SciCombinator

We use energy landscape methods to investigate the response of a supercooled liquid to random pinning. We classify the structural similarity of different energy minima using a measure of overlap. This analysis reveals a correspondence between distinct particle packings (which are characterised via the overlap) and funnels on the energy landscape (which are characterised via disconnectivity graphs). As the number of pinned particles is increased, we find a crossover from glassy behavior at low pinning to a structure-seeking landscape at high pinning, in which all thermally accessible minima are structurally similar. We discuss the consequences of these results for theories of randomly pinned liquids. We also investigate how the energy landscape depends on the fraction of pinned particles, including the degree of frustration and the evolution of distinct packings as the number of pinned particles is reduced.

The free-complement chemical-formula theory (FC-CFT) for solving the Schrödinger equation (SE) was applied to the first-row atoms and several small molecules, limiting only to the ground state of a spin symmetry. Highly accurate results, satisfying chemical accuracy (kcal/mol accuracy for the absolute total energy), were obtained for all the cases. The local Schrödinger equation (LSE) method was applied for obtaining the solutions accurately and stably. For adapting the sampling method to quantum mechanical calculations, we developed a combined method of local sampling and Metropolis sampling. We also reported the method that leads the calculations to the accurate energies and wave functions as definite converged results with minimum ambiguities. We have also examined the possibility of the stationarity principle in the sampling method: it certainly works, though more extensive applications are necessary. From the high accuracy and the constant stability of the results, the present methodology seems to provide a useful tool for solving the SE of atoms and molecules.

Molecular simulation results at extreme temperatures and pressures can supplement experimental data when developing fundamental equations of state. Since most force fields are optimized to agree with vapor-liquid equilibria (VLE) properties, however, the reliability of the molecular simulation results depends on the validity/transferability of the force field at higher temperatures and pressures. As demonstrated in this study, although state-of-the-art united-atom Mie λ-6 potentials for normal and branched alkanes provide accurate estimates for VLE, they tend to over-predict pressures for dense supercritical fluids and compressed liquids. The physical explanation for this observation is that the repulsive barrier is too steep for the “optimal” united-atom Mie λ-6 potential parameterized with VLE properties. Bayesian inference confirms that no feasible combination of non-bonded parameters (ϵ, σ, and λ) is capable of simultaneously predicting saturated vapor pressures, saturated liquid densities, and pressures at high temperatures and densities. This conclusion has both practical and theoretical ramifications, as more realistic non-bonded potentials may be required for accurate extrapolation to high pressures of industrial interest.

The thermoelectric efficiency of a thermal machine consisting of a triangular graphene nano-junction connected to three electrodes in the linear response regime is studied. Using the Onsager formalism and a combination of semi-empirical tight-binding calculations as well as Green’s function theory, the efficiency at maximum output power which can be written in terms of generalized figures of merit is investigated. The results for a set temperature and chemical potential parameters have shown that adding a third terminal improves the efficiency at maximum output power compared to the two-terminal setup.

We use molecular dynamics simulations with the ReaxFF-lg potential to model the high pressure pyrolysis of carbon suboxide (C3O2) in mixture with argon as a pressure bath. We show that the reactive simulations catch the experimental behavior of the low-pressure detonation of C3O2 (around 10 bars in shock tube experiments) and allow extrapolations to the high-pressure range of solid-state explosive detonation (up to 60 GPa). While at low pressure carbonaceous nanostructures are formed through the aggregation of species such as carbon dimers C2, it appears that the high pressure deeply modifies the process, with the aggregation of growing CxOy heterostructures, in which the oxygen amount is driven by the pressure and the temperature. Pressures in the order of 60 GPa lead to high oxygen ratios, which prevent carbon atoms to get four carbon neighbors (the first condition to get a diamond structure). But a pressure lowering leads to a substantial carbon enrichment through CO2/CO release and facilitates the formation of pure sp3-carbon phases where diamond precursors can form. These results give new insights on the conditions leading to nanodiamonds during the detonation of carbon-rich high explosives.

