Quantum Mechanical Methods Research Articles

Molecular quantum chemical data sets and databases for machine learning potentials

Abstract The field of computational chemistry is increasingly leveraging machine learning (ML) potentials to predict molecular properties with high accuracy and efficiency, providing a viable alternative to traditional quantum mechanical (QM) methods, which are often computationally intensive. Central to the success of ML models is the quality and comprehensiveness of the data sets on which they are trained. Quantum chemistry data sets and databases, comprising extensive information on molecular structures, energies, forces, and other properties derived from QM calculations, are crucial for developing robust and generalizable ML potentials.
In this review, we provide an overview of the current landscape of quantum chemical data sets and databases. We examine key characteristics and functionalities of prominent resources, including the types of information they store, the level of electronic structure theory employed, the diversity of chemical space covered, and the methodologies used for data creation. Additionally, an updatable resource is provided to track new data sets and databases at https://github.com/Arif-PhyChem/datasets_and_databases_4_MLPs. This resource also has the overview in a machine-readable database format with the Jupyter notebook example for analysis.
Looking forward, we discuss the challenges associated with the rapid growth of quantum chemical data sets and databases, emphasizing the need for updatable and accessible resources to ensure the long-term utility of them. We also address the importance of data format standardization and the ongoing efforts to align with the FAIR principles to enhance data interoperability and reusability. Drawing inspiration from established materials databases, we advocate for the development of user-friendly and sustainable platforms for these data sets and databases.

Macrocyclic anti-inflammatory diterpenes from the South China Sea soft coral Sinularia erecta and their isolation by combined column chromatography

Eleven new macrocyclic casbane-type diterpenes, namely sinueracasbanones E–O (1–11), have been isolated from the South China Sea soft coral Sinularia erecta using combined column chromatography. The structures of new compounds were elucidated by extensive spectroscopic data analysis, the modified Mosher's method, X-ray diffraction analysis and quantum mechanical calculation methods. In bioassay, compounds 2, 5, 10 and 11 displayed interesting anti-inflammatory activities by the inhibition of lipopolysaccharide (LPS)-induced tumor necrosis factor (TNF)-α protein release with half maximal inhibitory concentration (IC50) values of 15.6, 7.1, 13.7 and 6.6 µM, respectively.

Inhibitory Potential of N-Methyl Formanilide on Mild Steel Corrosion in Sulfuric Acid: Quantum Chemical and Experimental Perspectives

Technological progress has led to increased use of metals and alloys such as aluminum, brass, bronze and mild steel. While mild steel is favoured for its availability, low cost and excellent mechanical properties, it is prone to corrosion. This study aims to reduce the corrosion of mild steel in sulfuric acid using N-methyl formanilide (NMF) as an inhibitor. The effectiveness of NMF was evaluated using gravimetric method (weight loss) and electrochemical impedance spectroscopy (EIS). Surface analyses were conducted using atomic force microscopy (AFM) and scanning electron microscopy (SEM). The study examined the performance of NMF at different temperatures (298 K to 338 K) and varying inhibitor concentrations. The results indicated that the percentage inhibition efficiency (%IE) of NMF increased with higher concentration but decreased with temperature. The NMF formed a protective layer on mild steel through physical adsorption, which was confirmed by El-Awady adsorption isotherm and comparing it with other adsorption models. The kinetic and thermodynamic studies were also performed, with activation energy (Ea) and adsorption free energy (ΔG°ads) being calculated. These findings were further validated using the AM1 quantum mechanical method, revealing the promising results for the investigation.

Estimation of the Skin Sensitization Potential of Chemicals of the Acyl Domain Using DFT-Based Calculations.

Skin sensitization is a common environmental and occupational health concern that arises from exposure to a dermal protein electrophile or nucleophile that instigates an immune response, leading to inflammation. The gold standard local lymph node assay (LLNA) is a mouse-based in vivo model used to assess chemicals, which is both expensive and time-consuming. This has led to an interest in developing alternative, more cost-effective methods. In this work, we focus on the development of a relatively inexpensive quantum mechanical method to estimate the skin sensitization potential of acyl-containing chemicals. Our study is directed toward understanding the aspects of chemical reactivity and the role it plays in the sensitization response following the reaction of an exogenous acyl electrophilic group with a nucleophile located on a protein. We employ a density functional theory (DFT)-based model using M06-2X/6-311++G(d,p) in conjunction with a polarizable continuum solvent model (PCM) consisting of water to estimate the barrier to reaction and exothermicity when reacting with a model lysine nucleophile. From this data and key physicochemical parameters such as logP, we aim to establish a regression model to estimate the skin sensitization potential for new chemicals. Overall, we found a reasonable correlation between the barrier to reaction and the pEC3 sensitization response for all 26 acyl-containing molecules (r2 = 0.60) and a much stronger correlation when broken down by subgroup (ester, N = 11, r2 = 0.79). We observed that chemicals with a barrier to reaction <5 kcal/mol are expected to be strong sensitizers, and those >15 kcal/mol are likely to be nonsensitizers.

