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In two recent papers [A. D. Becke, J. Chem. Phys. 156, 214101 (2022) and A. D. Becke, J. Chem. Phys. 157, 234102 (2022)], we compared two Kohn–Sham density functionals based on physical modeling and theory with the best density-functional power-series fits in the literature. The best error statistics reported to date for a hybrid functional on the general main-group thermochemistry, kinetics, and noncovalent interactions (GMTKN55) chemical database of Goerigk et al. [Phys. Chem. Chem. Phys. 19, 32184 (2017)] were obtained. In the present work, additional second-order perturbation-theory terms are considered. The result is a 12-parameter double-hybrid density functional with the lowest GMTKN55 WTMAD2 "weighted total mean absolute deviation" error (1.76 kcal/mol) yet seen for any hybrid or double-hybrid density-functional approximation. We call it "DH23." [ABSTRACT FROM AUTHOR]

Light-induced orientation of gas phase molecules is a long-pursued goal in physics and chemistry. Here, we experimentally demonstrate a six-fold increase in the terahertz-induced orientation of iodomethane (CH3I) molecules at room temperature, provided by rotational pre-excitation with a moderately intense near-IR pulse. The paper highlights the underlying interference of multiple coherent transition pathways within the rotational coherence manifold and is analyzed accordingly. Our experimental and theoretical results provide desirable and practical means for all-optical experiments on oriented molecular ensembles. [ABSTRACT FROM AUTHOR]

The theory of adiabatic electron transport in a correlated condensed-matter system is rooted in a seminal paper by Niu and Thouless [J. Phys. A: Math. Gen. 17, 2453 (1984)]; I adopt here an analogous logic in order to retrieve the known expression for the adiabatic electronic flux in a molecular system [L. A. Nafie, J. Chem. Phys. 79, 4950 (1983)]. Its derivation here is considerably simpler than those available in the current quantum-chemistry literature; it also explicitly identifies the adiabaticity parameter, in terms of which the adiabatic flux and the electron density are both exact to first order. It is shown that the continuity equation is conserved to the same order. For the sake of completeness, I also briefly outline the relevance of the macroscopic electronic flux to the physics of solids and liquids. [ABSTRACT FROM AUTHOR]

It is well documented that conventional methods such as dynamic light scattering have encountered difficulties in characterizing charged macromolecules and, therefore, it is desirable that new methods and techniques are introduced. With the ultra-high sensitivity, single molecule fluorescence spectroscopy has successfully lowered the detection limit considerably and enabled measurement under extreme dilution conditions—around the concentration of 10−9M—at which the effect of inter-chain electrostatic repulsion is suppressed. Furthermore, the excellent spatial and temporal resolution as well as the capacity of molecular recognition of these methods help in obtaining rich information of charged macromolecules. This paper summarizes the applications of single molecule fluorescence spectroscopy, especially fluorescence correlation spectroscopy and photon counting histogram, in the studies on charged macromolecules in aqueous solutions and plenty of new information has been revealed on the molecular conformation, counterion distribution, and a few important governing factors. The powerfulness and effectiveness of single molecule fluorescence spectroscopy make it promising in the investigations of charged macromolecules. [ABSTRACT FROM AUTHOR]

In this paper, we compare and contrast basis set sampling techniques recently developed for use in the ab initio multiple cloning method, a direct dynamics extension to the multiconfigurational Ehrenfest approach, used recently for the quantum simulation of ultrafast photochemistry. We demonstrate that simultaneous use of basis set cloning and basis function trains can produce results which are converged to the exact quantum result. To demonstrate this, we employ these sampling methods in simulations of quantum dynamics in the spin boson model with a broad range of parameters and compare the results to accurate benchmarks. [ABSTRACT FROM AUTHOR]

Ice accumulation on solid surfaces is a severe problem for safety and functioning of a large variety of engineering systems, and its control is an enormous challenge that influences the safety and reliability of many technological applications. The use of molecular dynamics (MD) simulations is popular, but as ice nucleation is a rare event when compared to simulation timescales, the simulations need to be accelerated to force ice to form on a surface, which affects the accuracy and/or applicability of the results obtained. Here, we present an alternative seeded MD simulation approach, which reduces the computational cost while still ensuring accurate simulations of ice growth on surfaces. In addition, this approach enables, for the first time, brute-force all-atom water simulations of ice growth on surfaces unfavorable for nucleation within MD timescales. Using this approach, we investigate the effect of surface wettability and structure on ice growth in the crucial surface–ice interfacial region. Our main findings are that the surface structure can induce a flat or buckled overlayer to form within the liquid, and this transition is mediated by surface wettability. The first overlayer and the bulk ice compete to structure the intermediate water layers between them, the relative influence of which is traced using density heat maps and diffusivity measurements. This work provides new understanding on the role of the surface properties on the structure and dynamics of ice growth, and we also present a useful framework for future research on surface icing simulations. [ABSTRACT FROM AUTHOR]

