Functional Material Systems Enabled by Automated Data Extraction and Machine Learning

The development of new functional materials is crucial for addressing global challenges such as clean energy or the discovery of new drugs and antibiotics. Functional material systems are typically composed of functional molecular building blocks, organized across multiple length scales in a hierarchical order. The large design space allows for precise tuning of properties to specific applications, but also makes it time-consuming and expensive to screen for optimal structures using traditional experimental methods. Machine learning (ML) models can potentially revolutionize the field of materials science by predicting chemical syntheses and materials properties with high accuracy. However, ML models require data to be trained and validated. Methods to automatically extract data from scientific literature make it possible to build large and diverse datasets for ML models. In this article, opportunities and challenges of data extraction and machine learning methods are discussed to accelerate the discovery of high-performing functional material systems, while ensuring that the predicted materials are stable, synthesizable, scalable, and sustainable. The potential impact of large language models (LLMs) on the data extraction process are discussed. Additionally, the importance of research data management tools is discussed to overcome the intrinsic limitations of data extraction approaches

Potassium carbonate-based ternary transition temperature mixture (deep eutectic analogues) for CO2 absorption: characterizations and DFT analysis

Is it possible to improve CO2 solubility in potassium carbonate (K2CO3)-based transition temperature mixtures (TTMs)? To assess this possibility, a ternary transition-temperature mixture (TTTM) was prepared by using a hindered amine, 2-amino-2-methyl-1,3-propanediol (AMPD). Fourier transform infrared spectroscopy (FT-IR) was employed to detect the functional groups including hydroxyl, amine, carbonate ion, and aliphatic functional groups in the prepared solvents. From thermogravimetric analysis (TGA), it was found that the addition of AMPD to the binary mixture can increase the thermal stability of TTTM. The viscosity findings showed that TTTM has a higher viscosity than TTM while their difference was decreased by increasing temperature. In addition, Eyring’s absolute rate theory was used to compute the activation parameters (∆G*, ∆H*, and ∆S*). The CO2 solubility in liquids was measured at a temperature of 303.15 K and pressures up to 1.8 MPa. The results disclosed that the CO2 solubility of TTTM was improved by the addition of AMPD. At the pressure of about 1.8 MPa, the CO2 mole fractions of TTM and TTTM were 0.1697 and 0.2022, respectively. To confirm the experimental data, density functional theory (DFT) was employed. From the DFT analysis, it was found that the TTTM + CO2 system has higher interaction energy (|∆E|) than the TTM + CO2 system indicating the higher CO2 affinity of the former system. This study might help scientists to better understand and to improve CO2 solubility in these types of solvents by choosing a suitable amine as HBD and finding the best combination of HBA and HBD

Deep Eutectic Solvents for Pretreatment, Extraction, and Catalysis of Biomass and Food Waste

Valorization of lignocellulosic biomass and food residues to obtain valuable chemicals is essential to the establishment of a sustainable and biobased economy in the modern world. The latest and greenest generation of ionic liquids (ILs) are deep eutectic solvents (DESs) and natural deep eutectic solvents (NADESs); these have shown great promise for various applications and have attracted considerable attention from researchers who seek versatile solvents with pretreatment, extraction, and catalysis capabilities in biomass- and biowaste-to-bioenergy conversion processes. The present work aimed to review the use of DESs and NADESs in the valorization of biomass and biowaste as pretreatment or extraction solvents or catalysis agents

Deep Eutectic Solvents as Catalysts for Upgrading Biomass

Deep eutectic solvents (DESs) have emerged as promising green solvents, due to their versatility and properties such as high biodegradability, inexpensiveness, ease of preparation and negligible vapor pressure. Thus, DESs have been used as sustainable media and green catalysts in many chemical processes. On the other hand, lignocellulosic biomass as an abundant source of renewable carbon has received ample interest for the production of biobased chemicals. In this review, the state of the art of the catalytic use of DESs in upgrading the biomass-related substances towards biofuels and value-added chemicals is presented, and the gap in the knowledge is indicated to direct the future research