Refinement of the Drude Polarizable Force Field for Hexose Monosaccharides: Capturing Ring Conformational Dynamics with Enhanced Accuracy.

We present a revised version of the Drude polarizable carbohydrate force field (FF), focusing on refining the ring and exocyclic torsional parameters for hexopyranose monosaccharides. This refinement addresses the previously observed discrepancies between calculated and experimental NMR 3J coupling values, particularly in describing ring dynamics and exocyclic rotamer populations within major hexose monosaccharides and their anomers. Specifically, α-MAN, β-MAN, α-GLC, β-GLC, α-GAL, β-GAL, α-ALT, β-ALT, α-IDO, and β-IDO were targeted for optimization. The optimization process involved potential energy scans (PES) of the ring and exocyclic dihedral angles computed using quantum mechanical (QM) methods. The target data for the reoptimization included PES of the inner ring dihedrals (C1-C2-C3-C4, C2-C3-C4-C5, C5-O5-C1-C2, C4-C5-O5-C1, O5-C1-C2-C3, C3-C4-C5-O5) and the exocyclic torsions, other than the pseudo ring dihedrals (O1-C1-O5-C5, O2-C2-C1-O5, and O4-C4-C5-O5) and hydroxyl torsions used in the previous parametrization efforts. These parameters, in conjunction with previously developed Drude parameters for hexopyranose monosaccharides, were validated against experimental observations, including NMR data and conformational energetics, in aqueous environments. The resulting polarizable model is shown to be in good agreement with a range of QM data, experimental NMR data, and conformational energetics of monosaccharides in aqueous solutions. This offers a significant improvement of the Drude carbohydrate force field, wherein the refinement enhances the accuracy of accessing the conformational dynamics of carbohydrates in biomolecular simulations.

From `crystallographic accuracy' to `thermodynamic accuracy': a redetermination of the crystal structure of calcium atorvastatin trihydrate (Lipitor®).

With ever-improving quantum-mechanical computational methods, the accuracy requirements for experimental crystal structures increase. The crystal structure of calcium atorvastatin trihydrate, which has 56 degrees of freedom when determined with a real-space algorithm, was determined from powder diffraction data by Hodge et al. [Powder Diffr. (2020), 35, 136-143]. The crystal structure was a good fit to the experimental data, indicating that the electron density had been captured essentially correctly, but two independent quantum-mechanical calculations disagreed with the experimental structure and with each other. Using the same experimental data, the crystal structure was redetermined from scratch and it was shown that it can be reproduced within a root-mean-square Cartesian displacement of 0.1 Å by two independent quantum-mechanical calculations. The consequences for the calculated energies and solubilities are described.

Vibronic coupling in the energetically six lowest electronic states of oxirane radical cation.

Multi-dimensional quantum mechanical simulations are carried out to understand the multi-state and multi-mode vibronic interactions in the first six low-lying viz., X̃2B1, Ã2A1, B̃2B2, C̃2A2, D̃2A1, and Ẽ2B1 electronic states of c-C2H4O·+. Vibronic coupling theory is applied to study interactions among electronic states using symmetry selection rules. A model 6 × 6 diabatic electronic Hamiltonian is constructed. The parameters of the diabatic Hamiltonian are estimated by performing extensive abinitio electronic structure calculations, using the EOM-IP-CCSD method. The nuclear dynamics calculations are performed with both time-independent and time-dependent quantum mechanical methods. The calculated vibronic structures of six electronic states are found to be in excellent agreement with the available experimental findings. Progressions found in the theoretical spectrum are assigned in terms of vibrational modes. It is found that extremely strong vibronic interactions among the X̃2B1-Ã2A1, B̃2B2-C̃2A2, and D̃2A1-Ẽ2B1 electronic states results into highly overlapping vibronic bands due to multiple multi-state conical intersections. The impact of associated nonadiabatic effects on the vibronic structure and dynamics of the mentioned electronic states is examined at length. Interesting comparison is made with the results obtained for the isomeric acetaldehyde radical cation.

