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Classical (MD) and ab initio (AIMD) molecular dynamics simulations were conducted to investigate the fundamental properties of solid and liquid MgO. AIMD was performed by DFT using the Strongly Conditioned and Appropriately Normed (SCAN) exchange correlation functional. The obtained pair-correlation functions of liquid MgO were used as reference data for the optimization of parameters of classical MD. For the latter, a Born–Mayer–Huggins (BMH) potential was applied, and parameters were adjusted until a best fit of both structural properties was obtained by AIMD and physical properties by experimental data. Different structural, dynamic and thermodynamic properties of solid and liquid MgO were then calculated by classical MD and compared with the literature data. Good agreement was found for the Mg-O bond length, self-diffusion coefficients, density of liquid MgO and for heat content and density of crystalline MgO. Using a void-melting approach, the melting temperature of MgO was found as 3295 ± 30 K, which is in good agreement with the recent experimental work by Ronchi et al. (3250 ± 20 K). The optimized parameters of BMH potential describe well the structural, dynamic and thermodynamic properties of solid and liquid MgO and may be combined with our previous results of a CaO-Al2O3-TiO2 system to calculate the properties of a quaternary CaO-MgO-Al2O3-TiO2 system.

Atomic force microscopes are used, besides their principal function as surface imaging tools, in the surface manipulation and measurement of interfacial properties. In particular, they can be modified to measure lateral friction forces that occur during the sliding of the tip against the underlying substrate. However, the shape, size, and deformation of the tips profoundly affect the measurements in a manner that is difficult to predict. In this work, we investigate the contribution of these effect to the magnitude of the lateral forces during sliding. The surface substrate is chosen to be a few-layer AB-stacked graphene surface, whereas the tip is initially constructed from face-centered cubic gold. In order to separate the effect of deformation from the shape, the rigid tips of three different shapes were considered first, namely, a cone, a pyramid and a hemisphere. The shape was seen to dictate all aspects of the interface during sliding, from temperature dependence to stick–slip behavior. Deformation was investigated next by comparing a rigid hemispherical tip to one of an identical shape and size but with all but the top three layers of atoms being free to move. The deformation, as also verified by an indentation analysis, occurs by means of the lower layers collapsing on the upper ones, thereby increasing the contact area. This collapse mitigates the friction force and decreases it with respect to the rigid tip for the same vertical distance. Finally, the size effect is studied by means of calculating the friction forces for a much larger hemispherical tip whose atoms are free to move. In this case, the deformation is found to be much smaller, but the stick–slip behavior is much more clearly seen.

We introduced a novel machine-learned interatomic potential (MLIP) by thoroughly discussing the step–by–step MLIP creation process using precise but limited data. This study explored the mechanical properties of hexagonal boron nitride (hBN) nanosheets and addressed the challenges of accurately predicting their structural properties. We explored the use of ab initio molecular dynamics and classical molecular dynamics (CMD) simulation techniques, emphasizing the necessity for a more effective and efficient solution. We also discussed the machine learning procedure to construct an effective interatomic potential. Furthermore, we address techniques for evaluating the performance and robustness of MLIPs on unseen datasets. Using the newly formed MLIP in a CMD simulation, we investigated the mechanical attributes of hBN nanosheets, exploring the fluctuations in sheet strength across a range of dimensions, temperatures, and varying numbers of layers. We obtained an average Young’s modulus in the range of 980–1000 GPa at 1 K, whereas the average failure stress and strain were approximately 106 GPa and 0.16, respectively. Our results demonstrate significant improvements in the accuracy of hBN nanosheets compared to prior studies, highlighting the effectiveness of MLIP in achieving higher precision with minimal computational cost. This study offers comprehensive analysis and theoretical exploration, delivering valuable insights into MLIP and the mechanical properties of hBN nanosheets, and paves the way for future applications in materials science and engineering.

