Uniform Distribution Research Articles

Succinct Quantum Testers for Closeness and k-Wise Uniformity of Probability Distributions

Succinct Quantum Testers for Closeness and <i>k</i>-Wise Uniformity of Probability Distributions

In Ukrainian

Due to the variety of their forms and properties, silver nanoparticles (AgNPs) are promising for obtaining nanomaterials with various functional applications. Today, regardless of the method of obtaining AgNPs, there is a problem of stabilizing their surface to prevent aggregation, which significantly reduces their activity and prevents uniform distribution during the preparation of nanomaterials. The aim of this work was the synthesis of silver nanoparticles using an oligomeric ionic liquid (OIL) and the study of their structure and antimicrobial properties. In this work, for the first time, an anionic OIL with a hyperbranched structure developed by us was used as a surface stabilizer in the synthesis of AgNPs. The synthesis of AgNPs was carried out by the reduction of Ag ions in the composition of AgNO3 with trisodium citrate in the presence of this OIL. Using the methods ofUV-vis and FTIR spectroscopy, X-ray analysis, electron microscopy and the disc-diffusion method, the peculiarities of the structural organization of AgNPs and their antimicrobial properties were studied. UV-visible spectroscopy data indicate the formation of silver nanoparticles and their spherical or quasi-spherical shape. It was found that there are adsorbed ionic and carbonyl groups on the surface of the formed AgNPs, and the formation of host-guest complexes between OIL and silver ions was revealed using FTIR. The formation of AgNPs and complexes between OIL and silver ions is also confirmed by X-ray diffraction. According to electron microscopy, the size of the synthesized nanoparticles varies from 5 to 16 nm, with an average value of 10.2 nm. This average value is very close to the value of 9.3 nm obtained from the results of X-ray analysis. The synthesized silver nanoparticles showed a very high antimicrobial activity against C. albicans fungi, while the width of the inhibition zone (d) was 34 mm. Also, the AgNPs powder shows very high activity against gram-positive bacteria S. aureus (d = 30 mm) and gram-negative bacteria E. coli (d = 12 mm). The approach developed by us to the synthesis of AgNPs in the presence of OIL as a surface stabilizer with certain functionalization of the latter opens up new opportunities in the synthesis of AgNPs and the preparation of highly dispersed related systems, including functionalized nanocomposite polymer materials with antimicrobial properties.

Stellar spectral template library construction based on generative adversarial networks

Stellar spectral template libraries play an important role in the automated analysis of stellar spectra. Synthetic template libraries cover a very large parameter space but suffer from poor matching with observed spectra. In this study, we propose a synthetic-to-observed spectral translation (SOST) method based on generative adversarial networks. The SOST method is able to calibrate synthetic spectra by converting them to the corresponding observed spectra. We applied this method to Kurucz synthetic spectra and observed spectra data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). After that, we constructed a stellar spectral library with uniform and broad parameter distributions using the SOST-corrected Kurucz synthetic spectra. Our stellar spectral template library contains 2431 spectra spanning a parameter space of 3500–8000 K for effective temperature (Teff), 0.0–5.0 dex for surface gravity (log g), and −2.0–0.5 dex for metallicity ([Fe/H]). The spectra in the library have a resolution of R ∼ 1800 and cover the wavelength range 3900–8700 Å. In order to verify the accuracy of this template library, we used the template library and the template-matching algorithm to derive the parameters of the PASTEL database. Compared to measurements using the original synthetic template library, the accuracies of the three parameters, Teff, log g, and [Fe/H], are improved, from 140 K, 0.31 dex, and 0.21 dex to 121 K, 0.26 dex, and 0.13 dex, respectively. In addition, we re-parameterised more than six million stellar spectra released by LAMOST DR8.

Stochastic characterization of navigation strategies in an automated variant of the Barnes maze.

Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate towards a goal vestibule from a random start vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial, and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions. They closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences, revealing a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every six vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.

