Opportunities For Applications Research Articles

Photonic Devices with Multi-Domain Liquid Crystal Structures

Photoalignment by azo dye nanolayers can provide high alignment quality for large-area liquid crystal devices. Application of this technology to active optical elements for signal processing and communications is a hot topic of photonics research. In this article, we review recent demonstrations and performance of liquid crystal photonic devices, discuss the advantages of the proposed technology, and identify challenges and future prospects in the research field of photoaligned multi-domain liquid crystal structures. We believe that the developments discussed here can provide directions for future research and potential opportunities for applications of liquid crystal devices based on multi-domain photoalignment.

Ultra‐Narrow Linewidth Polariton Lasing in Optically Trapped Bose‐Einstein Condensates at Room Temperature

AbstractPolariton lasing via Bose‐Einstein condensation (BEC) provides a peculiar method to achieve low threshold coherent light sources. Until now, the cryogenic operating temperature required for polariton lasers has hampered the development of polaritonics. Here, a novel approach is first reported to realize the ultra‐narrow linewidth polariton lasing under quasi‐3D quantum confinement at room‐temperature (RT). The potential trap landscape is constructed by ring‐shaped optical excitation, wherein the continuum polariton dispersion is modulated into discrete simple harmonic oscillator (SHO) states. The coherent condensation lasing of trapped polaritons occurs beyond the threshold power. Benefiting from the horizontal quantum confinement, the trapped polariton lasing exhibits an ultra‐narrow linewidth (0.7 meV) and excellent quality factor (Q = 3510). Moreover, the second‐order quantum coherence properties of trapped polariton condensation are determined to reveal the quantum phase transition of Bosonic system. The results offer a feasible route for realizing a low‐threshold ultra‐narrow linewidth polariton laser at RT, which significantly facilitates the fabrication of polariton laser and switches on opportunities for future applications.

Web Application for Company Stock Price Prediction

This study contributes to predicting stock prices. In this paper, we have provided a novel machine learning and deep learning technique for stock prediction, which capitalizes on the complex emotional patterns of investors that can be extracted from Twitter data. By joining two separate datasets, such as Twitter sentiments and the associated stock prices, we have applied complex algorithms and evaluated this method, which classifies a user’s sentiment into a positive and negative one. It was possible to address the complexity of investor behavior within the highly unstable stock market environment. One of the most important problems that are encountered by developers is gaining the possibility to properly capture stock price fluctuations in the temporal dimension. It implies the necessity to utilize such reliable evaluation metrics as precision-recall factors for classification purpose and root mean squared error for regression purpose. by using these metrics, the performance of the predictive model can be evaluated in detail, which allows to draw meaningful permanent conclusions within the context of how well it reflects the complex relationship between investor sentiment and market dynamics. The results of the evaluation conducted as part of the process of validating the proposed hypothesis show that, indeed, the predictive accuracy improves significantly from the use of machine learning and deep learning algorithms if paired with Twitter users’ emotional sentiment data. This combination enhances the predictive capacity of the model and provides meaningful insights into how the changes in stock prices are impacted by the sentiment of investors. Moreover, in the process of this study, the explanation and detail consideration of the algorithms for feature engineering and data processing were provided, which stands crucial for increasing the predictive model’s accuracy The study has a valuable implication for both the financial analysis and technical spheres due to the resolution of these methods and presents a model for further research activities in stock prediction. To conclude, this interdisciplinary strategy that combines sentiment analysis and stock prediction not only advances our understanding of the investor behavior but also brings the opportunity for novel applications in the emerging field at the juncture of technology and finance. As a result, the current research sheds light on the intricate connection between the dynamics of the stock market and investor sentiment, thus offering new insights that can better inform predictive modeling research in the financial industry.

