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Nitrocellulose is a reactive derivative of cellulose, one of the most commonly occurring natural materials. Nitration of cellulose decreases the stability of the structure, meaning less is understood about its structure and reactions. Although cellulose is often found in fully crystalline forms, nitrocellulose is more commonly paracrystalline, or amorphous. We present a protocol based on molecular dynamics simulations for creating realistic structures of nitrocellulose, particularly focusing on the crystallinity of the systems being created. We will also provide a detailed analysis of the geometric and dynamical parameters used to quantify the degree of crystallinity for the structures created here, with nitration levels varying from 0–14.14 wt% nitrogen content. Paracrystalline cellulose was not created using the protocol designed here, although it was found that the more nitrated a nitrocellulose system, the more the structure tends to paracrystallinity. This is due to a decrease in the number of hydrogen bonds present, and an increase in the size of the functional groups pushing the chains apart and weakening the interactions between the chains of the structure. The structures created are representative of realistic systems, which in the future will be able to be used to build further understanding of long-term storage of nitrocellulose. [ABSTRACT FROM AUTHOR]

Fully quantum mechanical approaches to calculating protein–ligand free energies of binding have the potential to reduce empiricism and explicitly account for all physical interactions responsible for protein–ligand binding. In this study, we show a realistic test of the linear-scaling DFT-based QM-PBSA method to estimate quantum mechanical protein–ligand binding free energies for a set of ligands binding to the pharmaceutical drug-target bromodomain containing protein 4 (BRD4). We show that quantum mechanical QM-PBSA is a significant improvement over traditional MM-PBSA in terms of accuracy against experiment and ligand rank ordering and that the quantum and classical binding energies are converged to a similar degree. We test the interaction entropy and normal mode entropy correction terms to QM- and MM-PBSA. [ABSTRACT FROM AUTHOR]

Application of Li-ion batteries in electric vehicles requires improved safety, increased lifetime and high charging rates. One of the most commonly used intercalation anode material for Li-ion batteries, graphite, is vulnerable to Li nucleation, a side reaction which competes with the intercalation process and leads to loss of reversible capacity of the battery, ageing and short-circuits. In this study, we deploy a combined grand canonical large-scale electronic density-functional theory (DFT) and Poisson–Boltzmann electrolyte theory to study the nucleation and growth of Li clusters on the graphite anode in the presence of its surrounding electrolyte environment at different applied voltages with respect to the Li metal reference electrode. We find the voltage below which the nucleation energy becomes negative (corresponding to Li nucleation becoming energetically favourable), the 'potential of zero nucleation energy' (UPZN). We observe a distinct minimum in the plots of UPZN as a function of the size of nucleated clusters. When the applied voltage on the graphite electrode is below the minimum value of UPZN, the nucleated clusters start growing unbounded on graphite electrode. This potential for cluster growth (UPCG) is found to be −0.12 V on the periodic basal plane of unlithiated graphite and −0.08 V on lithiated graphite. The corresponding potential for the zigzag edge termination is −0.06 V on unlithiated graphite and −0.04 V on lithiated graphite. Thus, the nucleation and cluster growth is favored on the zigzag edge termination of the graphite electrode as compared to the periodic basal plane and on the lithiated graphite as compared to the unlithiated graphite. We find that the surrounding environment plays a significant role and that nucleation is more likely to occur in electrolyte environment than that predicted from calculations in vacuum. We observe that the potentials obtained with grand canonical ensemble DFT method in electrolyte are close to experimentally available data. The study has profound implications for the nucleation, growth and control of metal dendrites in a battery cell. [ABSTRACT FROM AUTHOR]

In this work, we present the first extension of an energy decomposition analysis (EDA) method to metallic systems. We extend the theory of our Hybrid Absolutely Localized Molecular Orbitals (HALMO) EDA to take into account that molecular orbitals in metallic systems are partially occupied, which is done by weighted orthogonalization (WO) of the molecular orbitals using their associated fractional occupancies as weights in the construction of the projection operators. These operators are needed for the self-consistent field for molecular interaction (SCF MI) computation of the polarization-energy contribution to the interaction. The method gives more weight to orbitals that have higher occupancies and treats each fragment as metallic. The resulting HALMO EDA for metallic systems naturally reduces to the insulator version and produces the same results when applied to an insulating system. We present the theory and implementation of our new approach, and we demonstrate it with sample calculations of relevance to industrial materials. This work provides a new EDA paradigm and tool for the study and analysis of interactions in metallic systems within large-scale DFT calculations. [ABSTRACT FROM AUTHOR]

