation on the Pt_n clusters is limited by the β–H elimination of HOCH₂CH₂O to HOCH₂CHO, which exhibits the lowest energy barrier on the Pt₁₃ surface. It is because the d-band center of the Pt₁₃ cluster is closer to the Fermi energy than that of other clusters, which then enhances the electronic density of Pt. This facilitates the adsorption of HOCH₂CH₂O at the Pt sites and the activation of the C–H bond in HOCH₂CH₂O and therefore results in superior catalytic performance. This paper offers theoretical insights into the influence of Pt size on the selective oxidation of ethylene glycol to glycolic acid.

Graphdiyne represents an emerging nanofiller of mixed matrix membranes for high-performance alcohol recovery by pervaporation due to its unique alkyne-rich and porous framework and hydrophobicity. However, such membranes often encounter a persistent challenge of nanofiller agglomeration within the polymer matrix, which diminishes the efficacy of graphdiyne during alcohol recovery. This study proposes a multilevel dispersion strategy that synergistically combines in situ confined growth, ultrasonication, atomization, and rotational shearing throughout membrane preparation to mitigate particle aggregation. The particle agglomeration scale in the polydimethylsiloxane matrix can be effectively reduced from 660 nm of triphenylamine-based graphdiyne to about 291 nm compared to the general stirring-casting method. The mixed matrix membrane loaded with 2.5 wt % triphenylamine-based graphdiyne demonstrated a permeate flux of 2.35 kg·m⁻²·h⁻¹ alongside a separation factor of 11.31 for a 5 wt % ethanol/water solution. Compared to the stirring-casting method, these performances represent enhancements of 41% in permeate flux and 80% in separation factor. Furthermore, a 96 h-continuous pervaporation test indicated the robust stability of the membrane, underscoring the potential for industrial alcohol recovery.

Ligand modification of Cu catalysts has emerged as a promising strategy to enhance activity and stability in acetylene hydrochlorination. However, the limited availability of primary coordinating heteroatoms hinders precise engineering of the Cu active site microenvironment. Herein, a secondary coordination sphere modulation strategy was developed using various substituted hydrocarbon groups in the ligands. The local microenvironment around the Cu active sites was precisely tuned, leading to the Cu⁺ ratio of freshly prepared catalysts and reactive activity revealing a linear correlation, and the C₂H₂ adsorption energy exhibiting a distinct volcano plot correlation with catalytic activity. Among these catalysts, Cu-MMTB/AC exhibited the highest activity, achieving an acetylene conversion of 88.5% under the reaction conditions (T = 180 °C, gas hourly space velocity (GHSV) (C₂H₂) = 180 h⁻¹, and V(HCl): V(C₂H₂) = 1.2). Moreover, ^1#Cu₃-MMTB₁ exhibits advantages in both intermediate formation and HCl activation processes along the reaction pathway. This strategy offers a new avenue for designing high-performance Cu catalysts and promoting the use of mercury-free industrial catalysts.

Plasma-based gas conversion has emerged as a sustainable and promising approach for chemical production, attracting increasing attention in recent years. Significant progress has been achieved in areas such as nitrogen fixation, CO₂ conversion, methane activation, and others, driven by the contributions of researchers from diverse disciplines. Given that most research in this field is experimental, the methodologies employed play a pivotal role and demand careful consideration. However, due to the interdisciplinary nature of the field and variations in research objectives, available resources, and laboratory standards, experimental set-ups and approaches often differ significantly. Moreover, critical details regarding operational techniques and key methodologies are sometimes overlooked. This paper provides a comprehensive review of the methodologies and experimental approaches used in the study of plasma-based gas conversion for chemical production. It first examines experimental systems, including plasma reactor design, plasma-catalyst integration, and set-up configuration. Subsequently, operational schemes, conditions, and analytical procedures are discussed, with examples showcasing state-of-the-art advancements. Finally, discussion on emerging research trends and potential opportunities are presented, aiming to inspire further advancements and broaden the scope of this growing field.

Cyclone separators are extensively utilized for the efficient separation of solid particles from fluid flows, where their operational effectiveness is intrinsically linked to the equilibrium between pressure drop and collection efficiency. However, in extreme industrial environments, such as fluidized catalytic cracking processes, severe wall erosion poses a significant challenge that compromises equipment lifespan. The present study aims to identify an optimal trade-off among separation efficiency, energy consumption, and erosion rate through the optimization of geometric ratios in cyclone separators. By adjusting specific key dimensions, erosion can be mitigated, extending the separator’s lifespan in harsh conditions. The relationships between six geometric dimension ratios and inlet gas velocity with respect to performance indicators are systematically investigated using design of experiments and computational fluid dynamics simulations. To develop a robust performance prediction model that accounts for multiple influencing factors, an auto machine learning approach is employed, incorporating ensemble learning strategies and automatic hyperparameter optimization techniques, which demonstrate superior performance compared to traditional artificial neural network methodologies. Furthermore, pareto-optimal solutions for maximizing separation efficiency while minimizing pressure drop and erosion rate are derived using the nondominated sorting genetic algorithm II, which is well-suited for addressing complex nonlinear optimization problems. The results show that the optimized cyclone separator design enhances separation efficiency from 76.19% to 87.95%, reduces pressure drop from 1698 to 1433 Pa, and decreases the erosion rate from 8.06 × 10⁻⁵ to 7.32 × 10⁻⁵ kg·s⁻¹, outperforming the conventional Stairmand design.