Explainable finite mixture of mixtures of bounded asymmetric generalized Gaussian and Uniform distributions learning for energy demand management

We introduce a mixture of mixtures of bounded asymmetric generalized Gaussian and uniform distributions. Based on this framework, we propose model-based classification and model-based clustering algorithms. We develop an objective function for the minimum message length (MML) model selection criterion to discover the optimal number of clusters for the unsupervised approach of our proposed model. Given the crucial attention received by Explainable AI (XAI) in recent years, we introduce a method to interpret the predictions obtained from the proposed model in both learning settings by defining their boundaries in terms of the crucial features. Integrating Explainability within our proposed algorithm increases the credibility of the algorithm’s predictions since it would be explainable to the user’s perspective through simple If-Then statements using a small binary decision tree. In this paper, the proposed algorithm proves its reliability and superiority to several state-of-the-art machine learning algorithms within the following real-world applications: fault detection and diagnosis (FDD) in chillers, occupancy estimation and categorization of residential energy consumers.

Smoothed Analysis with Adaptive Adversaries

We prove novel algorithmic guarantees for several online problems in the smoothed analysis model. In this model, at each time step an adversary chooses an input distribution with density function bounded above pointwise by \(\tfrac{1}{\sigma }\) times that of the uniform distribution; nature then samples an input from this distribution. Here, σ is a parameter that interpolates between the extremes of worst-case and average case analysis. Crucially, our results hold for adaptive adversaries that can base their choice of input distribution on the decisions of the algorithm and the realizations of the inputs in the previous time steps. An adaptive adversary can nontrivially correlate inputs at different time steps with each other and with the algorithm’s current state; this appears to rule out the standard proof approaches in smoothed analysis. This paper presents a general technique for proving smoothed algorithmic guarantees against adaptive adversaries, in effect reducing the setting of an adaptive adversary to the much simpler case of an oblivious adversary (i.e., an adversary that commits in advance to the entire sequence of input distributions). We apply this technique to prove strong smoothed guarantees for three different problems: (1) Online learning: We consider the online prediction problem, where instances are generated from an adaptive sequence of σ-smooth distributions and the hypothesis class has VC dimension d . We bound the regret by \(\tilde{O}(\sqrt {T d\ln (1/\sigma)} + d\ln (T/\sigma))\) and provide a near-matching lower bound. Our result shows that under smoothed analysis, learnability against adaptive adversaries is characterized by the finiteness of the VC dimension. This is as opposed to the worst-case analysis, where online learnability is characterized by Littlestone dimension (which is infinite even in the extremely restricted case of one-dimensional threshold functions). Our results fully answer an open question of Rakhlin et al. [ 64 ]. (2) Online discrepancy minimization: We consider the setting of the online Komlós problem, where the input is generated from an adaptive sequence of σ-smooth and isotropic distributions on the ℓ 2 unit ball. We bound the ℓ ∞ norm of the discrepancy vector by \(\tilde{O}(\ln ^2(\frac{nT}{\sigma }))\) . This is as opposed to the worst-case analysis, where the tight discrepancy bound is \(\Theta (\sqrt {T/n})\) . We show such \(\mathrm{polylog}(nT/\sigma)\) discrepancy guarantees are not achievable for non-isotropic σ-smooth distributions. (3) Dispersion in online optimization: We consider online optimization with piecewise Lipschitz functions where functions with ℓ discontinuities are chosen by a smoothed adaptive adversary and show that the resulting sequence is \(({\sigma }/{\sqrt {T\ell }}, \tilde{O}(\sqrt {T\ell }))\) -dispersed. That is, every ball of radius \({\sigma }/{\sqrt {T\ell }}\) is split by \(\tilde{O}(\sqrt {T\ell })\) of the partitions made by these functions. This result matches the dispersion parameters of Balcan et al. [ 13 ] for oblivious smooth adversaries, up to logarithmic factors. On the other hand, worst-case sequences are trivially (0, T )-dispersed. 1

Thermosensory Spiking Activity of Proteinoid Microspheres Cross-Linked by Actin Filaments.