Lithium metal plating is a critical safety issue in Li-ion cells with graphite anodes, and contributes significantly to ageing, drastically limiting the lifetime and inducing capacity loss. Nonetheless, the nucleation mechanism of metallic Li on graphite anodes is still poorly understood. But in-depth understanding is needed to rationally design mitigation measures. In this work, we conducted First-Principles studies to elucidate the Li nucleation mechanism on graphite surfaces. These large-scale density-functional-theory (DFT) calculations indicate that nano-particulate Li forms much more readily than classical nucleation theory predicts. Further, our calculations indicate a crucial role of topological surface states near the zigzag edge, lowering the nucleation barrier by a further 1.32 eV relative to nucleation on the basal plane. Li nucleation, therefore, is likely to initiate at or near the zigzag edges of graphitic particles. Finally, we suggest that chemical doping with a view to reducing the effect of the topological surface states might be a potential mitigation strategy to increase nucleation barriers and reduce the propensity to plate Li near the zigzag edge. [ABSTRACT FROM AUTHOR]

The accurate prediction of protein–ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein–ligand interaction at a quantum mechanical level, instead of relying on empirical classical-mechanics methods, is an important step toward this goal. In this study, we explore the QM-PBSA method to calculate the free energies of binding of seven ligands to the T4-lysozyme L99A/M102Q mutant using linear-scaling density functional theory on the whole protein–ligand complex. By leveraging modern high-performance computing we perform over 2900 full-protein (2600 atoms) DFT calculations providing new insights into the convergence, precision and reproducibility of the QM-PBSA method. We find that even at moderate sampling over 50 snapshots, the convergence of QM-PBSA is similar to traditional MM-PBSA and that the DFT-based energy evaluations are very reproducible. We show that in the QM-PBSA framework, the physically-motivated GGA exchange–correlation functional PBE outperforms the more modern, dispersion-including non-local and meta-GGA-nonlocal functionals VV10 and B97M-rV. Different empirical dispersion corrections perform similarly well but the three-body dispersion term, as included in Grimme's D3 dispersion, is significant and improves results slightly. Inclusion of an entropy correction term sampled over less than 25 snapshots is detrimental while an entropy correction sampled over the same 50 or 100 snapshots as the enthalpies improves the accuracy of the QM-PBSA method. As full-protein DFT calculations can now be performed on modest computational resources our study demonstrates that they can be a useful addition to the toolbox of free energy calculations. [ABSTRACT FROM AUTHOR]

GC content is a contributing factor to the stability of nucleic acids due to hydrogen bonding. More hydrogen bonding generally results in greater stability. Empirical evidence, however, has suggested that the GC content of a nucleic acid is a poor predictor of its stability, implying that there are sequence-dependent interactions besides what its GC content indicates. To examine how much such sequence-dependent interactions affect the interaction energies of double-stranded DNA (dsDNA) molecules, dsDNA molecules of different sequences are generated and examined in silico for variabilities in the interaction energies within each group of dsDNA molecules of the same GC content. Since the amount of hydrogen bonding depends on the GC content, holding the GC content fixed when examining the differences in interaction energies allows sequence-dependent interactions to be isolated. The nature of sequence-dependent interactions is then dissected using energy decomposition analysis (EDA). By using EDA, the components of the interactions that depend on the neighboring base pairs help explain some of the variability in the interaction energies of the dsDNA molecules despite having the same GC content. This work provides a new paradigm and tool for the study and analysis of the distributions of interaction components in dsDNA with the same GC content using EDA within large-scale quantum chemistry calculations. [ABSTRACT FROM AUTHOR]

Strain in Pt nanoalloys induced by the secondary metal has long been suggested as a major contributor to the modification of catalytic properties. Here, we investigate strain in PtCo nanoparticles using a combination of computational modelling and microscopy experiments. We have used a combination of molecular dynamics (MD) and large-scale density functional theory (DFT) for our models, alongside experimental work using annular dark field scanning transmission electron microscopy (ADF-STEM). We have performed extensive validation of the interatomic potential against DFT using a Pt568Co18 nanoparticle. Modelling gives access to 3 dimensional structures that can be compared to the 2D ADF-STEM images, which we use to build an understanding of nanoparticle structure and composition. Strain has been measured for PtCo and pure Pt nanoparticles, with MD annealed models compared to ADF-STEM images. Our analysis was performed on a layer by layer basis, where distinct trends between the Pt and PtCo alloy nanoparticles are observed. To our knowledge, we show for the first time a way in which detailed atomistic simulations can be used to augment and help interpret the results of ADF-STEM strain mapping experiments, which will enhance their use in characterisation towards the development of improved catalysts. [ABSTRACT FROM AUTHOR]

