Challenges of modeling nanostructured materials for photocatalytic water splitting.

Understanding the water splitting mechanism in photocatalysis is a rewarding goal as it will allow producing clean fuel for a sustainable life in the future. However, identifying the photocatalytic mechanisms by modeling photoactive nanoparticles requires sophisticated computational techniques based on multiscale modeling. In this review, we will survey the strengths and drawbacks of currently available theoretical methods at different length and accuracy scales. Understanding the surface-active site through Density Functional Theory (DFT) using new, more accurate exchange-correlation functionals plays a key role for surface engineering. Larger scale dynamics of the catalyst/electrolyte interface can be treated with Molecular Dynamics albeit there is a need for more generalizations of force fields. Monte Carlo and Continuum Modeling techniques are so far not the prominent path for modeling water splitting but interest is growing due to the lower computational cost and the feasibility to compare the modeling outcome directly to experimental data. The future challenges in modeling complex nano-photocatalysts involve combining different methods in a hierarchical way so that resources are spent wisely at each length scale, as well as accounting for excited states chemistry that is important for photocatalysis, a path that will bring devices closer to the theoretical limit of photocatalytic efficiency.

Spectral forecast: A general purpose prediction model as an alternative to classical neural networks.

Here, we describe a general-purpose prediction model. Our approach requires three matrices of equal size and uses two equations to determine the behavior against two possible outcomes. We use an example based on photon-pixel coupling data to show that in humans, this solution can indicate the predisposition to disease. An implementation of this model is made available in the supplementary material.

Use of a Novel Resistive Strain Sensor Approach in an Experimental and Theoretical Study Concerning Large Spherical Storage Tank Structure Behavior During Its Operational Life and Pressure Tests.

This paper introduces a new method for the use of tensor-resistive sensors in large spherical storage tank equipment (over 12,000-mm diameters). We did an experiment with 19 petroleum or ammonia product sphere-shaped storage tanks with volumes of 1000 and 1800 cubic meters, respectively. The existing literature only contains experiments based on sensors for tanks with diameters no larger than 600 mm. Based on a number of resistive strain sensor measurements on large spherical pressurized vessels regarding structural integrity assessment, the present paper is focused on the comparison between "real-life" obtained sensor data versus finite element method (FEM) simulation results. The present paper is structured in three parts and examines innovative directions: the use of the classic tensor-resistive sensors in a new approach concerning large structural equipment; an original 3D modeling method with the help of the FEM; and conclusions with possible implications on the regulations, design, or maintenance as a result of the attempt of mutual validation of the new methods previously mentioned.

Contributions to the Dynamic Regime Behavior of a Bionic Leg Prosthesis.

The purpose of prosthetic devices is to reproduce the angular-torque profile of a healthy human during locomotion. A lightweight and energy-efficient joint is capable of decreasing the peak actuator power and/or power consumption per gait cycle, while adequately meeting profile-matching constraints. The aim of this study was to highlight the dynamic characteristics of a bionic leg with electric actuators with rotational movement. Three-dimensional (3D)-printing technology was used to create the leg, and servomotors were used for the joints. A stepper motor was used for horizontal movement. For better numerical simulation of the printed model, three mechanical tests were carried out (tension, compression, and bending), based on which the main mechanical characteristics necessary for the numerical simulation were obtained. For the experimental model made, the dynamic stresses could be determined, which highlights the fact that, under the conditions given for the experimental model, the prosthesis resists.

An Efficient System for Eye Movement Desensitization and Reprocessing (EMDR) Therapy: A Pilot Study.

In this paper, we describe an actuator-based EMDR (eye movement desensitization and reprocessing) virtual assistant system that can be used for the treatment of participants with traumatic memories. EMDR is a psychological therapy designed to treat emotional distress caused by a traumatic event from the past, most frequently in post-traumatic stress disorder treatment. We implemented a system based on video, tactile, and audio actuators which includes an artificial intelligence chatbot, making the system capable of acting autonomously. We tested the system on a sample of 31 participants. Our results showed the efficiency of the EMDR virtual assistant system in reducing anxiety, distress, and negative cognitions and emotions associated with the traumatic memory. There are no such systems reported in the existing literature. Through the present research, we fill this gap by describing a system that can be used by patients with traumatic memories.

