A phase field crystal model for materials crystallization in the presence of of nanoscale pores

The present work focuses on the development of a relatively simple phase field crystal model for materials with nanoscale porous inclusions. We found that the pore's main effect is to act as a nucleation agent, promoting crystallization of material at the pore’s interface, followed by micro-structural evolution of the solid in the supercooled liquid. Details of the crystal around the pore are investigated in terms of the pore radius and density of material outside the pore. Moreover, details of the pore-material interface is investigated through the interfacial tension and pressure. Finally, the model is extended to investigate the effect of multiple pores on the kinetics of crystallization.

A Simple Phase-Sensitive Surface Plasmon Resonance Sensor Based on Simultaneous Polarization Measurement Strategy

The SPR phenomenon results in an abrupt change in the optical phase such that one can measure the phase shift of the reflected light as a sensing parameter. Moreover, many studies have demonstrated that the phase changes more acutely than the intensity, leading to a higher sensitivity to the refractive index change. However, currently, the optical phase cannot be measured directly because of its high frequency; therefore, investigators usually have to use complicated techniques for the extraction of phase information. In this study, we propose a simple and effective strategy for measuring the SPR phase shift based on phase-shift interferometry. In this system, the polarization-dependent interference signals are recorded simultaneously by a pixelated polarization camera in a single snapshot. Subsequently, the phase information can be effortlessly acquired by a phase extraction algorithm. Experimentally, the proposed phase-sensitive SPR sensor was successfully applied for the detection of small molecules of glyphosate, which is the most frequently used herbicide worldwide. Additionally, the sensor exhibited a detection limit of 15 ng/mL (0.015 ppm). Regarding its simplicity and effectiveness, we believe that our phase-sensitive SPR system presents a prospective method for acquiring phase signals.

Deep-learning-based recognition of multi-singularity structured light

Structured light with customized topological patterns inspires diverse classical and quantum investigations underpinned by accurate detection techniques. However, the current detection schemes are limited to vortex beams with a simple phase singularity. The precise recognition of general structured light with multiple singularities remains elusive. Here, we report deep learning (DL) framework that can unveil multi-singularity phase structures in an end-to-end manner, after feeding only two intensity patterns upon beam propagation. By outputting the phase directly, rich and intuitive information of twisted photons is unleashed. The DL toolbox can also acquire phases of Laguerre–Gaussian (LG) modes with a single singularity and other general phase objects likewise. Enabled by this DL platform, a phase-based optical secret sharing (OSS) protocol is proposed, which is based on a more general class of multi-singularity modes than conventional LG beams. The OSS protocol features strong security, wealthy state space, and convenient intensity-based measurements. This study opens new avenues for large-capacity communications, laser mode analysis, microscopy, Bose–Einstein condensates characterization, etc.

Facile and versatile ligand analysis method of colloidal quantum dot

Colloidal quantum-dots (QDs) are highly attractive materials for various optoelectronic applications owing to their easy maneuverability, high functionality, wide applicability, and low cost of mass-production. QDs usually consist of two components: the inorganic nano-crystalline particle and organic ligands that passivate the surface of the inorganic particle. The organic component is also critical for tuning electronic properties of QDs as well as solubilizing QDs in various solvents. However, despite extensive effort to understand the chemistry of ligands, it has been challenging to develop an efficient and reliable method for identifying and quantifying ligands on the QD surface. Herein, we developed a novel method of analyzing ligands in a mild yet accurate fashion. We found that oxidizing agents, as a heterogeneous catalyst in a different phase from QDs, can efficiently disrupt the interaction between the inorganic particle and organic ligands, and the subsequent simple phase fractionation step can isolate the ligand-containing phase from the oxidizer-containing phase and the insoluble precipitates. Our novel analysis procedure ensures to minimize the exposure of ligand molecules to oxidizing agents as well as to prepare homogeneous samples that can be readily analyzed by diverse analytical techniques, such as nuclear magnetic resonance spectroscopy and gas-chromatography mass-spectrometry.

Tailoring the Random Lasing Properties by Controlled Phase Separation Process in PMMA:PVK Dye-Doped Polymeric Blends

This article describes the random lasing (RL) phenomenon obtained in a dye-doped, polymeric double-phase system composed of PMMA and PVK polymers. It shows how relative concentrations between mentioned macromolecules can influence lasing parameters of the resulting blends, including obtained emission spectra and threshold conditions. We describe the influence of lasers’ composition on their morphologies and link them with particular RL properties. Our studies reveal that the disorder caused by phase separation can support the RL phenomenon both in the waveguiding and quasi-waveguiding regimes. Changing the relative concentration of polymers enables one to switch between both regimes, which significantly influences threshold conditions, spectral shift, number of lasing modes, and ability to support extended and/or localized modes. Finally, we show that a simple phase separation technique can be used to fabricate efficient materials for RL. Moreover, it enables the tailoring of lasing properties of materials in a relatively wide range at the stage of the laser material fabrication process in a simple way. Therefore, this technique can be seen as a fast, cheap, and easy to perform way of random lasers fabrication.

Explicit asymptotic secret key rate of continuous-variable quantum key distribution with an arbitrary modulation

We establish an analytical lower bound on the asymptotic secret key rate of continuous-variable quantum key distribution with an arbitrary modulation of coherent states. Previously, such bounds were only available for protocols with a Gaussian modulation, and numerical bounds existed in the case of simple phase-shift-keying modulations. The latter bounds were obtained as a solution of convex optimization problems and our new analytical bound matches the results of Ghorai et al. (2019), up to numerical precision. The more relevant case of quadrature amplitude modulation (QAM) could not be analyzed with the previous techniques, due to their large number of coherent states. Our bound shows that relatively small constellation sizes, with say 64 states, are essentially sufficient to obtain a performance close to a true Gaussian modulation and are therefore an attractive solution for large-scale deployment of continuous-variable quantum key distribution. We also derive similar bounds when the modulation consists of arbitrary states, not necessarily pure.

Discovery of complex oxides via automated experiments and data science

The quest to identify materials with tailored properties is increasingly expanding into high-order composition spaces, with a corresponding combinatorial explosion in the number of candidate materials. A key challenge is to discover regions in composition space where materials have novel properties. Traditional predictive models for material properties are not accurate enough to guide the search. Herein, we use high-throughput measurements of optical properties to identify novel regions in three-cation metal oxide composition spaces by identifying compositions whose optical trends cannot be explained by simple phase mixtures. We screen 376,752 distinct compositions from 108 three-cation oxide systems based on the cation elements Mg, Fe, Co, Ni, Cu, Y, In, Sn, Ce, and Ta. Data models for candidate phase diagrams and three-cation compositions with emergent optical properties guide the discovery of materials with complex phase-dependent properties, as demonstrated by the discovery of a Co-Ta-Sn substitutional alloy oxide with tunable transparency, catalytic activity, and stability in strong acid electrolytes. These results required close coupling of data validation to experiment design to generate a reliable end-to-end high-throughput workflow for accelerating scientific discovery.

An Oscillatory Mechanism for Multi-level Storage in Short-term Memory

Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here, we demonstrate a simple phase-locking mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity patterns that encode information not only in their location but also in a discrete set of amplitudes.