Tailored plasmon polariton landscape in graphene/boron nitride patterned heterostructures

Surface plasmon polaritons (SPPs), which are electromagnetic modes representing collective oscillations of charge density coupled with photons, have been extensively studied in graphene. This has provided a solid foundation for understanding SPPs in 2D materials. However, the emergence of wafer-transfer techniques has led to the creation of various quasi-2D van der Waals heterostructures, highlighting certain gaps in our understanding of their optical properties in relation to SPPs. To address this, we analyzed electromagnetic modes in graphene/hexagonal-boron-nitride/graphene heterostructures on a dielectric Al2O3 substrate using the full ab initio RPA optical conductivity tensor. Our theoretical model was validated through comparison with recent experiments measuring evanescent in-phase Dirac and out-of-phase acoustic SPP branches. Furthermore, we investigate how the number of plasmon branches and their dispersion are sensitive to variables such as layer count and charge doping. Notably, we demonstrate that patterning of the topmost graphene into nanoribbons provides efficient Umklapp scattering of the bottommost Dirac plasmon polariton (DP) into the radiative region, resulting in the conversion of the DP into a robust infrared-active plasmon. Additionally, we show that the optical activity of the DP and its hybridization with inherent plasmon resonances in graphene nanoribbons are highly sensitive to the doping of both the topmost and bottommost graphene layers. By elucidating these optical characteristics, we aspire to catalyze further advancements and create new opportunities for innovative applications in photonics and optoelectronic integration.

Poly(aniline‐co‐pyrrole) as Adsorbent for Removal of Pharmaceuticals: Preparation, Characterization, Kinetics, Isotherms and Application on Sample Preparation

AbstractHerein, poly(aniline‐co‐pyrrole) has been synthetized and investigated to adsorb phenylbutazone (PBZ), ceftiofur (CEF) and prednisolone (PRD) in aqueous medium as proof of concept. After proper adsorbent characterization, some studies were carried out in batch process, i. e., contact time, pH, and concentration. The adsorption mechanism has been conducted using kinetic and isothermal models. It was found that the reaction equilibrium was reached in 20 min for all analytes. The best fit for the experimental data were obtained employing the models of dual‐site Langmuir–Freundlich, Fritz–Schlunder and Langmuir, with R2=0.999, 0.952 and 0.974, for PBZ, CEF and PRD, respectively. For PBZ, CEF and PRD, poly(aniline‐co‐pyrrole) provided a Qmax=238.8 mg g−1 and Kmax=0.086 L g−1, Q=0.028 mg g−1 and Kmax=3.258 L g−1, Q=13.66 mg g−1 and KL=0.005 L g−1, respectively. Finally, the copolymer was evaluated in solid phase extraction, which showed recovery around 70 % for PBZ, offering also exciting opportunities for further application in the separation process.

Label Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications.

Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions - like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others have been considered to be waste products - like lipofuscin and advanced glycation end products - which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence these materials have great utility for enabling non-invasive, label-free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, have been applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, we review the applications of label-free autofluorophore assessment for clinical and health-research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring and tissue assessment - fields which greatly benefit from non-invasive methodologies capable of continuous, in vivo characterisation. This article is protected by copyright. All rights reserved.

Estimation of magnetic levitation and lateral forces in MgB2 superconducting bulks with various dimensional sizes using artificial intelligence techniques

Abstract The advent of superconducting bulks, because of their compactness and performance, offers new perspectives and opportunities in many applications and sectors, such as magnetic field shielding, motors/generators, NMR/MRI, magnetic bearings, flywheel energy storage, Maglev trains, among others. The investigation and characterization of bulks typically relies on time-consuming and expensive experimental campaigns; hence the development of effective surrogate models would considerably speed up the research progress around them. In this study, we have first produced an experimental dataset with the levitation and lateral forces between different MgB2 bulks and one permanent magnet under different operating conditions. Next, we have exploited the dataset to develop surrogate models based on Artificial Intelligence (AI) techniques, namely Extremely Gradient Boosting (XGBoost), Support Vector Machine Regressor (SVR), and Kernel Ridge Regression (KRR). After the tuning of the hyperparameters of the AI models, the results demonstrated that SVR is the superior technique and can predict levitation and lateral forces with a worst-case accuracy scenario 99.86% in terms of goodness of fit to experimental data. Moreover, the response time of these models for prediction of new datapoints is ultra-fast.

Characterization of Complex Proteoform Mixtures by Online Nanoflow Ion-Exchange Chromatography-Native Mass Spectrometry.

