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The relationship between slag structure and viscosity is studied, employing Raman spectroscopy for the five-component slag system of MnO-SiO2-CaO-Al2O3-MgO and its subsystems. This study aims to investigate the influence of variations in slag composition on viscosity, which is crucial for optimizing industrial processes. Based on industrial slag compositions produced in a silicomanganese submerged arc furnace, 17 slags with a fixed content of MnO of 10 wt% are synthesized with varying contents of SiO2 of 33 to 65 wt%; CaO within the range of 14 to 40 wt%; and fixed contents of Al2O3 and MgO of 17 and 6 wt%, respectively. The slag compositions are divided into four groups, ranging from low basicity (0.38) to high basicity (0.80), with each group containing the four slag systems of MnO-SiO2-CaO, MnO-SiO2-CaO-Al2O3, MnO-SiO2-CaO-MgO, and MnO-SiO2-CaO-Al2O3-MgO, with fixed basicity. Additionally, a five-component composition with the lowest basicity of 0.28 is considered. Raman spectroscopy measurements are performed in the wavenumber range of 200 to 1200 cm-1 using a green source laser with a 532 nm wavelength. The high-wavenumber region of the Raman spectra (800 to 1200 cm-1) is deconvoluted to quantitatively investigate the effect of each oxide on the slag structure and the degree of polymerization (DOP) of the silicate network. Results indicate that measured NBO/T increases with increasing basicity, demonstrating a reduction in DOP of the silicate structure. This depolymerization effect is more pronounced in slags containing Al2O3 compared to those without it. In a group of slags with similar basicity, the substitution of SiO2 with Al2O3 leads to further depolymerization. In contrast, substituting CaO with MgO has little effect on the silicate structure in slags without Al2O3 but causes depolymerization in slags containing Al2O3. To study the relationship between structure and viscosity, viscosity data obtained from FactSage are used as reference values. The predictions of slag viscosity using the Raman-structure model and the NBO/T viscosity model are then compared to the FactSage results. The adjustable parameters of the Raman-structure model are re-determined using the FactSage data for the studied slag compositions. The NBO/T viscosity model employs both calculated NBO/T values from the slag compositions and measured NBO/T values from the deconvolution results. The findings of this study reveal good agreement between the predictions of the Raman-structure model and the FactSage viscosity data.
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In the deep-ultraviolet (DUV) region, nonlinear optical (NLO) crystals must meet stringent requirements, including a large optical band gap and sufficient second harmonic generation (SHG) response. Typically, these criteria are fulfilled by borates, carbonates and nitrates containing π-conjugated groups. In contrast, sulfates and phosphates, with polarizabilities significantly smaller than those of π-conjugated groups, struggle to achieve similar performance. Here, we present the discovery of Mg2PO4Cl, a magnesium-based phosphate, identified from over 10,000 phosphates based on a polar-axial-symmetry screening strategy, which exhibits the highest SHG response (5.2 × KH2PO4 (KDP)) with phase-matching ability among non-π-conjugated DUV transparent NLO crystals. This compound belongs to the Pna21 space group, with [PO4] units consistently aligned along the 21 screw axis and glide planes throughout its crystal structure. Theoretical calculations attribute its remarkable SHG effect to the orderly arrangement of heteroanionic [MgO5Cl] and [MgO4Cl2] polyhedra alongside isolated [PO4] tetrahedra, supported by Berry phase analysis. Furthermore, a crystallographic structure analysis of phosphates and sulfates with significant SHG effects validates the effectiveness of our screening strategy. These findings offer valuable insights into the origins of NLO effects in non-π-conjugated compounds from both a material design and structural chemistry perspective, inspiring future efforts to revitalize DUV phosphates.
