Exceptional Value Research Articles

Investigation of optical and thermoelectric characteristics of novel zintl-phase alloys CaZn2X2 (X = P, As, Sb) for green energy applications

Abstract This study examines the photovoltaic and thermoelectric response of calcium-based novel Zintl-phase alloys CaZn2X2 (X = P, As, Sb). The structural, optoelectronics, and transport features of Zintl CaZn2X2 (X = P, As, Sb) compounds have been analyzed using the full potential linearized augmented plane wave (FPLAPW) technique. Investigations on formation energy and phonon dispersion have confirmed the formation and dynamical stabilities. These compounds exhibit a semiconductor behavior, as their predicted bandgap values: 1.76 eV for CaZn2P2, 1.14 eV for CaZn2As2, and 0.32 eV for CaZn2Sb2. By investigating the optical properties, we have discovered their potential applicability in optoelectronic and photovoltaic devices, as evidenced by the optical response of these phases. The traditional Boltzmann transport theory has assessed transport characteristics against temperature and chemical potential. Significantly higher values of the Seebeck coefficient are achieved at room and elevated temperatures. Moreover, the power factor demonstrates a linear relationship with rising temperature. The remarkable optoelectronic properties and exceptional power factor values suggest that these materials are suitable for deployment in photovoltaic and transport devices.

Long-Term Changes in the Thermal and Ice Regime of the Biebrza River (Northeastern Poland) in the Era of Global Warming

In the context of ongoing environmental changes, particularly against the backdrop of global warming, significant attention is being given to areas of exceptional natural value that, in many aspects, retain a pristine character. One such area is the Biebrza River in northeastern Poland, which, together with the wetlands in its basin, forms one of the most valuable ecosystems of its kind in Europe. This study analyses the changes in the thermal and ice regime for two hydrological stations, Sztabin and Burzyn, in the period from 1959 to 2023. It was found that the average annual water temperature in this period for the Biebrza River increased by 0.28 °C/decade, and in the case of ice phenomena, statistically significant changes for both stations showed a decline, with an acceleration of the ice cover disappearance by an average of 3 days/decade. These recorded changes should be considered unfavourable, as they will affect the transformation of both the biotic and abiotic characteristics of the river itself, as well as the natural elements associated with it.

Predicting corrosion current density in magnesium alloy battery anodes: machine learning approach using rapid miner

ABSTRACT Magnesium (Mg) alloys are increasingly recognised for their potential as anode materials in batteries due to their high specific capacity and cost-effectiveness. However, their susceptibility to corrosion poses a significant challenge to practical applications. This study explores the effectiveness of various machine learning models – local polynomial regression, Decision Trees, Random Forest, Gradient Boost, and Extreme Gradient Boost – in predicting the corrosion behaviour of Mg alloy battery anodes in a 3.5 wt.% NaCl electrolyte. Experimental data on the corrosion current density of Mg alloys are collected and analysed using the RapidMiner tool for model training and evaluation. The findings highlight that the Extreme Gradient Boost (XGBoost) model excels among other machine learning techniques in accurately forecasting the corrosion rates of Mg alloys. XGBoost achieves an exceptional R2 value of 0.9931 in Tafel plots, indicating a robust fit to the data as evidenced by scatter plots. Furthermore, the XGBoost model demonstrates strong positive monotonic and ordinal relationships between actual and predicted corrosion current densities, as indicated by a Spearman correlation coefficient of 1 and a Kendall tau coefficient of 0.99. These outcomes underscore XGBoost's potential as a powerful tool for enhancing the understanding and management of corrosion in Mg alloy battery applications.