The characterization of proteins and complexes in biological systems is essential to establish their critical properties and to understand their unique functions in a plethora of bioprocesses. However, it is highly difficult to analyze low levels of intact proteins in their native states (especially those exceeding 30 kDa) with liquid chromatography (LC)-mass spectrometry (MS). Herein, we describe for the first time the use of nanoflow ion-exchange chromatography directly coupled with native MS to resolve mixtures of intact proteins. Reference proteins and protein complexes with molecular weights between 10 and 150 kDa and a model cell lysate were separated using a salt-mediated pH gradient method with volatile additives. The method allowed for low detection limits (0.22 pmol of monoclonal antibodies), while proteins presented nondenatured MS (low number of charges and limited charge state distributions), and the oligomeric state of the complexes analyzed was mostly kept. Excellent chromatographic separations including the resolution of different proteoforms of large proteins (>140 kDa) and a peak capacity of 82 in a 30 min gradient were obtained. The proposed setup and workflows show great potential for analyzing diverse proteoforms in native top-down proteomics, opening unprecedented opportunities for clinical studies and other sample-limited applications.

Unlocking the Potential of CO2 Capture: A Synergistic Hybridization Strategy for Polymeric Hydrogels with Tunable Physicochemical Properties.

Unlocking CO2 capture potential remains a complex and challenging endeavor. Here, a blueprint is crafted for optimizing materials through CO2 capture and developing a synergistic hybridization strategy that involves synthesizing CO2-responsive hydrogels by integrating polymeric networks interpenetrated with polyethyleneimine (PEI) chains and inorganic CaCl2. Diverging from conventional CO2 absorbents, which typically serve a singular function in CO2 capture, these hybrid PEAC hydrogels additionally harness its presence to tune their optical and mechanical properties once interacting with CO2. Such synergistic functions entail two significant steps: (i) rapid CO2-fixing through PEI chains to generate abundant carbamic acid and carbamate species and (ii) mineralization via CaCl2 to induce the formation of CaCO3 micro-crystals within the hydrogel matrix. Due to the reversible bonding, the PEAC hydrogels enable the decoupling of CO2 through an acid fumigation treatment or a heating process, achieving dynamic CO2 capture-release cycles up to 8 times. Furthermore, the polyethyleneimine-acrylamide-calcium chloride (PEAC) hydrogel exhibits varying antibacterial attributes and high interfacial adhesive strength, which can be modulated by fine-tuning the compositions of PEI and CaCl2. This versatility underscores the promising potential of PEAC hydrogels, which not only unlocks CO2 capture capabilities but also offers opportunities in diverse biological and biomedical applications.

A Comprehensive Review of Plant-Based Biopolymers as Viscosity-Modifying Admixtures in Cement-Based Materials

As the construction industry is facing the challenge of meeting the ever-increasing demand for environmentally friendly and durable concrete, the role of viscosity-modifying admixtures (VMAs) has become increasingly essential to improve the rheological properties, stability, and mechanical properties of concrete. Additionally, natural polymers are ever evolving, offering multiple opportunities for innovative applications and sustainable solutions. This comprehensive review delves into the historical context and classifications of VMAs, accentuating their impact in enhancing the rheological properties, stability, and mechanical properties of concrete. Emphasis is placed on the environmental impact of synthetic VMAs, promoting the exploration of sustainable alternatives derived from plant-based biopolymers. Indeed, biopolymers, such as cellulose, starch, alginate, pectin, and carrageenan are considered in this paper, focusing on understanding their efficacy in improving concrete properties while enhancing the environmental sustainability within the concrete.