Actin, found in all eukaryotic cells as globular (G) or filamentous (F) actin, undergoes polymerization, with G-actin units changing shape to become F-actin. Thermal proteins, or proteinoids, are created by heating amino acids (160-200 °C), forming polymeric chains. These proteinoids can swell in an aqueous solution at around 50 °C, producing hollow microspheres filled with a solution, exhibiting voltage spikes. Our research explores the signaling properties of proteinoids, actin filaments, and hybrid networks combining actin and proteinoids. Proteinoids replicate brain excitation dynamics despite lacking specific membranes or ion channels. We investigate enhancing conductivity and spiking by using pure actin, yielding improved coordination in networks compared with individual filaments or proteinoids. Temperature changes (20 short-peptide supramolecular C to 80 °C) regulate conduction states, demonstrating external control over emergent excitability in protobrain systems. Adding actin to proteinoids reduces spike timing variability, providing a more uniform feature distribution. These findings support theoretical models proposing cytoskeletal matrices for functional specification in synthetic protocell brains, promoting stable interaction complexity. The study concludes that life-like signal encoding can emerge spontaneously within biological polymer scaffolds, incorporating abiotic chemistry.

Enhanced solar energy utilization of thermal energy storage tanks with phase change material and baffle incorporating holes

In response to the pressing need for more efficient thermal energy storage solutions, this study investigates the strategic implementation of baffles in phase change material (PCM) tanks to enhance thermal performance. PCM offers a promising solution for efficient thermal energy storage (TES); however, ensuring uniform temperature distribution inside the tanks remains challenging. Horizontal baffles with holes of varying diameters were introduced in Tanks 02, 03, and 04, while an inclined baffle with holes was used in Tank 05. The Tank 06 benefitted from an inclined baffle with holes of different diameters. A comprehensive analysis of all Tanks was evaluated by assessing PCM and water heat flux, PCM and water static enthalpy, Richardson number, velocity vectors, temperature, and liquid fraction contours. The results demonstrated that significant improvements were achieved with the addition of baffles. Tank 01, without a baffle, exhibited a melting time of 2860 s. However, the introduction of baffles resulted in reduced melting times for Tanks 02 to 06: 2360 s (17.48 %), 2350 s (17.83 %), 2400 s (16.08 %), 2320 s (18.88 %), and 2240 s (21.67 %), respectively; which led to enhance TES efficiency, and a quicker energy storage process. The study also includes a comprehensive economic analysis, evaluating the total cost (Ctotal) and performance-economic ratio (Pc). Tank 06 shows superior economic performance, with a Pc value of 0.26 despite a slightly higher cost than Tank 01 by $2 USD. These findings highlight the baffle design’s effectiveness in achieving better heat transfer and uniform temperature distribution within PCM tanks, making them more efficient for TES applications.

Amelioration of protective organic layer using acenaphthene-based inhibitor responsible for excellent anti-corrosion performance: Experimental and computational perspectives

Despite the engineering promise offered by the co-existence of organic substances in protecting vulnerable metallic materials from corrosive environments, the interaction and formation mechanisms that induce the development of new materials with improved structural properties remain less understood. This study investigated the corrosion inhibitory properties of two acenaphthene derivatives, acenaphthylene-1,2‑dione (ACP) and 1,2-dihydroacenaphthylen-1-ol (DCP), as inhibitors for N80 steel in a 15 % HCl solution. The anticorrosive effectiveness of ACP and DCP compounds was evaluated through multiple research methods, including weight loss analysis, electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), and surface characterization using scanning electron microscopy (SEM). The experimental findings demonstrate that ACP exhibits superior inhibition performance compared to DCP, with an inhibition efficiency of 93.54 % for ACP and 73.12 % for DCP at an optimum concentration of 5 × 10–3 M. EIS data show that the charge transfer resistance increases with higher concentrations of both compounds. PDP results indicate that ACP and DCP act as mixed-type inhibitors without altering the corrosion mechanism. The kinetic parameters of corrosion adsorption follow the Langmuir isotherm, highlighting a competition between physical and chemical interactions. To investigate how the geometric structures resulting from functional groups influence their interaction with the metal surface, theoretical calculations employing density functional theory (DFT), molecular dynamics (MD), and density-functional tight-binding (DFTB) were conducted. These calculations were aimed at gaining insights into the adsorption behavior of ACP and DCP on the metal surface and their interfacial mechanism. The calculations demonstrate that the molecule possessing twin donor atoms along with p-type orbitals of aromatic rings significantly influenced the formation of a protective film with a uniform distribution. This configuration exhibited superior corrosion performance compared to a molecule containing only one hydroxyl group (—OH). Theoretical calculations further suggest that ACP exhibits stronger adsorption ability, with the two oxygen atoms identified as the most reactive sites, indicating their tendency to donate electrons to the iron surface. The robust resonance-stabilized structure of ACP enhances the stability of the molecules, facilitating its interaction and adsorption onto the metal surface compared to the DCP inhibitor. Overall, the superior inhibition performance of ACP is attributed to the close bonding of twin donor fragments within the ACP molecule, forming a more compact adsorbed inhibitor film on the steel surface.