DESIGN AND FABRICATION OF SHAPE MORPHING MAGNETO-IMPEDANCE MAGNETIC SENSOR

The magnetoimpedance (MI) effect is characterized by the alteration in the impedance of soft magnetic materials when subjected to a magnetic field while a high-frequency alternating current flows through them. In this study, we engineered two distinct sensor architectures utilizing amorphous FeCSi magnetic ribbon: a single-bar structure with the dimension of 10 mm × 90 μm × 20 μm and a meander structure consisting of 13 parallel single bars. These structures were miniaturized through advanced techniques combining laser engraving and chemical etching. The magnetic analysis reveals that the meander structure exhibits a pronounced dependency on the angle θ between the magnetic field and the sensor orientation, enhancing its soft magnetic properties by up to fivefold compared to the single-bar design. This enhancement might be attributed to a reduction in the demagnetization effect and shape anisotropy energy within the meander sensor. Furthermore, the analysis of the MI effect indicates that the resonance frequency remains unaffected by external magnetic fields for both sensor types. Notably, the meander sensor demonstrates exceptional MI ratio values exceeding 82%, representing a remarkable 24-fold increase over the 3.5% observed in the single-bar sensor. Additionally, the isotropy - quantified as the MI ratio's dependence on angle θ, and magnetic field sensitivity are significantly improved in the meander configuration. These advancements in soft magnetic and physical properties are correlated to the domain structure of the sensor, particularly its transverse magnetic permeability, as evidenced by micromagnetic simulations conducted using Mumax3. With its superior MI ratio, isotropy, and heightened magnetic field sensitivity, the meander-type magnetic field sensor presents substantial potential for applications across diverse fields, ranging from biological systems to specialized practical missions.

Nanopore-based full-length transcriptome sequencing of the skin in Pseudopleuronectes yokohamae identifies novel antimicrobial peptide genes

The marbled flounder (Pseudopleuronectes yokohamae) is highly esteemed for its exceptional nutritional value and delicious taste. However, this species has extremely limited transcriptome data, which can offer priceless information for disease protection. In the study, the skin transcriptomic sequencing of P. yokohamae revealed 7.72 GB of clean data using the Nanopore sequencing platform. The results revealed 30,498 transcripts of functional annotations in the P. yokohamae transcriptome. All transcripts were searched in eight functional databases. A total of 10,337 ORFs were obtained, of which 6081 complete ORFs accounted for 58.83% of all predicted CDS. Moreover, 10,195 SSRs were detected. Meanwhile, the non-pecific immunity pathways were investigated for better understanding of the immunological reaction in P. yokohamae, and seven innate immune pathways were identified. The innate-immune related genes were highly expressed in the NOD-like receptor signaling pathway, followed by the C-type lectin receptor signaling pathway, Toll-like receptor signaling pathway, RIG-I-like receptor signaling pathway and Cytosolic DNA-sensing pathway. In this study, four families of antimicrobial peptides (AMPs) in P. yokohamae were analysed for the first time, including piscidins, hepcidins, liver-expressed antimicrobial peptide and defensins. Seven AMPs, including Pypleurocidin-like WF3, Pypleurocidin-like WFX, Pyhepcidin 1, Pyhepcidin-like 1, PyLEAP-2, Pybeta-defensin and Pybeta-defensin-like 1, were further identified. The seven AMPs showed a highly identity in their cDNA and genomic structures and an inducible expression pattern preferable to skin in response to pathogens. The transcriptomic data and investigation of AMPs from P. yokohamae promote a deeper awareness of fish mucosal immunity and provide information in the prevention of fish diseases.

Exploring optoelectronic, optical thin films, mechanical and thermal transport properties of bromide double perovskites Rb2Ag(Ga/In)Br6 for photovoltaic and thermoelectric applications

Lead-free double halide perovskites like Rb2Ag(Ga/In)Br6 have demonstrated themselves potential candidates in solar cell research owing to their environmental friendliness, stability, and exceptional performance. This study comprehensively analyzes the structural, mechanical, optoelectronic and optical coating features, as well as thermodynamic and thermoelectric properties of two Rb2AgGaBr6 and Rb2AgInBr6 compounds. Using the Wien2k code with GGA + mBJ exchange-correlation potentials, we confirm their structural stability in cubic phase Fm-3m and identifying them as direct band gap semiconductors (Γ → Γ) of 0.38 eV and 1.0644 eV, respectively. Then, optical analysis reveals broad absorption bands across visible and ultraviolet wavelengths, making them suitable for photovoltaic absorbers. Finally, the thermoelectric investigations under varying temperatures show favourable properties, such as a high Seebeck coefficient with poor electronic thermal conductivity. This also yields exceptional value (0.96 and 0.994 for Rb2AgGaBr6, Rb2AgInBr6, respectively) of figure of merit (ZT) at room temperature and chemical potential μ-μ0 = - 0.09eV near the Fermi energy level, enhancing their potential for thermoelectric applications. These findings underscore the versatility and promising future of Rb2Ag(Ga/In)Br6 as important semiconductors processing for optoelectronic, thermoelectric, and mechanical devices.