A model is developed for simulating entangled polymers by dissipative particle dynamics (DPD) using the segmental repulsive potential (SRP). In contrast to previous SRP models that define a single-point interaction on each bond, the proposed SRP model applies a dynamically adjustable multipoint on the bond. Previous SRP models could not reproduce the equilibrium properties of Groot and Warren’s original DPD model [R. D. Groot and P. B. Warren, J. Chem. Phys. 107, 4423 (1997)] because the introduction of a single SRP induces a large excluded volume, whereas, the proposed multipoint SRP (MP-SRP) introduces a cylindrical effective excluded bond volume. We demonstrate that our MP-SRP model exhibits equilibrium properties similar to those of the original DPD polymers. The MP-SRP model parameters are determined by monitoring the number of topology violations, thermodynamic properties, and the polymer internal structure. We examine two typical DPD polymers with different bond-length distributions; one of them was used in the modified SRP model by Sirk et al. [J. Chem. Phys. 136, 134903 (2012)], whereas the other was used in the original DPD model. We demonstrate that for both polymers, the proposed MP-SRP model captures the entangled behaviors of a polymer melt naturally, by calculating the slowest relaxation time of a chain in the melt and the shear relaxation modulus. The results indicate that the proposed MP-SRP model can be applied to a variety of DPD polymers.

This paper continues the investigation of the exponentially repulsive EXP pair-potential system of Paper I [A. K. Bacher et al., J. Chem. Phys. 149, 114501 (2018)] with a focus on isomorphs in the low-temperature gas and liquid phases. As expected from the EXP system’s strong virial potential-energy correlations, the reduced-unit structure and dynamics are isomorph invariant to a good approximation. Three methods for generating isomorphs are compared: the small-step method that is exact in the limit of small density changes and two versions of the direct-isomorph-check method that allows for much larger density changes. Results from the latter two approximate methods are compared to those of the small-step method for each of the three isomorphs generated by 230 one percent density changes, covering one decade of density variation. Both approximate methods work well.

The liquid-liquid hypothesis, which states that a pure substance can exhibit two liquid forms (or polymorphs), has drawn considerable interest in recent years. The appeal of this theory is that it provides the basis for a deeper understanding of the properties of supercooled liquids. However, the study of this phenomenon is extremely challenging and a complete understanding of its impact on fluid properties has remained elusive so far, since the low-temperature liquid form is generally not stable and undergoes rapid crystallization. Using a coarse-grained model for methanol, we show that methanol under shear can exhibit, in the steady state, two liquid forms that respond differently to the applied shear. Using molecular simulations, we show that the difference in dynamical response is correlated with structural differences between the two liquid forms. This establishes the existence of liquid polymorphism for systems driven out-of-equilibrium. Our findings also show how, by varying the pressure or the shear stress applied to the system, liquid-liquid transitions can be triggered and how a control of liquid polymorphism can be achieved. The resulting solid-liquid-liquid nonequilibrium phase diagram leads us to identify new ways for the stabilization and study of liquid polymorphism.

It was recently shown that the exponentially repulsive EXP pair potential defines a system of particles in terms of which simple liquids' quasiuniversality may be explained [A. K. Bacher et al., Nat. Commun. 5, 5424 (2014); J. C. Dyre, J. Phys.: Condens. Matter 28, 323001 (2016)]. This paper and its companion [A. K. Bacher et al., J. Chem. Phys. 149, 114502 (2018)] present a detailed simulation study of the EXP system. Here we study how structure monitored by the radial distribution function and dynamics monitored by the mean-square displacement as a function of time evolve along the system’s isotherms and isochores. The focus is on the gas and liquid phases, which are distinguished pragmatically by the absence or presence of a minimum in the radial distribution function above its first maximum. A constant-potential-energy (NVU)-based proof of quasiuniversality is presented, and quasiuniversality is illustrated by showing that the structure of the Lennard-Jones system at four state points is well approximated by those of EXP pair-potential systems with the same reduced diffusion constant. Paper II studies the EXP system’s isomorphs, focusing also on the gas and liquid phases.

Graphene’s unique physical structure, as well as its chemical and electrical properties, make it ideal for use in sensor technologies. In the past years, novel sensing platforms have been proposed with pristine and modified graphene with nanoparticles and polymers. Several of these platforms were used to immobilize biomolecules, such as antibodies, DNA, and enzymes to create highly sensitive and selective biosensors. Strategies to attach these biomolecules onto the surface of graphene have been employed based on its chemical composition. These methods include covalent bonding, such as the coupling of the biomolecules via the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride and N-hydroxysuccinimide reactions, and physisorption. In the literature, several detection methods are employed; however, the most common is electrochemical. The main reason for researchers to use this detection approach is because this method is simple, rapid and presents good sensitivity. These biosensors can be particularly useful in life sciences and medicine since in clinical practice, biosensors with high sensitivity and specificity can significantly enhance patient care, early diagnosis of diseases and pathogen detection. In this review, we will present the research conducted with antibodies, DNA molecules and, enzymes to develop biosensors that use graphene and its derivatives as scaffolds to produce effective biosensors able to detect and identify a variety of diseases, pathogens, and biomolecules linked to diseases.