Dielectric response of a polar fluid trapped in a spherical nanocavity

We present extensive Molecular Dynamics simulation results for the structure, static and dynamical response of a droplet of 1000 soft spheres carrying extended dipoles and confined to spherical cavities of radii $R=2.5$, 3, and 4 nm embedded in a dielectric continuum of permittivity $\epsilon' \geq 1$. The polarisation of the external medium by the charge distribution inside the cavity is accounted for by appropriate image charges. We focus on the influence of the external permittivity $\epsilon'$ on the static and dynamic properties of the confined fluid. The density profile and local orientational order parameter of the dipoles turn out to be remarkably insensitive to $\epsilon'$. Permittivity profiles $\epsilon(r)$ inside the spherical cavity are calculated from a generalised Kirkwood formula. These profiles oscillate in phase with the density profiles and go to a ``bulk'' value $\epsilon_b$ away from the confining surface; $\epsilon_b$ is only weakly dependent on $\epsilon'$, except for $\epsilon' = 1$ (vacuum), and is strongly reduced compared to the permittivity of a uniform (bulk) fluid under comparable thermodynamic conditions. The dynamic relaxation of the total dipole moment of the sample is found to be strongly dependent on $\epsilon'$, and to exhibit oscillatory behaviour when $\epsilon'=1$; the relaxation is an order of magnitude faster than in the bulk. The complex frequency-dependent permittivity $\epsilon(\omega)$ is sensitive to $\epsilon'$ at low frequencies, and the zero frequency limit $\epsilon(\omega=0)$ is systematically lower than the ``bulk'' value $\epsilon_b$ of the static primitivity.Comment: 12 pages including 17 figure

On-chip broadband nonreciprocal light storage

Breaking the symmetry between forward- and backward-propagating optical modes is of fundamental scientific interest and enables crucial functionalities, such as isolators, circulators, and duplex communication systems. Although there has been progress in achieving optical isolation on-chip, integrated broadband nonreciprocal signal processing functionalities that enable transmitting and receiving via the same low-loss planar waveguide, without altering the frequency or mode of the signal, remain elusive. Here, we demonstrate a nonreciprocal delay scheme based on the unidirectional transfer of optical data pulses to acoustic waves in a chip-based integration platform. We experimentally demonstrate that this scheme is not impacted by simultaneously counterpropagating optical signals. Furthermore, we achieve a bandwidth more than an order of magnitude broader than the intrinsic optoacoustic linewidth, linear operation for a wide range of signal powers, and importantly, show that this scheme is wavelength preserving and avoids complicated multimode structures

Equilibrium solvation in quadrupolar solvents

We present a microscopic theory of equilibrium solvation in solvents with zero dipole moment and non-zero quadrupole moment (quadrupolar solvents). The theory is formulated in terms of autocorrelation functions of the quadrupolar polarization (structure factors). It can be therefore applied to an arbitrary dense quadrupolar solvent for which the structure factors are defined. We formulate a simple analytical perturbation treatment for the structure factors. The solute is described by coordinates, radii, and partial charges of constituent atoms. The theory is tested on Monte Carlo simulations of solvation in model quadrupolar solvents. It is also applied to the calculation of the activation barrier of electron transfer reactions in a cleft-shaped donor-acceptor complex dissolved in benzene with the structure factors of quadrupolar polarization obtained from Molecular Dynamics simulations.Comment: Submitted to J. Chem. Phys., 20 pages and 13 figure

Coherently refreshed acoustic phonons for extended light storage

Acoustic waves can serve as memory for optical information, however, acoustic phonons in the GHz regime decay on the nanosecond timescale. Usually this is dominated by intrinsic acoustic loss due to inelastic scattering of the acoustic waves and thermal phonons. Here we show a way to counteract the intrinsic acoustic decay of the phonons in a waveguide by resonantly reinforcing the acoustic wave via synchronized optical pulses. This scheme overcomes the previous constraints of phonon-based optical signal processing for light storage and memory. We experimentally demonstrate on-chip storage up to 40 ns, four times the intrinsic acoustic lifetime in the waveguide. We confirm the coherence of the scheme by detecting the phase of the delayed optical signal after 40 ns using homodyne detection. Through theoretical considerations we anticipate that this concept allows for storage times up to microseconds within realistic experimental limitations while maintaining a GHz bandwidth of the optical signal. The refreshed phonon-based light storage removes the usual bandwidth-delay product limitations of e.g. slow-light schemes

Smartphone placement within vehicles

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordSmartphone-based driver monitoring is quickly gaining ground as a feasible alternative to competing in-vehicle and aftermarket solutions. Currently the main challenges for data analysts studying smartphone-based driving data stem from the mobility of the smartphone. In this paper, we use kernel-based k-means clustering to infer the placement of smartphones within vehicles. The trip segments are mapped into fifteen different placement clusters. As a part of the presented framework, we discuss practical considerations concerning e.g., trip segmentation, cluster initialization, and parameter selection. The proposed method is evaluated on more than 10 000 kilometers of driving data collected from approximately 200 drivers. To validate the interpretation of the clusters, we compare the data associated with different clusters and relate the results to real-world knowledge of driving behavior. The clusters associated with the label “Held by hand” are shown to display high gyroscope variances, low maximum speeds, low correlations between the measurements from smartphone-embedded and vehicle-fixed accelerometers, and short segment durations

Ready Student One: Exploring the predictors of student learning in virtual reality

Immersive virtual reality (VR) has enormous potential for education, but classroom resources are limited. Thus, it is important to identify whether and when VR provides sufficient advantages over other modes of learning to justify its deployment. In a between-subjects experiment, we compared three methods of teaching Moon phases (a hands-on activity, VR, and a desktop simulation) and measured student improvement on existing learning and attitudinal measures. While a substantial majority of students preferred the VR experience, we found no significant differences in learning between conditions. However, we found differences between conditions based on gender, which was highly correlated with experience with video games. These differences may indicate certain groups have an advantage in the VR setting.Comment: 28 pages, 7 figures, 4 tables. Published in PLOS ONE March 25, 202

Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we present a new machine-learning method, critical random networks (CRNs), for predicting one-dimensional structures, and apply it, with position-specific scoring matrices, to the prediction of secondary structures (SS), contact numbers (CN), and residue-wise contact orders (RWCO). The present method achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS prediction is comparable to other state-of-the-art methods, and that of the CN prediction is a significant improvement over previous methods. We give a detailed formulation of critical random networks-based prediction scheme, and examine the context-dependence of prediction accuracies. In order to study the nonlinear and multi-body effects, we compare the CRNs-based method with a purely linear method based on position-specific scoring matrices. Although not superior to the CRNs-based method, the surprisingly good accuracy achieved by the linear method highlights the difficulty in extracting structural features of higher order from amino acid sequence beyond that provided by the position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for publication in BIOPHYSIC