Power law distributions are widely observed in chemical physics, geophysics, biology, and beyond. The independent variable x of these distributions has an obligatory lower bound and, in many cases, also an upper bound. Estimating these bounds from sample data is notoriously difficult, with a recent method involving O(N3) operations, where N denotes sample size. Here I develop an approach for estimating the lower and upper bounds that involve O(N) operations. The approach centers on calculating the mean values, x ̂ min and x ̂ max , of the smallest x and the largest x in N-point samples. A fit of x ̂ min or x ̂ max as a function of N yields the estimate for the lower or upper bound. Application to synthetic data demonstrates the accuracy and reliability of this approach. [ABSTRACT FROM AUTHOR]

Deep neural network (DNN) potentials have recently gained popularity in computer simulations of a wide range of molecular systems, from liquids to materials. In this study, we explore the possibility of combining the computational efficiency of the DeePMD framework and the demonstrated accuracy of the MB-pol data-driven, many-body potential to train a DNN potential for large-scale simulations of water across its phase diagram. We find that the DNN potential is able to reliably reproduce the MB-pol results for liquid water, but provides a less accurate description of the vapor–liquid equilibrium properties. This shortcoming is traced back to the inability of the DNN potential to correctly represent many-body interactions. An attempt to explicitly include information about many-body effects results in a new DNN potential that exhibits the opposite performance, being able to correctly reproduce the MB-pol vapor–liquid equilibrium properties, but losing accuracy in the description of the liquid properties. These results suggest that DeePMD-based DNN potentials are not able to correctly "learn" and, consequently, represent many-body interactions, which implies that DNN potentials may have limited ability to predict the properties for state points that are not explicitly included in the training process. The computational efficiency of the DeePMD framework can still be exploited to train DNN potentials on data-driven many-body potentials, which can thus enable large-scale, "chemically accurate" simulations of various molecular systems, with the caveat that the target state points must have been adequately sampled by the reference data-driven many-body potential in order to guarantee a faithful representation of the associated properties. [ABSTRACT FROM AUTHOR]

The elasticity of disordered and polydisperse polymer networks is a fundamental problem of soft matter physics that is still open. Here, we self-assemble polymer networks via simulations of a mixture of bivalent and tri- or tetravalent patchy particles, which result in an exponential strand length distribution analogous to that of experimental randomly cross-linked systems. After assembly, the network connectivity and topology are frozen and the resulting system is characterized. We find that the fractal structure of the network depends on the number density at which the assembly has been carried out, but that systems with the same mean valence and same assembly density have the same structural properties. Moreover, we compute the long-time limit of the mean-squared displacement, also known as the (squared) localization length, of the cross-links and of the middle monomers of the strands, showing that the dynamics of long strands is well described by the tube model. Finally, we find a relation connecting these two localization lengths at high density and connect the cross-link localization length to the shear modulus of the system. [ABSTRACT FROM AUTHOR]

Simulations of water near extended hydrophobic spherical solutes have revealed the presence of a region of depleted density and accompanying enhanced density fluctuations. The physical origin of both phenomena has remained somewhat obscure. We investigate these effects employing a mesoscopic binding potential analysis, classical density functional theory (DFT) calculations for a simple Lennard-Jones solvent, and Grand Canonical Monte Carlo (GCMC) simulations of a monatomic water (mw) model. We argue that the density depletion and enhanced fluctuations are near-critical phenomena. Specifically, we show that they can be viewed as remnants of the critical drying surface phase transition that occurs at bulk liquid–vapor coexistence in the macroscopic planar limit, i.e., as the solute radius Rs → ∞. Focusing on the radial density profile ρ(r) and a sensitive spatial measure of fluctuations, the local compressibility profile χ(r), our binding potential analysis provides explicit predictions for the manner in which the key features of ρ(r) and χ(r) scale with Rs, the strength of solute–water attraction ɛsf, and the deviation from liquid–vapor coexistence of the chemical potential, δμ. These scaling predictions are confirmed by our DFT calculations and GCMC simulations. As such, our theory provides a firm basis for understanding the physics of hydrophobic solvation. [ABSTRACT FROM AUTHOR]