Throughflow effect on bi-disperse convection in Rivlin-Ericksen fluid

In this investigation, we delve into the influence of throughflow on the phenomenon of bi-disperse convection within Rivlin-Ericksen fluid. In the context of examining bi-disperse convection within this specific type of fluid, the throughflow effect is considered to have a uniform vertical distribution. The primary focus of this study centers on evaluating the system’s linear stability. To achieve this, we employ normal mode analysis to compute the Darcy-Rayleigh number at the onset of convection. This Darcy-Rayleigh number is computed for both stationary and oscillatory convection modes. Furthermore, we conduct a comprehensive analysis and present the results in graphical form to illustrate the impact of various parameters, including Peclet number and kinematic viscoelastic parameter, on both stationary and oscillatory convection. Our research findings demonstrate that when Peclet number Pr1 &lt; 0, it leads to destabilising effect on both stationary and oscillatory convections. Conversely, when Peclet number Pr1 &gt; 0, it induces stabilising effect on both stationary as well as oscillatory convections.

Effect of the porous structure on the hygrothermal vibration analysis of functional graded nanoplates using nonlocal high-order continuum plate model

AbstractThis study delves into the thermomechanical vibration behavior of functionally graded porous nanoplates under extreme thermal temperature and humidity conditions. The equation of motion of the nanoplate was derived using advanced theories in elasticity and deformation. The nanoplate consists of metal (SUS304) on the bottom surface and ceramic (Ni3S4) on the top surface, with the material distribution changing according to the power law across the plate thickness. The nanoplate was modeled with uniform and symmetric distributions of porosity reaching as high as 60%. Upon incorporating the thermal and moisture loads from the humid surroundings into the equations of motion derived from Hamilton's principle, the equations were solved using Navier's method and simplified to the eigenvalue equation. Analyzed within a broad framework are the thermomechanical vibration behavior of the nanoplate, temperature impact, humidity influence, porosity and its distribution, material grading parameter effects, and nonlocal integral elasticity effects. Observations indicate that variations in thermal temperature, humidity, and nonlocal parameters can lower the thermomechanical vibration frequency of the nanoplate, whereas porosity has the opposite effect. The effects mentioned are influenced by factors, such as the porosity ratio, porosity distribution, material ratios, and the size of the nonlocal parameter in the plate. The primary objective of this work is to uncover the nonlinear frequency response of nanoplates with high porosity in conditions characterized by high temperature and humidity.

Strength of Composite Pressure Insulators for High Voltage Circuit Breakers: An Experimental and Numerical Investigation.