Engineered 3D Vortex Array with Customized Energy and Topological Charges for Multi‐View Display

AbstractArrays of multiple vortex beams enhance parallel processing capabilities from particle manipulation to information communication. However, the spatial position, topological charge, and energy parameters of the vortex beams within the array have yet to be precisely controlled, posing significant challenges to the realization of multi‐view 3D Orbital Angular Momentum (OAM) display using vortex arrays as information carriers. To address this issue, a method for generating vortex arrays based on a phase‐only hologram, customizing the array by using the energy and OAM spectrum of each vortex beam as the loss function is developed. Experimental results indicate that a 2D array generates 100 vortex beams in the spatial frequency domain, while a 3D array in the Fresnel zone produces 252 vortex beams across 7 planes, each with 36 unprecedentedly controllable energy and topological charge vortex beams. Subsequently, images of 4 views using the 3D vortex arrays and decoded through coordinate transformation to achieve a multi‐view 3D OAM display are encoded. The results demonstrate imaging quality with Mean Peak Signal‐to‐Noise Ratio (MPSNR) of 12.7, 13.0, 13.4, and 12.2 dB in 4 views, respectively, offering promising opportunities for applications in 3D optical manipulation, high‐capacity communication, and 3D OAM holography.

Laser-driven pointed acceleration of electrons with preformed plasma lens

The simultaneous laser-driven acceleration and angular manipulation of the fast electron beam are experimentally demonstrated. The bunch of multi-MeV energy charged particles is generated during the propagation of the femtosecond laser pulse through the near-critical plasma slab accompanied by plasma channeling. Plasma is formed by the controlled breakdown of a thin-tape target by a powerful nanosecond prepulse. The electron beam pointing approach is based on the refraction of a laser pulse in the presence of a strong radial density gradient in the breakdown of the tape with a small displacement of the femtosecond laser beam relative to the breakdown symmetry axis. A shift of several micrometers makes it possible to achieve beam deflection by an angle up to 10° with acceptable beam charge and spectrum conservation. This opens up opportunities for applications for scanning objects with an electron beam and the multistage electron beam energy gain in consecutive laser accelerators without bulk magnetic optics for particles. Experimental findings are supported by numerical particle-in-cell calculations of laser-plasma acceleration and hydrodynamic simulations. Published by the American Physical Society 2024

Near‐Infrared Metalens Empowered Dual‐Mode High Resolution and Large FOV Microscope

AbstractThe spiral phase contrast microscope can clearly distinguish the morphological information of the low contrast objects (i.e., biological samples) owing to the isotropic edge‐enhancement effect, while the bright field microscope can image the overall morphology of amplitude objects. However, the imaging resolution, magnification, and field of view of conventional spiral phase contrast microscopes based on 4f filtering configuration are limited by the system's complexity. Here, compact dual‐mode microscopes working at near‐infrared using the engineered metalens are reported, which can be tuned between the spiral phase contrast imaging and bright field imaging by polarization control. The metalens combine the high‐resolution objective lens and polarization‐controlled phase filter into a single‐layer nanofins array. Two infinity‐corrected microscope systems are demonstrated to achieve subwavelength resolution (0.7λ), large magnification (58X), and large field of view (600 × 800 µm). Unstained onion epidermal is imaged by the microscope to show the dual‐mode imaging ability for the biological sample. Finally, a singlet dual‐mode microscope system is demonstrated to show the edge‐detection application for industrial standards. These results can open new opportunities in applications of biological imaging, industrial machine vision, and semiconductor inspection.

2D Materials‐Based Pulsed Solid‐State Laser: Status and Prospect

AbstractPulsed solid‐state lasers comprise 2D materials as saturable absorbers that contain transparent windows of the atmosphere and characteristic fingerprint spectra of several vital molecules that are significant in various applications and research. Over the past few decades, significant progress has been made in the development of narrow pulse width, high energy, high average output power, high efficiency, and simple construction of passively Q‐switched and mode‐locked lasers with 2D materials as saturable absorbers. This review summarizes the development of 2D materials, including graphene, transition metal dichalcogenides, black phosphorus, topological insulators, and MXenes, as modulator devices for solid‐state lasers owing to their broadband operation, excellent nonlinear optical response, low recovery time, ultrafast dynamic processing, and easy fabrication. Then, some new emerging and representative applications of pulsed solid‐state lasers are introduced and illustrated such as laser surgery, material processing, and lidar. Finally, future challenges and perspectives of pulsed solid‐state lasers with 2D materials‐based saturable absorbers are analyzed and addressed. The rapid development of pulsed solid‐state lasers with the continuous improvement of modulation technology is expected to expand opportunities for application in industry, scientific, medical, and other areas.