Deep Eutectic Solvents as Catalysts for Upgrading Biomass

Deep eutectic solvents (DESs) have emerged as promising green solvents, due to their versatility and properties such as high biodegradability, inexpensiveness, ease of preparation and negligible vapor pressure. Thus, DESs have been used as sustainable media and green catalysts in many chemical processes. On the other hand, lignocellulosic biomass as an abundant source of renewable carbon has received ample interest for the production of biobased chemicals. In this review, the state of the art of the catalytic use of DESs in upgrading the biomass-related substances towards biofuels and value-added chemicals is presented, and the gap in the knowledge is indicated to direct the future research

A General Picture of Cucurbit[8]uril Host-Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamical feature of host-guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has intermediate portal size and cavity volume. It can exploit almost all host-guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of 7 commonly abused and structurally diverse drugs to the CB8 host was performed and a general dynamical binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted to improve the intra-molecular conformational preference and thus the description of inter-molecular host-guest interactions. The interaction pattern and binding thermodynamics show significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host-guest binding

A General Picture of Cucurbit[8]uril Host–Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamic feature of host–guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has an intermediate portal size and cavity volume. It can exploit almost all host–guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of seven commonly abused and structurally diverse drugs to the CB8 host was performed, and a general dynamic binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted with generalized force-matching to improve the intra-molecular conformational preference, and thus the description of inter-molecular host–guest interactions. The interaction pattern and binding thermodynamics show a significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host–guest binding

Molecular Modelling of Ionic Liquids: General Guidelines on Fixed-Charge Force Fields for Balanced Descriptions

It has been increasingly common to investigate dynamic and thermodynamic properties of green solvents at atomistic scales with molecular simulation. These designed solvents such as ionic liquids are often highly charged species, which pose a problem for molecular modelling with classical fixed-charge force fields. Simulation outcomes with atomic charges derived from ab initio calculations often show significant deviations from the experimental reference, and charge scaling is widely applied as a simple yet efficient solution to achieve satisfactory experiment-simulation accordance. Although the massive emphasis on the reproduction of bulk properties such as density of the liquids as charge scaling criteria, a more crucial thermodynamic observable is the solvation behavior of external agents in these green solvents. Astonishingly, our recent large-scale benchmark calculation on solvation thermodynamics suggests that the solvation-free-energy-derived scaling factor is generally slightly larger (~0.1) than the bulk-property-derived estimate. This phenomenon is rather not unexpected, as the density-matching estimate only considers the solvent-solvent interaction (overfitting), while accurate calculations of solvation free energies require balanced descriptions of solute-solvent and solvent-solvent interactions. A more interesting observation is that different solute-solvent pairs exhibit different responses to the variation of the scaling parameter, which arises from the competing electrostatic and vdW contributions. Another perspective provided in our previous extensive benchmark is about the suitability of general-purpose force fields for bonded and vdW interactions in the modelling of ionic liquids. The bond stretching and angle bending terms in pre-fitted GAFF derivatives are often problematic, while the torsional potential shows satisfactory reproduction of ab initio results. In the current work, we expect to accumulate more experiences from large-scale fast-growth solvation free energy simulations in ionic liquids with compositions different from our previous benchmark. The obtained new results are combined with our previous dataset to form a large solvation set (and also partition or water-ionic-liquids transfer set), from which a universally applicable charge scaling factor with at least half-optimal performance is derived. Aside from the force-field issue, another extremely important modelling detail considered in the current work is the finite-size effect. It is observed that the finite-size artifacts in solvation thermodynamics are much more severe than mass density, which emphasizes the use of a sufficiently large ionic solvent box in molecular simulations of ionic liquids derivatives. Finally, combining the extensive computational perspectives accumulated in our series works, general guidelines for molecular modelling of ionic liquids with fixed-charge force fields are summarized