Glass fiber-reinforced composite cylinders, capable of withstanding internal pressure generated during service, are increasingly utilized as insulators in high voltage circuit breakers. Different testing procedures have been suggested by various standards to assess the pressure resistance of these components. Due to its simplicity and cost-effectiveness, the split-disk testing method is the most widely used for evaluating the hoop strength of pressure cylinders during the development and verification phases. However, the method presents several aspects, such as those related to the influence of specimen geometry and friction, which require further examination since they may impact the outcome of the experimental tests. The investigation, carried out by a combination of experimental testing and finite element analyses, shows that the friction between the specimen and the semi-disks has a noteworthy effect on the hoop load applied to the specimen. Almost constant load distributions along the hoop direction, representative of the real operating conditions in a pressurized cylinder, can be achieved via proper lubrication of the contact surfaces. Furthermore, FE analyses demonstrate that the notch geometry suggested by specific standards (short notch) is not capable of inducing a uniform strain distribution in the notched region. A different notch geometry (long notch) is proposed in the study to attain a more uniform strain field over the reduced area region. The experimental results indicate that the strength measured on the short notch specimens is higher than that determined on the long notch specimens, thus confirming the significant influence of strain distribution on the strength properties measured with the split-disk method.

Insights into the roles of heat‐stable protein derived from egg white in vitamin A stabilisation

SummaryVitamin A (VA) is a fat‐soluble compound that is essential for physiological functions including vision, fetal growth, immune response, cell differentiation and proliferation. However, its susceptibility to environmental conditions leading to poor stability limits its application in food. This study investigated the interaction between egg white protein (EWP) and VA by spectroscopy and molecular docking. The results indicated one EWP could bind 16.00 ± 0.89 VA molecules and the binding constant is (2.59 ± 0.71) × 105 m−1. What's more, there was a fluorescence resonance energy transfer between EWP and VA, and the Förster radius is 5.28 nm. In addition, VA enhanced the hydrophobic interactions with the EWP, resulting in protein aggregation, larger average particle size and more uniform particle size distribution. Finally, the combination of VA with EWP could significantly improve the photothermal stability and storage stability of VA. These studies indicate that EWP nanocomplexes can be used as ideal delivery carriers for bioactive substances.

Studies of electrical resistivity and magnetic properties of CuFe and CuNiFe films prepared by magnetron sputtering

The Cu-Fe binary alloys exhibit severe elemental segregation, resulting in an inhomogeneous microstructure, which leads to differences in microregion magnetic properties, thus affecting their application. Employing magnetron sputtering to produce films is advantageous for achieving a consistent dispersion of Fe within the Cu matrix. Furthermore, the addition of Ni will result in a more uniform distribution of Fe and facilitate the formation of the ferromagnetic Ni3Fe phase. In this study, Cu100−xFex and Cu100−x(Ni3/4Fe1/4)x series films were prepared by magnetron sputtering technique. The magnetic properties of films are closely related to their ferromagnetic element content. An increase in the content of ferromagnetic elements leads to an improvement in the saturation magnetization (MS) strength and a decrease in the coercivity (HC). The formation of Fe-Fe pairs is more favorable for magnetic properties compared to Ni-Fe pairs. Meanwhile, by comparing with bulk alloys, the distribution of the magnetic elements severely affects the magnetic properties. Moreover, the resistivity of Cu100−xFex films (20.3–96.7 μΩ cm) is much higher than that of Cu100−x(Ni3/4Fe1/4)x films (15.6–60.6 μΩ cm), which depends on the magnetic properties. This study systematically analyzes the effect of the content and distribution of magnetic elements on magnetic and electrical properties.

Development of silver-doped copper oxide and chitosan nanocomposites for enhanced antimicrobial activities.

