Faraday Discussions最新文献

Experimental measurements of interactions in ionic liquids and concentrated electrolytes over the past decade or so have revealed simultaneous monotonic and oscillatory decay modes. These observations have been hard to interpret using classical theories, which typically allow for just one electrostatic decay mode in electrolytes. Meanwhile, substantial progress in the theoretical description of dielectric response and ion correlations in electrolytes has illuminated the deep connection between density and charge correlations and the multiplicity of decay modes characterising a liquid electrolyte. The challenge in front of us is to build connections between the theoretical expressions for a pair of correlation functions and the directly measured free energy of interaction between macroscopic surfaces in experiments. Towards this aim, we here present measurements and analysis of the interactions between macroscopic bodies across a fluid mixture of two ionic liquids of widely diverging ionic size. The measured oscillatory interaction forces in the liquid mixtures are significantly more complex than for either of the pure ionic liquids, but can be fitted to a superposition of two oscillatory and one monotonic mode with parameters matching those of the pure liquids. We discuss this empirical finding, which hints at a kind of wave mechanics for interactions in liquid matter.

Ionic liquids (ILs) are an extremely exciting class of electrolytes for energy storage applications. Upon dissolving alkali metal salts, such as Li or Na based salts, with the same anion as the IL, an intrinsically asymmetric electrolyte can be created for use in batteries, known as a salt-in-ionic liquid (SiIL). These SiILs have been well studied in the bulk, where negative transference numbers of the alkali metal cation have been observed from the formation of small, negatively charged clusters. The properties of these SiILs at electrified interfaces, however, have received little to no attention. Here, we develop a theory for the electrical double layer (EDL) of SiILs where we consistently account for the thermoreversible association of ions into Cayley tree aggregates. The theory predicts that the IL cations first populate the EDL at negative voltages, as they are not strongly bound to the anions. However, at large negative voltages, which are strong enough to break the alkali metal cation–anion associations, these IL cations are exchanged for the alkali metal cation because of their higher charge density. At positive voltages, we find that the SiIL actually becomes more aggregated while screening the electrode charge from the formation of large, negatively charged aggregates. Therefore, in contrast to conventional intuition of associations in the EDL, SiILs appear to become more associated in certain electric fields. We present these theoretical predictions to be verified by molecular dynamics simulations and experimental measurements.

For molecules and solids containing heavy elements, accurate electronic-structure calculations require accounting not only for electronic correlations but also for relativistic effects. In molecules, relativity can lead to severe changes in the ground-state description. In solids, the interplay between both correlation and relativity can change the stability of phases or it can lead to an emergence of completely new phases. Traditionally, the simplest illustration of relativistic effects can be done either by including pseudopotentials in non-relativistic calculations or alternatively by employing large all-electron basis sets in relativistic methods. By analyzing different electronic properties (band structure, equilibrium lattice constant and bulk modulus) in semiconductors and insulators, we show that capturing the interplay of relativity and electron correlation can be rather challenging in Green's function methods. For molecular problems with heavy elements, we also observe that similar problems persist. We trace these challenges to three major problems: deficiencies in pseudopotential treatment as applied to Green's function methods, the scarcity of accurate and compact all-electron basis sets that can be converged with respect to the basis-set size, and linear dependencies arising in all-electron basis sets, particularly when employing Gaussian orbitals. Our analysis provides detailed insight into these problems and opens a discussion about potential approaches to mitigate them.

Room-temperature ionic liquids are an exciting group of materials with the potential to revolutionize energy storage. Due to their chemical structure and means of interaction, they are challenging to study computationally. Classical descriptions of their inter- and intra-molecular interactions require time intensive parametrization of force-fields which is prone to assumptions. While ab initio molecular dynamics approaches can capture all necessary interactions, they are too slow to achieve the time and length scales required. In this work, we take a step towards addressing these challenges by applying state-of-the-art machine-learned potentials to the simulation of 1-butyl-3-methylimidazolium tetrafluoroborate. We demonstrate a learning-on-the-fly procedure to train machine-learned potentials from single-point density functional theory calculations before performing production molecular dynamics simulations. Obtained structural and dynamical properties are in good agreement with computational and experimental references. Furthermore, our results show that hybrid machine-learned potentials can contribute to an improved prediction accuracy by mitigating the inherent shortsightedness of the models. Given that room-temperature ionic liquids necessitate long simulations to address their slow dynamics, achieving an optimal balance between accuracy and computational cost becomes imperative. To facilitate further investigation of these materials, we have made our IPSuite-based training and simulation workflow publicly accessible, enabling easy replication or adaptation to similar systems.

Enzymes exhibit diverse conformations, as represented in the free energy landscape (FEL). Such conformational diversity provides enzymes with the ability to evolve towards novel functions. The challenge lies in identifying mutations that enhance specific conformational changes, especially if located in distal sites from the active site cavity. The shortest path map (SPM) method, which we developed to address this challenge, constructs a graph based on the distances and correlated motions of residues observed in nanosecond timescale molecular dynamics (MD) simulations. We recently introduced a template based AlphaFold2 (tAF2) approach coupled with 10 nanosecond MD simulations to quickly estimate the conformational landscape of enzymes and assess how the FEL is shifted after mutation. In this study, we evaluate the potential of SPM when coupled with tAF2-MD in estimating conformational heterogeneity and identifying key conformationally-relevant positions. The selected model system is the beta subunit of tryptophan synthase (TrpB). We compare how the SPM pathways differ when integrating tAF2 with different MD simulation lengths from as short as 10 ns until 50 ns and considering two distinct Amber forcefield and water models (ff14SB/TIP3P versus ff19SB/OPC). The new methodology can more effectively capture the distal mutations found in laboratory evolution, thus showcasing the efficacy of tAF2-MD-SPM in rapidly estimating enzyme dynamics and identifying the key conformationally relevant hotspots for computational enzyme engineering.