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Vacancy-ordered perovskites and derivatives represent an important subclass of hybrid metal halides with promise in applications including light emitting devices and photovoltaics. Understanding the vacancy-property relationship is crucial for designing related task-specific materials, yet research in this field remains sporadic. For the first time, we use the Connolly surface to quantitatively calculate the volume of vacancy (Vâ¡, â¡ = vacancy) in vacancy-ordered double perovskite derivatives (VDPDs). A relationship between void fraction and the structure, photoluminescent properties and humidity stability was established based on zero-dimensional (0-D) [N(alkyl)4]2Sbâ¡Cl5â¡'-type VDPDs. Compared with the more commonly studied A2M(IV)X6â¡-type double perovskite (A = cation, M = metal ion, X = halide), [N(alkyl)4]2Sbâ¡Cl5â¡' features double vacancy sites. Our results demonstrate an inverse relationship between the photoluminescent quantum yield and Vâ¡ in 0-D VDPDs. Additionally, structural transformation from A2SbCl5 to A3Sb2Cl9 was first reported, during which the novel 'gate-opening' gas adsorption phenomenon was observed in VDPDs for the first time, as evidenced by 'S'-shaped sorption isotherms for water vapor, indicating a cation-controlled water-vapor response behavior. A mixed-cation strategy was developed to modulate the humidity stability of VDPDs. Characterized by controllable water-responsive behavior and unique 'on-off-on' luminescent switching, A2M(III)â¡X5â¡'-type materials show great promise for multi-level information anti-counterfeiting applications.
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Anisotropy is crucial for birefringence (Δn) in optical materials, but optimizing it remains a formidable challenge (Δn > 0.3). Supramolecular frameworks incorporating π-conjugated components are promising for achieving enhanced birefringence since their structural diversity and inherent anisotropy. Herein, we first synthesized (C6H6NO2)+Cl- (NAC). And then constructed a halogen bonded supramolecular framework I+(C6H4NO2)- (INA) by halogen aliovalent substitution of Cl- with I+. The organic moieties are protonated and deprotonated nicotinic acid (NA), respectively. The antiparallel arrangement of birefringent-active units in NAC and INA leads to significant differences in bonding characteristics between interlayer and intralayer domains. Moreover, [O···I+···N] halogen bond in 1D [I+(C6H4NO2)-] chain exhibits stronger interactions and stricter directionality, resulting in a more pronounced in-plane anisotropy between the intrachain and interchain directions. Consequently, INA exhibits exceptional birefringent performance, with a value of 0.778 at 550 nm, twice that of NAC (0.363 at 550 nm). This value significantly exceeds those of commercial birefringent crystals, such as CaCO3 (0.172 at 546 nm), and is the highest reported value among ultraviolet birefringent crystals. This work presents a novel design strategy that employs halogen bonds as connection sites and modes for birefringent-active units, opening new avenues for developing high-performance birefringent crystals.
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In this study, we present a nanosized biosensor based on the photobiological properties of one-dimensional (1D) topological photonic crystals (PCs). A topological structure had been designed by combining two PC structures (PC 1 and PC 2) comprised of functional material layers, Si and SiO2. These two, PC 1 and PC 2, differ in terms of the thickness and arrangement of these dielectric materials. We carried out a comparison between two distinct topological PCs: one using random PCs, and the other featuring a mirror heterostructure. Tuberculosis may be diagnosed by inserting a sensor layer into 1D topological PCs. The sensing process is based on the refractive indexes of the analytes in the sensor layer. When the 1D-topological heterostructure-based PC and its mirror-image structures are stacked together, the sensor becomes more efficient for analyte detection than the conventional PCs. The random-based topological PC outperformed the heterostructure-based topological PC in analyte sensing. Photonic media witness notable blue shifts due to the analytes' variations in refractive index. The numerical results of the sensor are computed using the transfer matrix approach. Effective results are achieved by optimizing the thicknesses of the sensor layer and dielectric layers; number of periods and incident angle. In normal incident light, the developed sensor shows a high sensitivity of 1500 nm RIU-1with a very low limit of detection in the order of 2.2 × 10-06RIU and a high-quality factor of 30 659.54.