Antimicrobial resistance (AMR) has emerged as a significant and pressing public health concern, posing serious challenges to effectively preventing and treating persistent diseases. Despite various efforts made in recent years to address this problem, the global trends of AMR continue to escalate without any indication of decline. As AMR is well-known for antibiotics, developing new materials such as metal containing compounds with different mechanisms of action is crucial to effectively address this challenge. Copper, silver, and chitosan in various forms have demonstrated significant biological activities and hold promise for applications in medicine and biotechnology. Exploring the biological properties of these nanoparticles is essential for innovative therapeutic approaches in treating bacterial and fungal infections, cancer, and other diseases. To this end, the present study aimed to synthesize silver@copper oxide (Ag@CuO) nanoparticles and its chitosan nanocomposite (Chi-Ag@CuO) to investigate their antimicrobial efficacy. Various established spectroscopic and microscopic methods were employed for characterization purposes, encompassing scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Subsequently, the antimicrobial activity of the nanoparticles was assessed through MIC (minimum inhibitory concentration), MBC (minimum bactericidal concentration), and well-disk diffusion assays against Pseudomonas aeruginosa, Acinetobacter baumannii Staphylococcus aureus, Staphylococcus epidermidis, and Candida albicans. The size of the CuO-NPs, Ag@CuO, and Chi-Ag@CuO NPs was found to be 70-120 nm with a spherical shape and an almost uniform distribution. The nanocomposites were found to possess a minimum inhibitory concentration (MIC) of 5 μg/mL and a minimum bactericidal concentration (MBC) of 250 μg/mL. Moreover, these nanocomposites generated varying clear inhibition zones, with diameters ranging from a minimum of 9±0.5 mm to a maximum of 25±0.5 mm. Consequently, it is evident that the amalgamation of copper-silver-chitosan nanoparticles has exhibited noteworthy antimicrobial properties in the controlled laboratory environment, surpassing the performance of other types of nanoparticles.

Effects of various long-term thermal aging levels on the morphology, rheology and self-healing performances of high-viscosity asphalt

Large macroporous structures of permeable asphalt pavement made high-viscosity asphalt (HVA) more susceptible to aging and failure. However, the standard pressure aging vessel (PAV) test was difficult to accurately emulate the long-term aging behavior of HVA. Hence, 1–5PAV aging levels of two HVAs (i.e. HVA-1 and HVA-2) were emulated by the simple aging test (SAT). Rheological analysis indicated that asphalt oxidation consistently dominated regardless of the long-term aging levels of HVAs. Combined with the fluorescence microscopy observation, HVA-2 with meticulous and uniform granular distribution was more resistant to aging than HVA-1 with coarse and continuously strip-like structures. Stress-strain curve analysis in linear amplitude sweep (LAS) test revealed that the accumulated strain energy (ASE) representing the overall mechanical properties of HVAs first increased and then decreased as the long-term aging level grew. The continuous repeated LAS (RLAS) test further reflected that the yield stress, yield strain and ASE of HVAs gradually decreased as the LAS loading number increased at initial long-term aging states; but as the sustained growth of aging level, the stress-strain curve of HVAs become increasingly chaotic until remarkable strain hardening occurred. Furthermore, RLAS-based self-healing (RLASSH) test was developed by introducing intermittent time into RLAS test. The variation of ratio of ASE decrease can characterize the self-healing performance of HVAs. RLASSH test showed that the self-healing performance of HVAs was unstable at 1–3PAV aging level, and the HVAs with 4 or 5PAV aging levels completely lost their self-healing performance. Overall, with the increase in long-term aging levels, significant differences were observed in the evolution characteristics of morphology, rheology and self-healing performances of different HVAs. This study helps to understand the rheology and self-healing performance evolution pattern of HVA during long-term service.

Surface Passivation with Tailoring Organic Potassium Salt for Efficient FAPbI3 Perovskite Solar Cells and Modules

AbstractPassivating surface defects on perovskite films with tailored functional materials has emerged as one of the most effective strategies for achieving high‐performance perovskite solar cells (PSCs). Among existing material selections, potassium salts stand out for their effective passivation of defects surrounding perovskite grain boundaries. However, the widely used potassium salts are inorganic and only soluble in highly polar solvents, which limits their practical application for surface passivation. Herein, a novel organic potassium salt (KCFSO), with multiple organic functional groups and good solubility in low polar isopropanol, is reported to function as a post‐treatment agent for perovskite. Combined with experimental results and theoretical calculations, the formed multiple intermolecular interactions between KCFSO and perovskite are revealed to play a vital role in determining the defect passivation effect. Thus, the KCFSO‐modified film shows a more uniform surface potential distribution, dramatically decreased defect density, and improved charge transfer, leading to a champion power conversion efficiency (PCE) of 25.11%, and good stability for the derived PSCs. As a demonstration of scalability, the centimeter‐sized PSCs and 5 cm × 5 cm mini‐modules also demonstrate impressive PCEs of 24.17% and 20.18%, respectively. These findings provide insights into passivator design principles to achieve efficient and stable perovskite photovoltaics.