The use of fully or partially absorbing boundary conditions for diffusion-based problems has become paradigmatic in physical chemistry and biochemistry to describe reactions occurring in solutions or in living media. However, as chemical states may indeed disappear, particles cannot, unless such degradation happens physically and should, thus, be accounted for explicitly. Here, we introduce a simple, yet general idea that allows one to derive the appropriate boundary conditions self-consistently from the chemical reaction scheme and the geometry of the physical reaction boundaries. As an illustration, we consider two paradigmatic examples, where the known results are recovered by taking specific physical limits. More generally, we demonstrate that our mathematical analysis delivers physical insight that cannot be accessed through standard treatments. [ABSTRACT FROM AUTHOR]

In systems with frustration, the critical slowing down of the dynamics severely impedes the numerical study of phase transitions for even the simplest of lattice models. In order to help sidestep the gelation-like sluggishness, a clearer understanding of the underlying physics is needed. Here, we first obtain generic insight into that phenomenon by studying one-dimensional and Bethe lattice versions of a schematic frustrated model, the axial next-nearest neighbor Ising (ANNNI) model. Based on these findings, we formulate two cluster algorithms that speed up the simulations of the ANNNI model on a 2D square lattice. Although these schemes do not eliminate the critical slowing own, speed-ups of factors up to 40 are achieved in some regimes. [ABSTRACT FROM AUTHOR]

We develop closed expressions for a time-resolved photon counting signal induced by an entangled photon pair in an interferometric spectroscopy setup. Superoperator expressions in Liouville-space are derived that can account for relaxation and dephasing induced by coupling to a bath. Interferometric setups mix matter and light variables non-trivially, which complicates their interpretation. We provide an intuitive modular framework for this setup that simplifies its description. Based on the separation between the detection stage and the light–matter interaction processes, we show that the pair entanglement time and the interferometric time-variables control the observed physics time scale. Only a few processes contribute in the limiting case of small entanglement time with respect to the sample response, and specific contributions can be singled out. [ABSTRACT FROM AUTHOR]

Liquid–liquid phase separation of fluids exhibiting interconversion between alternative states has been proposed as an underlying mechanism for fluid polyamorphism and may be of relevance to the protein function and intracellular organization. However, molecular-level insight into the interplay between competing forces that can drive or restrict phase separation in interconverting fluids remains elusive. Here, we utilize an off-lattice model of enantiomers with tunable chiral interconversion and interaction properties to elucidate the physics underlying the stabilization and tunability of phase separation in fluids with interconverting states. We show that introducing an imbalance in the intermolecular forces between two enantiomers results in nonequilibrium, arrested phase separation into microdomains. We also find that in the equilibrium case, when all interaction forces are conservative, the growth of the phase domain is restricted only by the system size. In this case, we observe phase amplification, in which one of the two alternative phases grows at the expense of the other. These findings provide novel insights on how the interplay between dynamics and thermodynamics defines the equilibrium and steady-state morphologies of phase transitions in fluids with interconverting molecular or supramolecular states. [ABSTRACT FROM AUTHOR]

The quantum control of ultrafast excited state dynamics remains an unachieved goal within the chemical physics community. In this study, we assess how strongly coupling to cavity photons affects the excited state dynamics of strongly coupled zinc (II) tetraphenyl porphyrin (ZnTPP) and copper (II) tetraphenyl porphyrin (CuTPP) molecules. By varying the concentration of each chromophore within different Fabry–Pérot (FP) structures, we control the collective vacuum Rabi splitting between the energies of cavity polariton states formed through the strong coupling of molecular electrons and cavity photons. Using ultrafast transient reflectivity and transmission measurements probing optical transitions of individual ZnTPP and CuTPP molecules, we find that the polaritonic states localize into uncoupled excited states of these chromophores through different mechanisms. For ZnTPP, we build a simple kinetic model including a direct channel of relaxation between the polaritonic states. We find that our models necessitate a small contribution from this interpolaritonic relaxation channel to explain both our steady-state and transient optical spectroscopic measurements adequately. In contrast, we propose that strong cavity coupling slows the internal conversion between electronic states of CuTPP not directly interacting with the photons of FP structures. These results suggest that researchers must consider the vibrational structure and excited state properties of the strongly coupled chromophores when attempting to use polariton formation as a tool to control the dynamics of molecules central to photo-sensitizing and light harvesting applications. [ABSTRACT FROM AUTHOR]