Surface functionalization of metal nanoparticles (NPs), e.g., using peptides and proteins, has recently attracted a considerable attention in the field of design of therapeutics and diagnostics. The possibility of diverse functionalization allows them to selectively interact with proteins, while the metal core ensures solubility, making them tunable therapeutic agents against diseases due to mis-folding or aggregation. On the other hand, their action is limited by possible self-aggregation, which could be, however, prevented based on the full understanding of their phase diagram as a function of the environmental variables (temperature, ionic strength of the solution, concentration) and intrinsic characteristics (size, charge, amount, and type of functional groups). A common modeling strategy to study the phase behavior is to represent the NPs as spheres interacting via effective potentials implicitly accounting for the solvation effects. Their size put the NPs into the class of colloids, albeit with particularly complex interactions including both attractive and repulsive features, and a consequently complex phase diagram. In this work, we review the studies exploring the phases of these systems starting from those with only attractive or repulsive interactions, displaying a simpler disperse-clustered-aggregated transitions. The phase diagram is here interpreted focusing on the universal aspects, i.e., those dependent on the general feature of the potentials, and available data are organized in a parametric phase diagram. We then consider the potentials with competing attractive short range well and average-long-range repulsive tail, better representing the NPs. Through the proper combination of the attractive only and repulsive only potentials, we are able to interpret the appearance of novel phases, characterized by aggregates with different structural characteristics. We identify the essential parameters that stabilize the disperse phase potentially useful to optimize NP therapeutic activity and indicate how to tune the phase behavior by changing environmental conditions or the NP chemical–physical properties.

n the last two decades, colloidal semiconductor nanocrystals have emerged as a phenomenal research topic due to their size-dependent optoelectronic properties and to their outstanding versatility in many technological applications. In this review, we provide an historical account of the most relevant computational works that have been carried out to understand atomistically the electronic structure of these materials, including the main requirements needed for the preparation of nanocrystal models that align well with the experiments. We further discuss how the advancement of these computational tools has affected the analysis of these nanomaterials over the years. We focus our review on the three main families of colloidal semiconductor nanocrystals: group II-VI and IV-VI metal chalcogenides, group III-V metal pnictogenides and metal halides, in particular lead-based halide perovskites. We discuss the most recent research frontiers and outline the future outlooks expected in this field from a computational perspective.

Transitions between different conformational states are ubiquitous in proteins, being involved in signaling, catalysis, and other fundamental activities in cells. However, modeling those processes is extremely difficult, due to the need of efficiently exploring a vast conformational space in order to seek for the actual transition path for systems whose complexity is already high in the stable states. Here we report a strategy that simplifies this task attacking the complexity on several sides. We first apply a minimalist coarse-grained model to Calmodulin, based on an empirical force field with a partial structural bias, to explore the transition paths between the apo-closed state and the Ca-bound open state of the protein. We then select representative structures along the trajectory based on a structural clustering algorithm and build a cleaned-up trajectory with them. We finally compare this trajectory with that produced by the online tool MinActionPath, by minimizing the action integral using a harmonic network model, and with that obtained by the PROMPT morphing method, based on an optimal mass transportation-type approach including physical constraints. The comparison is performed both on the structural and energetic level, using the coarse-grained and the atomistic force fields upon reconstruction. Our analysis indicates that this method returns trajectories capable of exploring intermediate states with physical meaning, retaining a very low computational cost, which can allow systematic and extensive exploration of the multi-stable proteins transition pathways.

Artemis is an endonuclease responsible for breaking hairpin DNA strands during immune system adaptation and maturation as well as the processing of potentially toxic DNA lesions. Thus, Artemis may be an important target in the development of anticancer therapy, both for the sensitization of radiotherapy and for immunotherapy. Despite its importance, its structure has been resolved only recently, and important questions concerning the arrangement of its active center, the interaction with the DNA substrate, and the catalytic mechanism remain unanswered. In this contribution, by performing extensive molecular dynamic simulations, both classically and at the hybrid quantum mechanics/molecular mechanics level, we evidenced the stable interaction modes of Artemis with a model DNA strand. We also analyzed the catalytic cycle providing the free energy profile and key transition states for the DNA cleavage reaction.