On the Dendrite‐Suppressing Effect of Laser‐Processed Polylactic Acid‐Derived Carbon Coated Zinc Anode in Aqueous Zinc Ion Batteries

AbstractA major bottleneck limiting the commercialization of aqueous zinc ion batteries (AZIBs) is dendrite formation on the zinc (Zn) anode during the plating/stripping process, which leads to rapid deterioration in performance and, consequently to the device failure. In this regard, researchers are trying to design more stable anodes toward suppressing dendrite formation. One possible solution to tackle this problem and to extend the cycling life of AZIBs is to modify the zinc anode surface by coating carbonaceous materials, enabling more controlled charge flux and uniform ion distribution. This work reports sustainable and bio‐derived polylactic acid (PLA) as a coating layer on the zinc anode. Carbonizing this polymer under ambient conditions using a high‐power nanosecond laser forms a carbon‐coated zinc foil, which was directly utilized as the anode in aqueous zinc ion batteries. The fabricated laser‐processed PLA‐derived carbon‐coated zinc anode demonstrated an extended cycling life of almost 1600 hours, significantly outperforming the bare zinc anode. A full aqueous zinc ion battery assembled from as‐modified anode and as‐prepared V2O5 nanofibers as cathode was able to deliver a specific capacity of 238 mAh g−1 at 1.0 A g−1 with a capacity retention of 70 % after 1000 cycles.

On the Dendrite-Suppressing Effect of Laser-Processed Polylactic Acid-Derived Carbon Coated Zinc Anode in Aqueous Zinc Ion Batteries.

A major bottleneck limiting the commercialization of aqueous zinc ion batteries (AZIBs) is dendrite formation on the zinc (Zn) anode during the plating/stripping process, which leads to rapid deterioration in performance and, consequently to the device failure. In this regard, researchers are trying to design more stable anodes toward suppressing dendrite formation. One possible solution to tackle this problem and to extend the cycling life of AZIBs is to modify the zinc anode surface by coating carbonaceous materials, enabling more controlled charge flux and uniform ion distribution. This work reports sustainable and bio-derived polylactic acid (PLA) as a coating layer on the zinc anode. Carbonizing this polymer under ambient conditions using a high-power nanosecond laser forms a carbon-coated zinc foil, which was directly utilized as the anode in aqueous zinc ion batteries. The fabricated laser-processed PLA-derived carbon-coated zinc anode demonstrated an extended cycling life of almost 1600 hours, significantly outperforming the bare zinc anode. A full aqueous zinc ion battery assembled from as-modified anode and as-prepared V2O5 nanofibers as cathode was able to deliver a specific capacity of 238 mAh g-1 at 1.0 A g-1 with a capacity retention of 70 % after 1000 cycles.

Segmentation of THz holograms for homogenous illumination

This paper investigates the feasibility of applying the hologram segmentation method for homogeneous illumination. Research focuses on improving the uniformity of the illumination obtained from diffractive optical elements in the THz range. The structures are designed with a modified Ping-Pong algorithm and a neural network-based solution. This method allows for the improvement of uniform illumination distribution with the desired shape. Additionally, the phase modulations of the structures are divided into segments, each responsible for imaging at different distances. Various segment combination methods are investigated, differing in shapes, image plane distances, and illumination types. The obtained image intensity maps allow for the identification of the performance of each combination method. Each of the presented structures shows significant improvements in the uniformity of imaged targets compared to the reference Ping-Pong structure. The presented structures were designed for a narrow band case—260 GHz frequency, which corresponds to 1.15 mm wavelength. The application of diffractive structures for homogenization of illumination shows promise. The created structures perform designed beamforming task with variability of intensity improved up to 23% (standard deviation) or 45% (interquartile range) compared with reference structure.