Multi-channel polarization manipulation based on graphene for encryption communication

Wave-based cryptography, at the vanguard of advancing technologies in advanced information science, is essential for establishing a diverse array of secure cryptographic platforms. The realization of these platforms hinges on the intelligent application of multiplexing techniques, seamlessly combined with appropriate metasurface technology. Nevertheless, existing multi-channel encryption technologies based on metasurfaces face challenges related to information leakage during partial channel decoding processes. In this paper, we present a reprogrammable metasurface for polarization modulation. This metasurface not only allows for the arbitrary customization of linearly polarized reflected waves but also enables real-time amplitude modulation. Here, relying on polarization amplitude control, a fully secure communication protocol is developed precisely in the terahertz (THz) spectrum to achieve real-time information encryption based on polarization modulation metasurfaces where access to information is highly restricted. The proposed metasurface employs the double random phase encryption (DRPE) algorithm for information encryption. It transmits the encrypted data through different polarization channels using two graphene nanoribbons, exclusively controlled by external biasing conditions. Various encryption scenarios have been outlined to fortify information protection against potential eavesdroppers. The simulated results show that this unique technology for hiding images by manipulating the polarization of the reflected wave provides new opportunities for various applications, including encryption, THz communications, THz secure data storage, and imaging.

Highly Stable MOF-Type Lead Halide Luminescent Ferroelectrics.

Lead halide molecular ferroelectrics represent an important class of luminescent ferroelectrics, distinguished by their high chemical and structural tunability, excellent processability and distinctive luminescent characteristics. However, their inherent instability, prone to decomposition upon exposure to moisture and light, hinders their broader ferroelectric applications. Herein, for the first time, we present a series of isoreticular metal-organic framework (MOF)-type lead halide luminescent ferroelectrics, demonstrating exceptional robustness under ambient conditions for at least 15 months and even when subjected to aqueous boiling conditions. Unlike conventional metal-oxo secondary building units (SBUs) in MOFs adopting highly centrosymmetric structure with limited structural distortion, our lead halide-based MOFs occupy structurally deformable [Pb2X]+ (X=Cl-/Br-/I-) SBUs that facilitate a c-axis-biased displacement of Pb2+ centers and substantially contribute to thermoinducible structural transformation. Importantly, this class of MOF-type lead halide ferroelectrics undergo ferroelectric-to-paraelectric phase transitions with remarkably high Curie temperature of up to 505 K, superior to most of molecular ferroelectrics. Moreover, the covalent bonding between phosphorescent organic component and the light-harvesting inorganic component achieves efficient spin-orbit coupling and intersystem crossing, resulting in long-lived afterglow emission. The compelling combination of high stability, ferroelectricity and afterglow emission exhibited by lead halide MOFs opens up many potential opportunities in energy-conversion applications.

Effect of Soy Protein Products on Growth and Metabolism of Bacillus subtilis, Streptococcus lactis, and Streptomyces clavuligerus.

Microbial nitrogen sources are promising, and soy protein as a plant-based nitrogen source has absolute advantages in creating microbial culture medium in terms of renewability, eco-friendliness, and greater safety. Soy protein is rich in variety due to different extraction technologies and significantly different in the cell growth and metabolism of microorganisms as nitrogen source. Therefore, different soy proteins (soy meal powder, SMP; soy peptone, SP; soy protein concentrate, SPC; soy protein isolate, SPI; and soy protein hydrolysate, SPH) were used as nitrogen sources to culture Bacillus subtilis, Streptococcus lactis, and Streptomyces clavuligerus to evaluate the suitable soy nitrogen sources of the above strains. The results showed that B. subtilis had the highest bacteria density in SMP medium; S. lactis had the highest bacteria density in SPI medium; and S. clavuligerus had the highest PMV in SPI medium. Nattokinase activity was the highest in SP medium; the bacteriostatic effect of nisin was the best in SPI medium; and the clavulanic acid concentration was the highest in SMP medium. Based on analyzing the correlation between the nutritional composition and growth metabolism of the strains, the results indicated that the protein content and amino acid composition were the key factors influencing the cell growth and metabolism of the strains. These findings present a new, high-value application opportunity for soybean protein.