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Intestinal absorption of compounds is significant in drug research and development. To evaluate this efficiently, a method combining mathematical modeling and molecular simulation was proposed, from the perspective of molecular structure. Based on the quantitative structure-property relationship study, the model between molecular structure and their apparent permeability coefficients was successfully constructed and verified, predicting intestinal absorption of drugs and interpreting decisive structural factors, such as AlogP98, Hydrogen bond donor and Ellipsoidal volume. The molecules with strong lipophilicity, less hydrogen bond donors and receptors, and small molecular volume are more easily absorbed. Then, the molecular dynamics simulation and molecular docking were utilized to study the mechanism of differences in intestinal absorption of drugs and investigate the role of molecular structure. Results indicated that molecules with strong lipophilicity and small volume interacted with the membrane at a lower energy and were easier to penetrate the membrane. Likewise, they had weaker interaction with P-glycoprotein and were easier to escape from it and harder to export from the body. More in, less out, is the main reason these molecules absorb well.
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Ligação de Hidrogênio , Absorção Intestinal , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Relação Quantitativa Estrutura-Atividade , Humanos , Estrutura Molecular , Preparações Farmacêuticas/metabolismo , Preparações Farmacêuticas/química , Membro 1 da Subfamília B de Cassetes de Ligação de ATP/metabolismo , Membro 1 da Subfamília B de Cassetes de Ligação de ATP/química , Interações Hidrofóbicas e Hidrofílicas , PermeabilidadeRESUMO
Bioelectricity provides electrostimulation to regulate cell/tissue behaviors and functions. In the human body, bioelectricity can be generated in electromechanically responsive tissues and organs, as well as biomolecular building blocks that exhibit piezoelectricity, with a phenomenon known as the piezoelectric effect. Inspired by natural bio-piezoelectric phenomenon, efforts have been devoted to exploiting high-performance synthetic piezoelectric biomaterials, including molecular materials, polymeric materials, ceramic materials, and composite materials. Notably, piezoelectric biomaterials polarize under mechanical strain and generate electrical potentials, which can be used to fabricate electronic devices. Herein, a review article is proposed to summarize the design and research progress of piezoelectric biomaterials and devices toward bionanotechnology. First, the functions of bioelectricity in regulating human electrophysiological activity from cellular to tissue level are introduced. Next, recent advances as well as structure-property relationship of various natural and synthetic piezoelectric biomaterials are provided in detail. In the following part, the applications of piezoelectric biomaterials in tissue engineering, drug delivery, biosensing, energy harvesting, and catalysis are systematically classified and discussed. Finally, the challenges and future prospects of piezoelectric biomaterials are presented. It is believed that this review will provide inspiration for the design and development of innovative piezoelectric biomaterials in the fields of biomedicine and nanotechnology.
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Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process-structure-property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process-structure-property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.
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Cyclodextrins are macrocyclic rings composed of glucose residues. Due to their remarkable structural properties, they can form host-guest inclusion complexes, which is why they are frequently used in the pharmaceutical, cosmetic, and food industries, as well as in environmental and analytical chemistry. This review presents the reports from 2011 to 2023 on the quantitative structure-activity/property relationship (QSAR/QSPR) approach, which is primarily employed to predict the thermodynamic stability of inclusion complexes. This article extensively discusses the significant developments related to the size of available experimental data, the available sets of descriptors, and the machine learning (ML) algorithms used, such as support vector machines, random forests, artificial neural networks, and gradient boosting. As QSAR/QPR analysis only requires molecular structures of guests and experimental values of stability constants, this approach may be particularly useful for predicting these values for complexes with randomly substituted cyclodextrins, as well as for estimating their dependence on pH. This work proposes solutions on how to effectively use this knowledge, which is especially important for researchers who will deal with this topic in the future. This review also presents other applications of ML in relation to CD complexes, including the prediction of physicochemical properties of CD complexes, the development of analytical methods based on complexation with CDs, and the optimisation of experimental conditions for the preparation of the complexes.