The Hückel Hamiltonian is an incredibly simple tight-binding model known for its ability to capture qualitative physics phenomena arising from electron interactions in molecules and materials. Part of its simplicity arises from using only two types of empirically fit physics-motivated parameters: the first describes the orbital energies on each atom and the second describes electronic interactions and bonding between atoms. By replacing these empirical parameters with machine-learned dynamic values, we vastly increase the accuracy of the extended Hückel model. The dynamic values are generated with a deep neural network, which is trained to reproduce orbital energies and densities derived from density functional theory. The resulting model retains interpretability, while the deep neural network parameterization is smooth and accurate and reproduces insightful features of the original empirical parameterization. Overall, this work shows the promise of utilizing machine learning to formulate simple, accurate, and dynamically parameterized physics models. [ABSTRACT FROM AUTHOR]

We examine the many open questions that arise for nonadiabatic dynamics in the presence of degenerate electronic states, e.g., for singlet-to-triplet intersystem crossing where a minimal Hamiltonian must include four states (two of which are always degenerate). In such circumstances, the standard surface hopping approach is not sufficient as the algorithm does not include Berry force. Yet, we hypothesize that such a Berry force may be crucial as far as creating chiral induced spin separation, which is now a burgeoning field of study. Thus, this Perspective highlights the fact that if one can generate a robust and accurate semiclassical approach for the case of degenerate states, one will take a big step forward toward merging chemical physics with spintronics. [ABSTRACT FROM AUTHOR]

The accurate determination of fluid viscosity based on the microscopic information of molecules is very crucial for the prediction of nanoscale flow. Despite the challenge of this problem, researchers have done a lot of meaningful work and developed several distinctive methods. However, one of the common approaches to calculate the fluid viscosity is using the Green–Kubo formula by considering all the fluid molecules in nanospace, inevitably causing the involvement of the frictional interaction between fluid and the wall into the fluid viscosity. This practice is certainly not appropriate because viscosity is essentially related only to the interactions among fluid molecules. Here, we clarify that the wall friction should be decoupled from fluid viscosity by distinguishing the frictional region and the viscous region for the accurate prediction of nanoscale flow. By comparing the fluid viscosities calculated from the Green–Kubo formula in the whole region and viscous region and the viscosity obtained from the velocity profile through the Hagen–Poiseuille equation, it is found that only the calculated viscosity in the viscous region agrees well with the viscosity from the velocity profile. To demonstrate the applicability of this clarification, the Lennard-Jones fluid and water confined between Lennard-Jones, graphene, and silica walls, even with different fluid–wall interactions, are extensively tested. This work clearly defines the viscosity of fluids at nanoscales from the inherent nature of physics, aiming at the accurate prediction of nanoscale flow from the classical continuum hydrodynamic theory. [ABSTRACT FROM AUTHOR]

The nature of bosonic excitations in disordered materials has remained elusive due to the difficulties in defining key concepts such as quasi-particles in the presence of disorder. We report on an experimental observation of phonon-polaritons in glasses, including a prominent boson peak (BP), i.e., excess of THz modes over the Debye law. A theoretical framework based on the concept of diffusons is developed to describe the broadening linewidth of the polariton due to disorder-induced scattering. It is shown here for the first time that the BP frequency and the Ioffe–Regel (IR) crossover frequency of the polariton collapse onto the same power-law decay with the diffusivity of the bosonic excitation. This analysis dismisses the hypothesis of the BP being caused by a relic of the van Hove singularity. The presented framework establishes a new methodology to analyze bosonic excitations in amorphous media, well beyond the traditional case of acoustic phonons, and establishes the IR crossover as the fundamental physical mechanism behind the BP. [ABSTRACT FROM AUTHOR]