Biocatalysis is becoming a powerful and sustainable alternative for asymmetric catalysis. However, enzymes are often restricted to metabolic and less complex reactivities. This can be addressed by protein engineering, such as incorporating new-to-nature functional groups into proteins through the so-called expansion of the genetic code to produce artificial enzymes. Selecting a suitable protein scaffold is a challenging task that plays a key role in designing artificial enzymes. In this work, we explored different protein scaffolds for an abiological model of iminium-ion catalysis, Michael addition of nitromethane into E-cinnamaldehyde. We studied scaffolds looking for open hydrophobic pockets and enzymes with described binding sites for the targeted substrate. The proteins were expressed and variants harboring functional amine groups – lysine, p-aminophenylalanine, or N⁶-(D-prolyl)-L-lysine – were analyzed for the model reaction. Among the newly identified scaffolds, a thermophilic ene-reductase from Thermoanaerobacter pseudethanolicus was shown to be the most promising biomolecular scaffold for this reaction.

The effective management of plastic waste has become a global imperative, given our reliance on a linear model in which plastics are manufactured, used once, and then discarded. This has led to the pervasive accumulation of plastic debris in landfills and environmental contamination. Recognizing this issue, numerous initiatives are underway to address the environmental repercussions associated with plastic disposal. In this study, we investigate the possible molecular mechanism of polyurethane esterase A (PueA), which has been previously identified as responsible for the degradation of a polyester polyurethane (PU) sample in Pseudomonas chlororaphis, as an effort to develop enzymatic biodegradation solutions. After generating the unsolved 3D structure of the protein by AlphaFold2 from its known genome, the enzymatic hydrolysis of the same model PU compound previously used in experiments has been explored employing QM/MM molecular dynamics simulations. This required a preliminary analysis of the 3D structure of the apo-enzyme, identifying the putative active site, and the search for the optimal protein–substrate binding site. Finally, the resulting free energy landscape indicates that wild-type PueA can degrade PU chains, although with low-level activity. The reaction takes place by a characteristic four-step path of the serine hydrolases, involving an acylation followed by a diacylation step. Energetics and structural analysis of the evolution of the active site along the reaction suggests that PueA can be considered a promising protein scaffold for further development to achieve efficient biodegradation of PU.

The large melting point depressions characterising deep eutectic solvents (DESs) are related to negative deviations from ideal mixing behaviour characterised by the excess Gibbs energy. Favourable excess Gibbs energies result from a balance between the excess entropy and enthalpy of mixing, which was experimentally determined for three choline chloride (ChCl) based mixtures using calorimetry. While the excess Gibbs energy of H₂O + ChCl is enthalpy dominated, those of ethylene glycol (EG) + ChCl and 1,3-propanediol + ChCl are entropy dominated. Molecular dynamics simulations using polarisable force-fields show intermolecular hydrogen bonds between DES constituents for H₂O + ChCl and EG + ChCl. Hence, inter-species hydrogen bonding does not guarantee enthalpy-dominated melting point depressions. We suggest future research to focus on tuning the entropy–enthalpy balance via the chemical nature of the DES constituents.

Deep eutectic solvents (DES) are mixtures of hydrogen bond donors and acceptors that form strongly hydrogen-bonded room temperature liquids. Changing the H-bonding components and their ratios can alter the physicochemical properties of deep eutectic solvents. Recent studies have shown p-toluenesulfonic acid (pTSA) forms room temperature liquids with choline chloride (ChCl) at different molar ratios: 1 : 1, 1 : 2 and 2 : 1 [Rodriguez Rodriguez et al., ACS Sustain. Chem. Eng., 2019, 7(4), 3940]. They also showed that the composition affects the physical properties of these liquids and their ability to dissolve metal oxides. In this work we evaluate the solubility and self-assembly of cationic surfactants alkyltrimethyl ammonium bromides (CnTAB) in these pTSA/ChCl based liquids. CnTABs are insoluble in 1pTSA : 2ChCl, whereas in 1pTSA : 1ChCl and 2pTSA : 1ChCl they form micelles. We characterise CnTAB (n = 12, 14, 16) micelles using small angle neutron scattering and also look at interaction of water with the micelles. These studies help determine the interaction of DES components with the surfactant and the influence of varying pTSA and water ratios on these interactions. This provides potential for controlled surfactant templating and for tuning rheology modification in such systems.

Water-in-salt (WiS) electrolytes are promising systems for a variety of energy storage devices. Indeed, they represent a great alternative to conventional organic electrolytes thanks to their environmental friendliness, non-flammability, and good electrochemical stability. Understanding the behaviour of such systems and their local organisation is a key direction for their rational design and successful implementation at the industrial scale. In the present paper, we focus our investigation on the 21 m bis(trifluoromethanesulfonyl)imide (LiTFSI) WiS electrolyte, recently reported to have acidic pH values. We explore the speciation of an excess proton in this system and its dependence on the initial local environment using ab initio molecular dynamics simulations. In particular, we observe the formation of HTFSI acid in the WiS system, known to act as a superacid in water. This acid is stabilised in the WiS solution for several picoseconds thanks to the formation of a complex with water molecules and a neighboring TFSI⁻ anion. We further investigate how the excess proton affects the microstructure of WiS, in particular, the recently observed oligomerisation of lithium cations, and we report possible notable perturbations of the lithium nanochain organisation. These two phenomena are particularly important when considering WiS as electrolytes in batteries and supercapacitors, and our results contribute to the comprehension of these systems at the molecular level.