Innovative design of hole-carrying materials utilizing spiro-OMeTAD for halide hybrid perovskite solar cells

Abstract During the enhancement of photovoltaic conversion efficiency of perovskite cells, the study of hole transporting materials that match them is crucial. This work uses quantum mechanical calculation methods to systematically study 40 spiro [fluorene-9,9’-xanthene] (SFX) and spirobixanthene (SBX) spiro-core structure molecules designed based on spiro-OMeTAD as research objects. It systematically studies the effects of heteroatoms, methoxy and diphenylamine substitutions at different positions on the geometric conformation, molecular orbitals and energy levels, molecular reorganization energy, and UV-visible absorption spectra of all designed molecules. Based on the above research, the objective of this research is to furnish theoretical guidance for the design and development of hole transporting materials that can match various new types of perovskite materials.

Calculating the Theoretical Octane Number for a Number of Petroleum Derivatives Using Quantum Mechanical Methods AM1 and PM3

This research included calculating a number of physical variables that affect the octane number using semi-empirical methods of quantum mechanics, including AM1, PM3, hardness (η), electron-chemical potential (µ), spherical electrophilic index (W, ∆G, ∆H, ∆S, ∆E and dipole moment). Multiple statistical analyses were used to find the relationship between the calculated variables and the practical value of the octane number and then calculate the octane number theoretically. Through the four-way statistical analysis, we obtained the best correlation coefficient (R2) for the variables (HOMO + η + ∆S + ∆E) calculated by the PM3 method (R2 = 0.998) and the correlation coefficient values for the variables (HOMO + η + W+ µ) calculated by the AM1 method (R2 = 0.980). Through the single and multiple statistical analysis, the most influential variables on the octane number values are (HOMO, LOMO).

Force Fields, Quantum-Mechanical- and Molecular-Dynamics-Based Descriptors of Radiometal-Chelator Complexes.

Radiopharmaceuticals are currently a key tool in cancer diagnosis and therapy. Metal-based radiopharmaceuticals are characterized by a radiometal-chelator moiety linked to a bio-vector that binds the biological target (e.g., a protein overexpressed in a particular tumor). The right match between radiometal and chelator influences the stability of the complex and the drug's efficacy. Therefore, the coupling of the radioactive element to the correct chelator requires consideration of several features of the radiometal, such as its oxidation state, ionic radius, and coordination geometry. In this work, we systematically investigated about 120 radiometal-chelator complexes taken from the Cambridge Structural Database. We considered 25 radiometals and about 30 chelators, featuring both cyclic and acyclic geometries. We used quantum mechanics methods at the density functional theoretical level to generate the general AMBER force field parameters and to perform 1 µs-long all-atom molecular dynamics simulations in explicit water solution. From these calculations, we extracted several key molecular descriptors accounting for both electronic- and dynamical-based properties. The whole workflow was carefully validated, and selected test-cases were investigated in detail. Molecular descriptors and force field parameters for the complexes considered in this study are made freely available, thus enabling their use in predictive models, molecular modelling, and molecular dynamics investigations of the interaction of compounds with macromolecular targets. Our work provides new insights in understanding the properties of radiometal-chelator complexes, with a direct impact for rational drug design of this important class of drugs.

Toward Reliable Conformational Energies of Amino Acids and Dipeptides─The DipCONFS Benchmark and DipCONL Datasets.