We review recent developments in structural–dynamical phase transitions in trajectory space based on dynamic facilitation theory. An open question is how the dynamic facilitation perspective on the glass transition may be reconciled with thermodynamic theories that posit collective reorganization accompanied by a growing static length scale and, eventually, a vanishing configurational entropy. In contrast, dynamic facilitation theory invokes a dynamical phase transition between an active phase (close to the normal liquid) and an inactive phase, which is glassy and whose order parameter is either a time-averaged dynamic or structural quantity. In particular, the dynamical phase transition in systems with non-trivial thermodynamics manifests signatures of a lower critical point that lies between the mode-coupling crossover and the putative Kauzmann temperature, at which a thermodynamic phase transition to an ideal glass state would occur. We review these findings and discuss such criticality in the context of the low-temperature decrease in configurational entropy predicted by thermodynamic theories of the glass transition. [ABSTRACT FROM AUTHOR]

We study the spinodal decomposition in a symmetric, binary homopolymer blend using our recently developed dynamical self-consistent field theory. By taking the extremal solution of a dynamical functional integral, the theory reduces the interacting, multi-chain dynamics to a Smoluchowski equation describing the statistical dynamics of a single, unentangled chain in a self-consistent, time-dependent, mean force-field. We numerically solve this equation by evaluating averages over a large ensemble of replica chains, each one of which obeys single-chain Langevin dynamics, subject to the mean field. Following a quench from the disordered state, an early time spinodal instability in the blend composition develops, before even one Rouse time elapses. The dominant, unstable, growing wavelength is on the order of the coil size. The blend then enters a late-time, t, scaling regime with a growing domain size that follows the expected Lifshitz–Slyozov–Wagner t1/3 power law, a characteristic of a diffusion-driven coarsening process. These results provide a satisfying test of this new method, which correctly captures both the early and late time physics in the blend. Our simulation spans five orders-of-magnitude in time as the domains coarsen to 20 times the coil size, while remaining faithful to the dynamics of the microscopic chain model. [ABSTRACT FROM AUTHOR]

General exact analytical expressions have been derived for the image force energy Wi(Z, φ) of a point dipole in a classical three-layer system composed of dispersionless media with arbitrary constant dielectric permittivities εi. Here, i = 1–3 is the layer number, and Z and φ are the dipole coordinate and orientation angle, respectively. It was found that the long-range asymptotics W i ( Z → ∞ , φ) in both covers (i = 1, 3) are reached unexpectedly far from the interlayer (i = 2). Another specific feature of the solution consists in that the interference of the fields created by polarization charges emerging at both interfaces leads to the appearance of a constant contribution inside the interlayer with a non-standard dependence on the dipole orientation angle φ. It was shown that by changing the dielectric constants of the structure components, one can realize two peculiar regimes of the Wi(Z, φ) behavior in the covers; namely, there arises either a potential barrier preventing adsorption or a well far from the interface, both being of a totally electrostatic origin, i.e., without involving the Pauli exchange repulsion, which is taken into account in the conventional theories of physical adsorption. The results obtained provide a fresh insight into the physics of adsorption in physical electronics, chemical physics, and electrochemistry. [ABSTRACT FROM AUTHOR]

Microemulsions are explored using the self-consistent field approach. We consider a balanced model that features two solvents of similar size and a symmetric surfactant. Interaction parameter χ and surfactant concentration φ s b complement the model definition. The phase diagram in χ– φ s b coordinates is known to feature two lines of critical points, the Scott and Leibler lines. Only upon imposing a finite distance between the interfaces, we observe that the Scott line meets the Leibler line. We refer to this as a Lifshitz point (LP) for real systems. We add regions that are relevant for microemulsions to this phase diagram by considering the saturation line, which connects (χ, φ s b )-points for which the interface becomes tensionless. Crossing this line implies a first-order phase transition as internal interfaces develop, characteristic for one-phase microemulsions. The saturation line ends at the so-called microemulsion point (MP). The MP is shown to connect with the LP by a line of MP-like critical points, found by searching for a "MP" while the distance between interfaces is fixed. A pair of binodal lines that envelop the three-phase (Winsor III) microemulsion region is shown to connect to the MP. The cohesiveness of the middle phase in Winsor III is related to non-monotonic, inverse DLVO-type interaction curves between the surfactant-loaded tensionless interfaces. The mean and Gaussian bending modulus, relevant for the shape fluctuations and the topology of interfaces, respectively, are evaluated along the saturation line. Near the MP, both rigidities are positive and vanish in a power-law fashion with coefficient unity at the MP. Overseeing these results proves that the MP has a pivoting role in the physics of microemulsions. [ABSTRACT FROM AUTHOR]