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Asymmetric nitrogen/carbon-coordinated single metal sites (M-NxC4-x) outperform symmetric M-N4 sites in carbon dioxide (CO2) electroreduction. However, the challenge of crafting well-defined M-NxC4-x sites complicates the understanding of their structure-catalytic performance relationship. In this study, we employ metallized N-confused tetraphenylporphyrin (M-NCTPP) to investigate CO2 conversion on M-N3C1 sites using both density functional theory and experimental methods. The optimal cobalt (Co)-N3C1 site (Co-NCTPP) achieves a current density of 500 mA cm-2 and a carbon monoxide Faraday efficiency exceeding 90 % at -1.25 V vs. the reversible hydrogen electrode, surpassing the performance of Co-N4 (Co-TPP). This research introduces a novel approach for designing and synthesizing high-activity heteroatom-anchored single metal sites, advancing fundamental understanding in the field.
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We report the synthesis of LiCoO2 (LCO) cathode materials for lithium-ion batteries via aerosol spray pyrolysis, focusing on the effect of synthesis temperatures from 600 to 1000 °C on the materials' structural and morphological features. Utilizing both nitrate and acetate metal precursors, we conducted a comprehensive analysis of material properties through X-ray diffraction (XRD), Raman spectroscopy, thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). Our findings reveal enhanced crystallinity and significant oxide decomposition within the examined temperature range. Morphologically, nitrate-derived particles exhibited hollow, spherical shapes, whereas acetate-derived particles were irregular. Guided by high-temperature X-ray diffraction (HT-XRD) data, the formation of a layered LCO oxide structure, with distinct spinel Li2Co2O4 and layered oxide LCO phases was shown to emerge at different annealing temperatures. Optimally annealed particles showcased well-defined layered structures, translating to high electrochemical performance. Specifically, nitrate-based particles annealed at 775 °C for 1 h demonstrated initial discharge capacities close to 179 mAh/g, while acetate-based particles, annealed at 750 °C for 3 h, achieved 136 mAh/g at a 0.1C discharge rate. This study elucidates the influence of synthesis conditions on LCO cathode material properties, offering insights that advance high throughput processes for lithium-ion battery materials synthesis.
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Topological indices (TIs) have rich applications in various biological contexts, particularly in therapeutic strategies for cancer. Predicting the performance of compounds in the treatment of cancer is one such application, wherein TIs offer insights into the molecular structures and related properties of compounds. By examining, various compounds exhibit different degree-based TIs, analysts can pinpoint the treatments that are most efficient for specific types of cancer. This paper specifically delves into the topological indices (TIs) implementations in forecasting the biological and physical attributes of innovative compounds utilized in addressing cancer through therapeutic interventions. The analysis being conducted to derivatives of sulfonamides, namely, 4-[(2,4-dichlorophenylsulfonamido)methyl]cyclohexanecarboxylic acid (1), ethyl 4-[(naphthalene-2-sulfonamido)methyl]cyclohexanecarboxylate (2), ethyl 4-[(2,5-dichlorophenylsulfonamido)methyl]cyclohexanecarboxylate (3), 4-[(naphthalene-2-sulfonamido)methyl]cyclohexane-1-carboxylic acid (4) and (2S)-3-methyl-2-(naphthalene-1-sulfonamido)-butanoic acid (5), is performed by utilizing edge partitioning for the computation of degree-based graph descriptors. Subsequently, a linear regression-based model is established to forecast characteristics, like, melting point and formula weight in a quantitative structure-property relationship. The outcomes emphasize the effectiveness or capability of topological indices as a valuable asset for inventing and creating of compounds within the realm of cancer therapy.