The interface between the electrolyte and graphite anodes plays an important role for lithium (Li) intercalation and has significant impact on the charging/discharging performance of Lithium-Ion Batteries (LIBs). However, atomistic understanding of interface effects that would allow the interface to be rationally optimized for application needs is largely missing. Here we comprehensively study the energetics of Li intercalation near the main non-basal surfaces of graphite, namely the armchair and zigzag edges. We find that edge sites at both surfaces bind Li more strongly than in the bulk of graphite. Therefore, lithiation of these sites is expected to proceed at higher voltages than in the bulk. Furthermore, this effect is significantly more pronounced at the zigzag edge compared to the armchair edge due to its unique electronic structure. The "peculiar" topologically stabilized electronic surface state found at zigzag edges strongly interacts with Li, thereby changing Li diffusion behavior at the surface as well. Finally, we investigate boron (B)/nitrogen (N) doping as a promising strategy to tune the Li intercalation behavior at both edge systems, which could lead to enhanced intercalation kinetics in B/N doped graphite anodes. [ABSTRACT FROM AUTHOR]

Field-Effect Transistor sensors (FET-sensors) have been receiving increasing attention for biomolecular sensing over the last two decades due to their potential for ultra-high sensitivity sensing, label-free operation, cost reduction and miniaturisation. Whilst the commercial application of FET-sensors in pH sensing has been realised, their commercial application in biomolecular sensing (termed BioFETs) is hindered by poor understanding of how to optimise device design for highly reproducible operation and high sensitivity. In part, these problems stem from the highly interdisciplinary nature of the problems encountered in this field, in which knowledge of biomolecular-binding kinetics, surface chemistry, electrical double layer physics and electrical engineering is required. In this work, a quantitative analysis and critical review has been performed comparing literature FET-sensor data for pH-sensing with data for sensing of biomolecular streptavidin binding to surface-bound biotin systems. The aim is to provide the first systematic, quantitative comparison of BioFET results for a single biomolecular analyte, specifically streptavidin, which is the most commonly used model protein in biosensing experiments, and often used as an initial proof-of-concept for new biosensor designs. This novel quantitative and comparative analysis of the surface potential behaviour of a range of devices demonstrated a strong contrast between the trends observed in pH-sensing and those in biomolecule-sensing. Potential explanations are discussed in detail and surface-chemistry optimisation is shown to be a vital component in sensitivity-enhancement. Factors which can influence the response, yet which have not always been fully appreciated, are explored and practical suggestions are provided on how to improve experimental design. [ABSTRACT FROM AUTHOR]

In this work, the crystal properties, HOMO and LUMO energies, band gaps, density of states, as well as the optical absorption spectra of fullerene C60 and its derivative phenyl-C61-butyric-acid-methyl-ester (PCBM) co-crystallised with various solvents such as benzene, biphenyl, cyclohexane, and chlorobenzene were investigated computationally using linear-scaling density functional theory with plane waves as implemented in the ONETEP program. Such solvates are useful materials as electron acceptors for organic photovoltaic (OPV) devices. We found that the fullerene parts contained in the solvates are unstable without solvents, and the interactions between fullerene and solvent molecules in C60 and PCBM solvates make a significant contribution to the cohesive energies of solvates, indicating that solvent molecules are essential to keep C60 and PCBM solvates stable. Both the band gap (Eg) and the HOMO and LUMO states of C60 and PCBM solvates are mainly determined by the fullerene parts contained in solvates. Chlorobenzene- and ortho-dichlorobenzene-solvated PCBM are the most promising electron-accepting materials among these solvates for increasing the driving force for charge separation in OPVs due to their relatively high LUMO energies. The UV-Vis absorption spectra of solvent-free C60 and PCBM crystals in the present work are similar to those of C60 and PCBM thin films shown in the literature. Changes in the absorption spectra of C60 solvates relative to the solvent-free C60 crystal are more significant than those of PCBM solvates due to the weaker effect of solvents on the π-stacking interactions between fullerene molecules in the latter solvates. The main absorptions for all C60 and PCBM crystals are located in the ultraviolet (UV) region. [ABSTRACT FROM AUTHOR]

The partitioning of the energy in ab initio quantum mechanical calculations into its chemical origins (e.g., electrostatics, exchange–repulsion, polarization, and charge transfer) is a relatively recent development; such concepts of isolating chemically meaningful energy components from the interaction energy have been demonstrated by variational and perturbation based energy decomposition analysis approaches. The variational methods are typically derived from the early energy decomposition analysis of Morokuma [Morokuma, J. Chem. Phys., 1971, 55, 1236], and the perturbation approaches from the popular symmetry-adapted perturbation theory scheme [Jeziorski et al., Methods and Techniques in Computational Chemistry: METECC-94, 1993, ch. 13, p. 79]. Since these early works, many developments have taken place aiming to overcome limitations of the original schemes and provide more chemical significance to the energy components, which are not uniquely defined. In this review, after a brief overview of the origins of these methods we examine the theory behind the currently popular variational and perturbation based methods from the point of view of biochemical applications. We also compare and discuss the chemical relevance of energy components produced by these methods on six test sets that comprise model systems that display interactions typical of biomolecules (such as hydrogen bonding and π–π stacking interactions) including various treatments of the dispersion energy. [ABSTRACT FROM AUTHOR]