A generally applicable approach for the calculation of relativistic properties described by one-electron operators within a two-component wave function approach is presented. The formalism is explicitly evaluated for the example of quasirelativistic wave functions obtained within the zeroth order regular approximation (ZORA). The wide applicability of the scheme is demonstrated for the calculation of parity (P) and time-reversal (T ) symmetry violating properties, which are important for searches of physics beyond the standard model of particle physics. The quality of the ZORA results is shown exemplarily for the molecules RaF and TlF by comparison with data from four-component calculations as far as available. Finally, the applicability of RaF in experiments that search for P , T -violation not only in the electronic but also in the quark sector is demonstrated. [ABSTRACT FROM AUTHOR]

The most successful and popular machine learning models of atomic-scale properties derive their transferability from a locality ansatz. The properties of a large molecule or a bulk material are written as a sum over contributions that depend on the configurations within finite atom-centered environments. The obvious downside of this approach is that it cannot capture nonlocal, nonadditive effects such as those arising due to long-range electrostatics or quantum interference. We propose a solution to this problem by introducing nonlocal representations of the system, which are remapped as feature vectors that are defined locally and are equivariant in O(3). We consider, in particular, one form that has the same asymptotic behavior as the electrostatic potential. We demonstrate that this framework can capture nonlocal, long-range physics by building a model for the electrostatic energy of randomly distributed point-charges, for the unrelaxed binding curves of charged organic molecular dimers, and for the electronic dielectric response of liquid water. By combining a representation of the system that is sensitive to long-range correlations with the transferability of an atom-centered additive model, this method outperforms current state-of-the-art machine-learning schemes and provides a conceptual framework to incorporate nonlocal physics into atomistic machine learning. [ABSTRACT FROM AUTHOR]

Sequential infiltration synthesis (SIS) is an emerging materials growth method by which inorganic metal oxides are nucleated and grown within the free volume of polymers in association with chemical functional groups in the polymer. SIS enables the growth of novel polymer-inorganic hybrid materials, porous inorganic materials, and spatially templated nanoscale devices of relevance to a host of technological applications. Although SIS borrows from the precursors and equipment of atomic layer deposition (ALD), the chemistry and physics of SIS differ in important ways. These differences arise from the permeable three-dimensional distribution of functional groups in polymers in SIS, which contrast to the typically impermeable two-dimensional distribution of active sites on solid surfaces in ALD. In SIS, metal-organic vapor-phase precursors dissolve and diffuse into polymers and interact with these functional groups through reversible complex formation and/or irreversible chemical reactions. In this perspective, we describe the thermodynamics and kinetics of SIS and attempt to disentangle the tightly coupled physical and chemical processes that underlie this method. We discuss the various experimental, computational, and theoretical efforts that provide insight into SIS mechanisms and identify approaches that may fill out current gaps in knowledge and expand the utilization of SIS. [ABSTRACT FROM AUTHOR]

We develop a theory of charge storage in ultranarrow slitlike pores of nanostructured electrodes. Our analysis is based on the Blume-Capel model in an external field, which we solve analytically on a Bethe lattice. The obtained solutions allow us to explore the complete phase diagram of confined ionic liquids in terms of the key parameters characterizing the system, such as pore ionophilicity, interionic interaction energy, and voltage. The phase diagram includes the lines of first- and second-order, direct and re-entrant phase transitions, which are manifested by singularities in the corresponding capacitance-voltage plots. Testing our predictions experimentally requires monodisperse, conducting ultranarrow slit pores, to permit only one layer of ions, and thick pore walls, to prevent interionic interactions across the pore walls. However, some qualitative features, which distinguish the behavior of ionophilic and ionophobic pores and their underlying physics, may emerge in future experimental studies of more complex electrode structures. [ABSTRACT FROM AUTHOR]

Bottlebrushes are an emerging class of polymers, characterized by a high density of side chains grafted to a linear backbone that offer promise in creating materials with unusual combinations of mechanical, chemical, and optoelectronic properties. Understanding the role of molecular architecture in the organization and assembly of bottlebrushes is of fundamental importance in polymer physics, but also enabling in applications. Here, we apply field-theoretic simulations to study the effect of grafting density, backbone length, and side-chain (SC) length on the structure and thermodynamics of bottlebrush homopolymer melts. Our results provide evidence for a phase transition from an isotropic to a nematic state with increasing grafting density and side-chain length. Variation in the backbone length is also observed to influence the location of the transition, primarily for short polymers just above the star to bottlebrush transition. [ABSTRACT FROM AUTHOR]