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A generic model of elastin-like polypeptides (ELP) is derived that includes proline isomerization (ProI). As a case study, conformational transition of a -[valine-proline-glycine-valine-glycine]- sequence is investigated in aqueous ethanol mixtures. While the non-bonded interactions are based on the Lennard-Jones (LJ) parameters, the effect of ProI is incorporated by tuning the intramolecular 3- and 4-body interactions known from the underlying all-atom simulations into the generic model. One of the key advantages of such a minimalistic model is that it readily decouples the effects of geometry and the monomer-solvent interactions due to the presence of ProI, thus gives a clearer microscopic picture that is otherwise rather nontrivial within the all-atom setups. These results are consistent with the available all-atom and experimental data. The model derived here may pave the way to investigate large scale self-assembly of ELPs or biomimetic polymers in general.
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A large optical anisotropy is the most important parameter of birefringent crystals. Integrating π-conjugated groups with large polarizable anisotropy into target compounds is a common strategy for constructing brilliant birefringent crystals. However, the key problem is to enhance the density of the birefringence-active units and further arrange them parallelly. In this study, three novel birefringent crystals, C9H7NBrX (X = Cl, Br, NO3), are successfully synthesized by introducing a new birefringence-active [C9H7NBr]+ unit. Interestingly, these compounds feature similar layered structures but exhibit different optical anisotropies at 550 nm (0.277 for C9H7NBrCl, 0.328 for C9H7NBrBr, and 0.401 for C9H7NBrNO3) owing to the different anions in them. Particularly, the small trigonal planar NO3 anions perfectly fill the interstices of the π-conjugated [C9H7NBr]+ groups with large optical anisotropy, with the resulting compound C9H7NBrNO3 showing superior optical properties compared to the others. The above findings provide strategies for designing new optical materials with large birefringence by matching birefringence-active groups of different sizes. Additionally, a new theory for predicting and comparing the polarizability anisotropy of compounds is proposed, which would guide in exploring large birefringent crystals.
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This article presents a comprehensive investigation into the functionalization of methoxyphenylazobenzene using electron-directing groups located at the meta position relative to the azo group. Spectroscopic analysis of meta-functionalized azobenzenes reveals that the incorporation of electron-withdrawing units significantly influences the absorption spectra of both E and Z isomers, while electron-donating functionalities lead to more subtle changes. The thermal relaxation process from Z to E result in almost twice as prolonged for electron-withdrawing functionalized azobenzenes compared to their electron-rich counterparts. Computational analysis contributes a theoretical understanding of the electronic structure and properties of meta-substituted azobenzenes. This combined approach, integrating experimental and computational techniques, yields significant insights into the structure-property relationship of meta-substituted asymmetrical phenolazobenzenes.
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Re-arrangement of cationic distribution in partially inverse spinel NiAl2O4 by using chemical pressure perturbation is studied. Structural, impedance and magnetic analysis suggest presence of regions/domains inside the grain/bulk with same lattice arrangement but varying in cationic oxidation state. Perturbing the cationic distribution in the grain via low concentrations of ambivalence substituent rearranges the cationic distribution across these domains within the partially inverse spinel lattice without disturbing the crystal structure. A comprehensive explanation on the origin & tunability of cationic distribution within the partially-inverse lattice is proposed.
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The developments of mixed matrix membranes (MMMs) are severely hindered by the complex inter-phase interaction and the resulting poor utilization of inorganics' microporosity. Herein, a dual porosity framework is constructed in MMMs to enhance the accessibility of inorganics' microporosity to external gas molecules for the effective application of microporosity for gas separation. Nanocomposite organogels are first prepared from the supramolecular complexation of rigid polymers and 2 nm microporous coordination nanocages (CNCs). The network structures can be maintained with microporous features after solvent removal originated from the rigid nature of polymers, and the strong coordination and hydrogen bond between the two components. Moreover, the strong supramolecular attraction reinforces the frustrated packing of the rigid polymers on CNC surface, leading to polymer networks' extrinsic pores and the interconnection of CNCs' micro-cavities for the fast gas transportation. The gas permeabilities of the MMMs are 869 times for H2 and 1099 times for CO2 higher than those of pure polymers. The open metal sites from nanocage also contribute to the enhanced gas selectivity and the overall performance surpasses 2008 H2/CO2 Robeson upper bound. The supramolecular complexation reinforced packing frustration strategy offers a simple and practical solution to achieve improved gas permselectivity in MMMs.