Various isomers of free clusters of zirconium ZrN (N=4÷15) were studied. The results were obtained using molecular dynamics simulation and many-body Clery and Rosato interaction potential. The average length and the binding energy, the coordination number and the frequency of occurrence of various isomers were calculated.

We report a multi-scale simulation study of the photocycle of the rhodopsins. The quasi-atomistic representation (“united atoms” UA) of retinal is combined with a minimalist coarse grained (CG, one-bead-per amino acid) representation of the protein, in a hybrid UA/CG approach, which is the homolog of QM/MM, but at lower resolution. An accurate multi-stable parameterization of the model allows simulating each state and transition among them, and the combination of different scale representation allows addressing the entire photocycle. We test the model on bacterial rhodopsin, for which more experimental data are available, and then also report results for mammalian rhodopsins. In particular, the analysis of simulations reveals the spontaneous appearance of meta-stable states in quantitative agreement with experimental data.

Background: Free-standing carbon nanomembranes (CNM) with molecular thickness and macroscopic size are fascinating objects both for fundamental reasons and for applications in nanotechnology. Although being made from simple and identical precursors their internal structure is not fully known and hard to simulate due to the large system size that is necessary to draw definite conclusions.Results: We performed large-scale classical molecular dynamics investigations of biphenyl-based carbon nanomembranes. We show that one-dimensional graphene-like stripes constitute a highly symmetric quasi one-dimensional energetically favorable ground state. This state does not cross-link. Instead cross-linked structures are formed from highly excited precursors with a sufficient amount of broken phenyls.Conclusion: The internal structure of the CNM is very likely described by a disordered metastable state which is formed in the energetic initial process of electron irradiation and depends on the process of relaxation into the sheet phase.

Fluidity of lipid membranes is known to play an important role in the functioning of living organisms. The fluorescent probe Laurdan embedded in a lipid membrane is typically used to assess the fluidity state of lipid bilayers by utilizing the sensitivity of Laurdan emission to the properties of its lipid environment. In particular, Laurdan fluorescence is sensitive to gel vs liquid–crystalline phases of lipids, which is demonstrated in different emission of the dye in these two phases. Still, the exact mechanism of the environment effects on Laurdan emission is not understood. Herein, we utilize dipalmitoylphosphatidylcholine (DPPC) and dioleoylphosphatidylcholine (DOPC) lipid bilayers, which at room temperature represent gel and liquid–crystalline phases, respectively. We simulate absorption and emission spectra of Laurdan in both DOPC and DPPC bilayers with quantum chemical and classical molecular dynamics methods. We demonstrate that Laurdan is incorporated in heterogeneous fashion in both DOPC and DPPC bilayers, and that its fluorescence depends on the details of this embedding.

We use the dimer (HF???HF) as a model system to understand the dynamics in hydrogen-bonded systems. This particularly simple system has been widely used both in experimental and theoretical studies. Here we focus on the remarkable mode selectivity in vibrational predissociation processes which occur on time scales of picoseconds to nanoseconds. We have performed classical molecular dynamics (MD) calculations on the six-dimensional SO-3 potential energy surface (PES) of (HF)2[1] to estimate absorption spectra and predissociation lifetimes ?PD for various initial vibrational excitations involving HF stretching. Our calculations can qualitatively reproduce the mode selectivity in ?PD observed experimentally: Excitations involving the 'hydrogen-bonded' HF stretching mode give rise to shorter ?PD than those involving the 'free' HF stretching mode. Besides results concerning the HF dimer, this study offers the opportunity to check to what extent classical MD calculations on an accurate and realistic potential are suitable to study dynamical properties in such a molecular system.