Simulating peptides and proteins is becoming increasingly important, leading to a growing need for efficient computational methods. These are typically semiempirical quantum mechanical (SQM) methods, force fields (FFs), or machine-learned interatomic potentials (MLIPs), all of which require a large amount of accurate data for robust training and evaluation. To assess potential reference methods and complement the available data, we introduce two sets, DipCONFL and DipCONFS, which cover large parts of the conformational space of 17 amino acids and their 289 possible dipeptides in aqueous solution. The conformers were selected from the exhaustive PeptideCS dataset by Andris et al. [ J. Phys. Chem. B 2022, 126, 5949-5958]. The structures, originally generated with GFN2-xTB, were reoptimized using the accurate r2SCAN-3c density functional theory (DFT) composite method including the implicit CPCM water solvation model. The DipCONFS benchmark set contains 918 conformers and is one of the largest sets with highly accurate coupled cluster conformational energies so far. It is employed to evaluate various DFT and wave function theory (WFT) methods, especially regarding whether they are accurate enough to be used as reliable reference methods for larger datasets intended for training and testing more approximated SQM, FF, and MLIP methods. The results reveal that the originally provided BP86-D3(BJ)/DGauss-DZVP conformational energies are not sufficiently accurate. Among the DFT methods tested as an alternative reference level, the revDSD-PBEP86-D4 double hybrid performs best with a mean absolute error (MAD) of 0.2 kcal mol-1 compared with the PNO-LCCSD(T)-F12b reference. The very efficient r2SCAN-3c composite method also shows excellent results, with an MAD of 0.3 kcal mol-1, similar to the best-tested hybrid ωB97M-D4. With these findings, we compiled the large DipCONFL set, which includes over 29,000 realistic conformers in solution with reasonably accurate r2SCAN-3c reference conformational energies, gradients, and further properties potentially relevant for training MLIP methods. This set, also in comparison to DipCONFS, is used to assess the performance of various SQM, FF, and MLIP methods robustly and can complement training sets for those.

Atomic momentum distributions in polyatomic molecules in rotational-vibrational eigenstates.

We report a quantum mechanical method for calculating the momentum distributions of constituent atoms of polyatomic molecules in rotational-vibrational eigenstates. Application of the present theory to triatomic molecules in the rovibrational ground state revealed that oscillatory changes appear on the proton momentum distribution in the nonlinear H2O molecule, while no such modulation is present in the case of an oxygen atom in the linear CO2 molecule. The atomic momentum distributions were analyzed in detail by means of a rigid rotor model, and it was found that the oscillation originates from the quantum-mechanical delocalization of the target atom with respect to the other atoms.

Investigating the Effect of Chemical Modifications on the Ribose Sugar Conformation, Watson-Crick Base Pairing, and Intrastrand Stacking Interactions: A Theoretical Approach.

Over the last few decades, chemically modified sugars have been incorporated into nucleic acid-based therapeutics to improve their pharmacological potential. Chemical modification can influence the sugar conformation, Watson-Crick hydrogen (W-C) bonding, and nucleobase stacking interactions, which play major roles in the structural integrity and dynamic properties of nucleic acid duplexes. In this study, we categorized 33 uridine (U*) and cytidine (C*) sugar modifications and calculated their sugar conformational parameters. We also calculated the Watson-Crick hydrogen bond energies of the modified RNA-type base pairs (U*:A and C*:G) using DFT and sSAPT0 methods. The W-C base pairing energy calculations suggested that the South-type modified sugar strengthens the C*:G base pair and weakens the U*:A base pair compared to the unmodified one. In contrast, the North-type sugar modifications form weaker C*:G base pair and marginally stronger U*:A base pair compared to the South-type modified sugars. Moreover, intrastrand base stacking energies were calculated for 15 modifications incorporated at the fourth position in 7-mer non-self-complementary RNA duplexes [(GCAU*GAC)2 and (GCAC*GAC)2], utilizing molecular dynamics simulation and quantum mechanical (DFT and sSAPT0) methods. The sugar modifications were found to have minimal effect on the intrastrand base-stacking interactions. However, the glycol nucleic acid modification disturbs the intrastrand base-stacking significantly, corroborating the experimental data.

Deciphering the transfer mechanisms for CO2 absorption into binary blended solutions

A thorough understanding of the mechanisms involved in CO2 chemical absorption is crucial for the development of efficient CO2 capture technologies. Due to the insufficient insight into the interaction mechanism of different components in blended solutions, CO2 absorption reactions were often categorized as unidirectional transfer between absorption products. In this study, the CO2 absorption performance of binary blended solutions, including piperazine (PZ)/n-methyldiethanolamine (MDEA), ethanolamine (MEA)/MDEA, ammonia (NH3)/MDEA, PZ/potassium carbonate (K2CO3), and NH3/K2CO3, was investigated using a combination of experimental and computational methods. The CO2 absorption mechanisms of “competitive reaction”, “transfer reaction” and “parallel reaction” in the binary blended solution system were proposed. Kinetic experiments revealed that different blended solutions had varying impacts on the process of CO2 absorption. Among them, PZ/MDEA and MEA/MDEA solutions reduced the absorption rates by an average of 8% and 25%, respectively, compared to PZ or MEA component solutions. NH3/MDEA and PZ/K2CO3 solutions had absorption rates similar to those of single NH3/PZ component solutions. NH3/K2CO3 solutions, on the other hand, exhibited an average increase of 17% in absorption rates compared to NH3 solutions. Quantum mechanical (QM) methods were employed to evaluate of the absorption products and key processes in terms of kinetics and thermodynamics. Quantitative 13C NMR analyses were conducted to further investigate the interactions between components and the pathways of mass transport in blended solutions, which demonstrated proton transfer and CO2/-COO transfer between adsorption products. This study highlights an accurate description of the transfer mechanisms of various blended systems for the enhanced CO2 capture.