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In biological systems, nucleosides play crucial roles in various physiological processes. In this study, we designed and synthesized four achiral anthracene-based tetracationic nanotubes (1-4) as artificial hosts and chiroptical sensors for nucleosides in aqueous media. Notably, different nanotubes exhibit varied chirality sensing on circular dichroism (CD)/circularly polarized luminescence (CPL) spectra through the host-guest complexation, which prompted us to explore the factors influencing their chiroptical responses. Through systematic host-guest experiments, the structure-chirality sensing relationship between achiral anthracene-based tetracationic nanotubes and nucleosides in the host-guest complexation was unraveled. Firstly, the CD response originates from the anthracene rings situated at the side-wall position, resulting from the right-handed (P)- or left-handed (M)-twisted conformation of the macrocyclic structure. Secondly, the CPL signal is influenced by the presence of anthracene rings at the linking-wall position, which results from intermolecular chiral twisted stacking between these anthracene rings. Therefore, these nanotubes can serve as chiroptical sensor arrays to enhance the accuracy of nucleotide recognition through principal component analysis (PCA) analysis based on the diversified CD spectra. This study provides insights for the construction of adaptive chirality from achiral nanotubes with dynamic conformational nature and might facilitate further design of chiral functional materials for several applications.
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Antracenos , Técnicas Biossensoriais , Dicroísmo Circular , Nanotubos , Nucleosídeos , Antracenos/química , Nanotubos/química , Técnicas Biossensoriais/métodos , Nucleosídeos/química , Água/química , EstereoisomerismoRESUMO
Covalent organic framework (COF) has attracted increasing interest in photocatalytic CO2 reduction, but it remains a challenge to achieve high conversion efficiency owing to the insufficient active site and fast charge recombination. Rationally optimizing the electronic structures of COF to regulate the local charge of active sites precisely is the key point to improving catalytic performance. Herein, intercalated single Co sites coordinated by imine-N motifs have been designed by using trinuclear copper-based imine-COFs with distinct electronic moieties via a molecular engineering strategy. It is confirmed that the charge delivery property and local charge distribution of these heterometallic frameworks can be profoundly influenced by electronic structures. Among these featured structures with mixed-state copper clusters, Co/Cu3-TPA-COF stands out for an exceptional photocatalytic CO2 reduction activity and tunable syngas (CO/H2) ratio by changing various bipyridines. Experimental and theoretical results indicate that interlayer Co-imine N motifs on the donor1-acceptor-donor2 structures facilitate the formation of a highly separated electron-hole state, which effectively induces the oriented electron transfer from dual electron donors to Co centers, achieving an enhanced CO2 activation and reduction. This work opens up an avenue for the design of high-performance COF-based catalysts for photocatalytic CO2 reduction.
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Lignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources. In this context, an increasing demand for high-quality lignin is to be expected. It is, therefore, essential to optimize the technological processes of obtaining it from natural sources, such as biomass. In this work, an investigation of the use of machine learning-based quantitative structure-property relationship (QSPR) modeling for the preliminary processing of lignin recovery from herbaceous biomass using ionic liquids (ILs) is described. Training of the models using experimental data collected from original publications on the topic is assumed, and molecular descriptors of the ionic liquids are used to represent structural information. The study explores the impact of both ILs' chemical structure and process parameters on the efficiency of lignin recovery from different bio sources. The findings give an insight into the extraction process and could serve as a foundation for further design of efficient and selective processes for lignin recovery using ionic liquids, which can have significant implications for producing biofuels, chemicals, and materials.