Optical vectorial-mode parity Hall effect: a case study with cylindrical vector beams

The vectorial optical field (VOF) assumes a pivotal role in light-matter interactions. Beyond its inherent polarization topology, the VOF also encompasses an intrinsic degree of freedom associated with parity (even or odd), corresponding to a pair of degenerate orthogonal modes. However, previous research has not delved into the simultaneous manipulation of both even and odd parities. In this study, we introduce and validate the previously unexplored parity Hall effect for vectorial modes using a metasurface design. Our focus lies on a cylindrical vector beam (CVB) as a representative case. Through the tailored metasurface, we effectively separate two degenerate CVBs with distinct parities in divergent directions, akin to the observed spin states split in the spin Hall effect. Additionally, we provide experimental evidence showcasing the capabilities of this effect in multi-order CVB demultiplexing and parity-demultiplexed CVB-encoded holography. This effect unveils promising opportunities for various applications, including optical communication and imaging.

Microwave irradiation-induced yield enhancement of coconut shell biomass-derived graphene-like material

This paper reports a new strategy (rapid and selective microwave irradiation) to achieve an improved yield of graphene-like material derived from coconut shell biomass. The influence of various microwave irradiation (MWI) powers (80, 240, and 400 W) treatment on the crystalline structures, morphology, and electrochemical performance of the produced samples was determined and compared with the virgin-untreated specimen. The obtained samples were analyzed using varied analytical techniques. The FESEM images of the irradiated samples revealed the existence of graphene-like morphologies accompanied by some thin and transparent sheets. The sample at 80 W displayed the best quality with the highest yield, improving the carbon content, reducing the oxygen functional groups, and increasing the BET-specific surface area by as much as 1238.48 m2/g. The electrochemical properties of the sample treated at 80 W (optimum MWI power treatment) exhibited rectangular curves against scanning speeds, indicating an ideal capacitive behaviour called electric double-layer capacitance (EDLC). It is asserted that the proposed systematic and eco-friendly approach in obtaining the high-performance graphene-like material at low cost may open up sundry opportunities for practical applications, leading towards sustainable development.

Preparations and Thermal Properties of PDMS-AlN-Al2O3 Composites through the Incorporation of Poly(Catechol-Amine)-Modified Boron Nitride Nanotubes

As one of the emerging nanomaterials, boron nitride nanotubes (BNNTs) provide promising opportunities for diverse applications due to their unique properties, such as high thermal conductivity, immense inertness, and high-temperature durability, while the instability of BNNTs due to their high surface induces agglomerates susceptible to the loss of their advantages. Therefore, the proper functionalization of BNNTs is crucial to highlight their fundamental characteristics. Herein, a simplistic low-cost approach of BNNT surface modification through catechol-polyamine (CAPA) interfacial polymerization is postulated to improve its dispersibility on the polymeric matrix. The modified BNNT was assimilated as a filler additive with AlN/Al2O3 filling materials in a PDMS polymeric matrix to prepare a thermal interface material (TIM). The resulting composite exhibits a heightened isotropic thermal conductivity of 8.10 W/mK, which is a ~47.27% increase compared to pristine composite 5.50 W/mK, and this can be ascribed to the improved BNNT dispersion forming interconnected phonon pathways and the thermal interface resistance reduction due to its augmented compatibility with the polymeric matrix. Moreover, the fabricated composite manifests a fire resistance improvement of ~10% in LOI relative to the neat composite sample, which can be correlated to the thermal stability shift in the TGA and DTA data. An enhancement in thermal permanence is stipulated due to a melting point (Tm) shift of ∼38.5 °C upon the integration of BNNT-CAPA. This improvement can be associated with the good distribution and adhesion of BNNT-CAPA in the polymeric matrix, integrated with its inherent thermal stability, good charring capability, and free radical scavenging effect due to the presence of CAPA on its surface. This study offers new insights into BNNT utilization and its corresponding incorporation into the polymeric matrix, which provides a prospective direction in the preparation of multifunctional materials for electric devices.