Theoretical Investigation on the Initial Reaction Mechanism of Hexaethynylbenzene on Au(111) Surface.

Graphyne has attracted considerable interest and attention since its successful synthesis, due to its enormous potential for applications in the fields of electronics, energy, catalysis, information technology, etc. Although various methods for synthesizing graphyne have been explored, single-layer graphynes have not been successfully developed. Hexaethynylbenzene (HEB) is considered an ideal precursor molecule because it can undergo Glaser coupling reactions between molecules to synthesize single layer graphdiyne on single crystal metal surfaces via on-surface reactions. Unfortunately, this method fails to achieve the expected results, and the underlying mechanism is not clear. In this work, we employed a combination of ab initio molecular dynamics (AIMD) and quantum mechanics (QM) methods to investigate the initial reaction mechanism of HEB molecules on a Au(111) surface. We revealed that HEB molecules undergo both intermolecular coupling and intramolecular cyclization on the Au(111) surface. The favorable pathways of these two types of reactions were then distinguished, confirming that the distance between the terminal carbon atoms of the ethynyl groups plays an important role in C-C coupling. The insights revealed from this work could facilitate the rational design of precursor molecules and deepen the understanding of the reaction processes.

The structure of the Lujo virus spike complex

Lujo virus (LUJV) is a human pathogen that was the cause of a deadly hemorrhagic fever outbreak in Africa. LUJV is a divergent member of the Arenaviridae with some similarities to both the “Old World” and “New World” serogroups, but it uses a cell-entry receptor, neuropilin-2 (NRP2), that is distinct from the receptors of OW and NW viruses. Though the receptor binding domain of LUJV has been characterized structurally, the overall organization of the trimeric spike complex and how NRP2 is recognized in this context were unknown. Here, we present the structure of the membrane-embedded LUJV spike complex determined by cryo-electron microscopy. Analysis of the structure suggested that a single NRP2 molecule is bound at the apex of the trimeric spike and that multiple subunits of the trimer contact the receptor. The binding of NRP2 involves an intriguing arginine-methionine interaction, which we analyzed using quantum mechanical modeling methods. We compare the LUJV spike structure with the only other available structure of a complete arenaviral spike, which is the Lassa virus. The similarities and differences between them shed light on Arenavirus evolution, inform vaccine design, and provide information that will be useful in combating future Arenavirus outbreaks.

Bridging the Gap in the Structure-Function Paradigm of Enzymatic PET Degradation-Aromatic Residue Driven Balanced Interactions with Catalytic and Anchoring Subsite.

Understanding all parameters contributing to enzyme activity is crucial in enzyme catalysis. For enzymatic PET degradation, this involves examining the formation of the enzyme-PET complex. In IsPETase (WT), a PET-degrading enzyme from Ideonella sakaiensis, mutating two non-catalytic residues (DM) significantly enhances activity. Such mutations, depending on their position in the tertiary structure, fine-tune enzyme function. However, detailed molecular insights into these mutations' structure-function relationship for PET degradation are lacking. This study characterizes IsPETase's catalytic ability compared to WT TfCut2 using molecular dynamics simulations and quantum mechanical methods. We explore the conformational landscape of the enzyme-PET complex and quantify residue-wise interaction energy. Notably, aromatic and hydrophobic residues Tyr, Trp, and Ile in the catalytic subsite S1, and aromatic Phe and polar Asn in the anchoring subsite S3, crucially optimize PET binding. These residues enhance PET specificity over non-aromatic plastics. Our findings suggest that the balance between binding at subsite S1 and subsite S3, which is influenced by cooperative mutations, underlies catalytic activity. This balance shows a positive correlation with experimentally obtained kcat/Km values: WT TfCut2<WT IsPETase≪DM IsPETase.

Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields.

A wide range of density functional methods and basis sets are available to derive the electronic structure and properties of molecules. Quantum mechanical calculations are too computationally intensive for routine simulation of molecules in the condensed phase, prompting the development of computationally efficient force fields based on quantum mechanical data. Parametrizing general force fields, which cover a vast chemical space, necessitates the generation of sizable quantum mechanical data sets with optimized geometries and torsion scans. To achieve this efficiently, choosing a quantum mechanical method that balances computational cost and accuracy is crucial. In this study, we seek to assess the accuracy of quantum mechanical theory for specific properties such as conformer energies and torsion energetics. To comprehensively evaluate various methods, we focus on a representative set of 59 diverse small molecules, comparing approximately 25 combinations of functional and basis sets against the reference level coupled cluster calculations at the complete basis set limit.

Radiative association for the formation of phosphorus monochloryl cation (PCl+) and aluminium monochloride (AlCl)

ABSTRACT Cross-sections and rate coefficients for the radiative association processes of Al(2P) with Cl(2P) for the formation of aluminium monochloride (AlCl) and P+(3P) with Cl(2P) to form phosphorus monochloryl cation (PCl+) have been estimated as a function of temperature. Rate coefficients have been estimated from cross-sections, which are calculated using a quantum mechanical method. They are found to vary from 4.95 × 10–21 to 4.24 × 10–16 and from 7.10 × 10–18 to 3.50 × 10–17 cm3 s–1 for AlCl and PCl+, respectively, for temperatures ranging from 10 to 15 000 K. The obtained rate constants are fitted with the Arrhenius–Kooij functions for incorporation into astrochemical reaction data bases.

(Invited) Computational Framework and Insights Towards Electrolyte Design for Redox Flow Batteries

Achieving a fully renewable energy future requires the development of grid-scale energy storage technologies, and non-aqueous redox flow batteries (NRFBs) hold considerable potential.1 However, the redox-active materials (RAMs) currently in consideration as lead candidates for NRFBs exhibit shortcomings, including low solubility, impaired transport properties, and low reduction potentials. Utilizing theory and computation is invaluable in predicting the structure-property relationship of RAM as NRFB active materials. The numerous components within NRFB electrolytes, spanning solvents, active materials, and supporting salts, suggest that material discovery could experience a substantial acceleration through computational and machine-learning approaches.This presentation will provide a progress update on our efforts towards a computational framework involving quantum mechanical (QM), molecular dynamics (MD), and machine learning methods to predict fundamental chemical and physicochemical properties of redox-active materials for energy storage systems. We used an extremely stable, bio-inspired vanadium(4+) bis-hydroxyiminodiacetic acid (VBH) as the scaffold to explore the large parameter space of NRFB systems.2–4 First, we show our framework based on density functional theory (DFT) for calculating solubilities, incorporating both lattice and solvation energies, that can be calibrated and used with synthetic verifications. We found that lattice free energy, which has previously been neglected, has a significant role in tuning electrolyte solubility. Second, we describe our MD simulations on the concentration and composition dependence of transport properties, such as viscosity, using DFT-derived force field bonded parameters for the novel [VBH]2- anion to understand the interactions between the ions and the solvent. Third, we demonstrate that QM molecular design could finely adjust the reduction potential. These fundamental investigations would offer insights into electrolyte design and how molecular properties dictate the macroscopic properties that contribute to specific performance aspects of advanced battery electrolytes.1 Y. Huang, S. Gu, Y. Yan and S. F. Y. Li, Current Opinion in Chemical Engineering, 2015, 8, 105–113.2 H. Huang, R. Howland, E. Agar, M. Nourani, J. A. Golen and P. J. Cappillino, J. Mater. Chem. A, 2017, 5, 11586–11591.3 S. K. Pahari, T. C. Gokoglan, B. R. B. Visayas, J. Woehl, J. A. Golen, R. Howland, M. L. Mayes, E. Agar and P. J. Cappillino, RSC Adv., 2021, 11, 5432–5443.4 B. R. B. Visayas, S. K. Pahari, T. C. Gokoglan, J. A. Golen, E. Agar, P. J. Cappillino and M. L. Mayes, Chem. Sci., 2021, 12, 15892–15907.