Reconstruction of atomistic details from coarse-grained structures.

We present an algorithm to reconstruct atomistic structures from their corresponding coarse-grained (CG) representations and its implementation into the freely available molecular dynamics (MD) program package GROMACS. The central part of the algorithm is a simulated annealing MD simulation in which the CG and atomistic structures are coupled via restraints. A number of examples demonstrate the application of the reconstruction procedure to obtain low-energy atomistic structural ensembles from their CG counterparts. We reconstructed individual molecules in vacuo (NCQ tripeptide, dipalmitoylphosphatidylcholine, and cholesterol), bulk water, and a WALP transmembrane peptide embedded in a solvated lipid bilayer. The first examples serve to optimize the parameters for the reconstruction procedure, whereas the latter examples illustrate the applicability to condensed-phase biomolecular systems.

Advances of unilateral mobile NMR in nondestructive materials testing.

Unilateral mobile NMR employs portable instrumentation with sensors, which are applied to the object from one side. Based on the principles of well-logging NMR, a hand-held sensor, the NMR-MOUSE (MObile Universal Surface Explorer) has been developed for nondestructive materials testing. In the following, a number of new applications of unilateral NMR in materials science are reviewed. They are the state assessment of polyethylene pipes, the characterization of wood, the in situ evaluation of stone conservation treatment, high-resolution profiling of rubber tubes and 2-D imaging for defect analysis in rubber products.

Improved Angle Potentials for Coarse-Grained Molecular Dynamics Simulations.

Potentials routinely used in atomistic molecular dynamics simulations are not always suitable for modeling systems at coarse-grained resolution. For example, in the calculation of traditional torsion angle potentials, numerical instability is often encountered in the case of very flexible molecules. To improve the stability and accuracy of coarse-grained molecular dynamics simulations, we propose two approaches. The first makes use of improved forms for the angle potentials: the restricted bending (ReB) potential prevents torsion angles from visiting unstable or unphysical configurations and the combined bending-torsion (CBT) potential smoothly flattens the interactions when such configurations are sampled. In the second approach, dummy-assisted dihedral (DAD), the torsion potential is applied differently: instead of acting directly on the beads, it acts on virtual beads, bound to the real ones. For simple geometrical reasons, the unstable region is excluded from the accessible conformational space. The benefits of the new approaches are demonstrated in simulations of polyethylene glycol (PEG), polystyrene (PS), and polypeptide molecules described by the MARTINI coarse-grained force field. The new potentials are implemented in an in-house version of the Gromacs package, publicly available.

Membrane poration by antimicrobial peptides combining atomistic and coarse-grained descriptions.

Antimicrobial peptides (AMPs) comprise a large family of peptides that include small cationic peptides, such as magainins, which permeabilize lipid membranes. Previous atomistic level simulations of magainin-H2 peptides show that they act by forming toroidal transmembrane pores. However, due to the atomistic level of description, these simulations were necessarily limited to small system sizes and sub-microsecond time scales. Here, we study the long-time relaxation properties of these pores by evolving the systems using a coarse-grain (CG) description. The disordered nature and the topology of the atomistic pores are maintained at the CG level. The peptides sample different orientations but at any given time, only a few peptides insert into the pore. Key states observed at the CG level are subsequently back-transformed to the atomistic level using a resolution-transformation protocol. The configurations sampled at the CG level are stable in the atomistic simulation. The effect of helicity on pore stability is investigated at the CG level and we find that partial helicity is required to form stable pores. We also show that the current CG scheme can be used to study spontaneous poration by magainin-H2 peptides. Overall, our simulations provide a multi-scale view of a fundamental biophysical membrane process involving a complex interplay between peptides and lipids.