Although molecular dynamics simulations have become a useful tool in essentially all fields of chemistry, condensed matter physics, materials science, and biology, there is still a large gap between the time scale which can be reached in molecular dynamics simulations and that observed in experiments. To address the problem, many enhanced sampling methods were introduced, which effectively extend the time scale being approached in simulations. In this perspective, we review a variety of enhanced sampling methods. We first discuss collective-variables-based methods including metadynamics and variationally enhanced sampling. Then, collective variable free methods such as parallel tempering and integrated tempering methods are presented. At last, we conclude with a brief introduction of some newly developed combinatory methods. We summarize in this perspective not only the theoretical background and numerical implementation of these methods but also the new challenges and prospects in the field of the enhanced sampling. [ABSTRACT FROM AUTHOR]

One of the most remarkable predictions to emerge out of the exact infinite-dimensional solution of the glass problem is the Gardner transition. Although this transition was first theoretically proposed a generation ago for certain mean-field spin glass models, its materials relevance was only realized when a systematic effort to relate glass formation and jamming was undertaken. A number of nontrivial physical signatures associated with the Gardner transition have since been considered in various areas, from models of structural glasses to constraint satisfaction problems. This perspective surveys these recent advances and discusses the novel research opportunities that arise from them. [ABSTRACT FROM AUTHOR]

A meta-generalized gradient approximation, range-separated double hybrid (DH) density functional with VV10 non-local correlation is presented. The final 14-parameter functional form is determined by screening trillions of candidate fits through a combination of best subset selection, forward stepwise selection, and random sample consensus (RANSAC) outlier detection. The MGCDB84 database of 4986 data points is employed in this work, containing a training set of 870 data points, a validation set of 2964 data points, and a test set of 1152 data points. Following an xDH approach, orbitals from the ωB97M-V density functional are used to compute the second-order perturbation theory correction. The resulting functional, ωB97M(2), is benchmarked against a variety of leading double hybrid density functionals, including B2PLYP-D3(BJ), B2GPPLYP-D3(BJ), ωB97X-2(TQZ), XYG3, PTPSS-D3(0), XYGJ-OS, DSD-PBEP86-D3(BJ), and DSD-PBEPBE-D3(BJ). Encouragingly, the overall performance of ωB97M(2) on nearly 5000 data points clearly surpasses that of all of the tested density functionals. As a Rung 5 density functional, ωB97M(2) completes our family of combinatorially optimized functionals, complementing B97M-V on Rung 3, and ωB97X-V and ωB97M-V on Rung 4. The results suggest that ωB97M(2) has the potential to serve as a powerful predictive tool for accurate and efficient electronic structure calculations of main-group chemistry. [ABSTRACT FROM AUTHOR]

Applications of inorganic scintillators—activated with lanthanide dopants, such as Ce and Eu—are found in diverse fields. As a strict requirement to exhibit scintillation, the 4f ground state (with the electronic configuration of [Xe]4fn 5d0) and 5d1 lowest excited state (with the electronic configuration of [Xe]4fn−1 5d1) levels induced by the activator must lie within the host bandgap. Here we introduce a new machine learning (ML) based search strategy for high-throughput chemical space explorations to discover and design novel inorganic scintillators. Building upon well-known physics-based chemical trends for the host dependent electron binding energies within the 4f and 5d1 energy levels of lanthanide ions and available experimental data, the developed ML model—coupled with knowledge of the vacuum referred valence and conduction band edges computed from first principles—can rapidly and reliably estimate the relative positions of the activator’s energy levels relative to the valence and conduction band edges of any given host chemistry. Using perovskite oxides and elpasolite halides as examples, the presented approach has been demonstrated to be able to (i) capture systematic chemical trends across host chemistries and (ii) effectively screen promising compounds in a high-throughput manner. While a number of other application-specific performance requirements need to be considered for a viable scintillator, the scheme developed here can be a practically useful tool to systematically down-select the most promising candidate materials in a first line of screening for a subsequent in-depth investigation. [ABSTRACT FROM AUTHOR]