Copper(II) isonicotinate metal-organic framework for reusable adsorption of salmeterol from wastewater

This study investigates the adsorption of salmeterol (SMT) from aqueous solutions using a novel nano-sized copper-based metal-organic framework (Cu-MOF). The Cu-MOF was synthesized under solvent-free conditions, enhancing its environmental sustainability. Key parameters such as adsorbent dosage, initial SMT concentration, temperature, and pH were systematically evaluated to optimize adsorption performance. The results demonstrate the exceptional adsorption capacity of the Cu-MOF, reaching a maximum of 400mg/g within 50minutes of contact time under optimal conditions of 4mg Cu-MOF, 50mg/L SMT, and pH 11. The kinetic and isotherm studies revealed that the pseudo-second-order and Langmuir models exhibited superior fitting to the experimental data, as evidenced by their exceptional R² values of 0.999 and 0.999, minimal RMSE values of 0.034 and 0.001, and significantly lower AIC values of -45.77 and -129.17 for the kinetic and isotherm models, respectively. Thermodynamic analysis confirmed the exothermic and spontaneous nature of the adsorption process. Moreover, the Cu-MOF exhibited excellent reusability, maintaining its adsorption efficiency over six consecutive cycles. Therefore, these findings highlight the potential of Cu-MOF as a promising and sustainable adsorbent for effectively removing salmeterol from wastewater.

Value distribution of a pair of meromorphic functions

The well-known Picard theorem shows only what happens on the Picard exceptional value of a meromorphic function f. In this paper, we mainly consider what happens on the common or different Picard exceptional values of two or three meromorphic functions with certain types. For instance, we will provide some new results and discussions for the generalized Picard exceptional values or small functions of a pair of meromorphic functions fng(k) and gmf(k), these two functions are the crossed variants of the complex differential polynomials in Hayman's conjecture, where n, m are positive integers and k≥0. We give more details on the case that fg′ and gf′ when f and g are exponential polynomials in particular.

Modulating Schottky barriers and active sites of Ag-Ni bi-metallic cluster on mesoporous carbon nitride for enhanced photocatalytic hydrogen evolution

The advancement of photocatalysis relies on the development of novel hetero-structured materials with unique architectures. In this study, we successfully synthesized a hetero-structured g-C3N4 (GCN) material with a distinctive surface-interface modification. To further enhance its photocatalytic performance, we optimized the Ag and Ni concentration to maximize the visible light absorption and catalytic active sites for hydrogen evolution reactions. By using systematic physicochemical characterizations and density functional theory (DFT) calculations, we elucidated the pivotal role of graphitic carbon nitride (g-C3N4) in facilitating the formation of an efficient charge transfer channel and promoting the effective generation and separation of photo-generated carriers. From the DFT calculations, we also demonstrated that the Ag and Ni nanoparticles provide more efficient visible light absorption and active sites than Ni nanoparticles for water splitting and hydrogen evolution and In-situ TEM exploration. Furthermore, the hetero microstructure consisting of thin g-C3N4 nano scrolls has a crucial role in shortening the migration distance of the carriers, effectively suppressing carrier recombination. Consequently, these extraordinary characteristics resulted in a superior solar light-driven photocatalytic H2 evolution rate of 2507 μmol.h-1.g−1, surpassing the rate achieved by g-C3N4 heterostructures by a remarkable 18.6-folds. Moreover, the apparent quantum efficiency of this hetero-structured material reached an exceptional value of 1.6 % under a 1.5 G air mass filter.

Dermal exposure assessment of formal e-waste dismantlers to flame retardants and plasticizers using passive sampling methodologies

The recycling of e-waste can lead to the release of organic chemicals when materials containing additives are subjected to dismantling and grinding. In this context, the exposure of workers from a Catalonian e-waste facility to flame retardants and plasticizers (including organophosphate esters (OPEs), polybrominated diphenyl ethers (PBDEs), novel brominated flame retardants (NBFRs) and dechloranes) was assessed using T-shirts and wristbands as passive samplers. The study area includes an area exclusively dedicated to cathodic ray-tube (CRT) TVs dismantling, and a grinding area where the rest of e-waste is ground. All the families of compounds were detected in both T-shirts and wristbands, with the highest concentration levels corresponding to OPEs, followed by PBDEs, NBFRs, and dechloranes. The CRT area presented higher concentration levels than the grinding area. The compounds with higher concentrations in T-shirts were 2-ethylhexyl diphenyl phosphate (EHDPP), diphenyl cresyl phosphate (DCP) and triphenyl phosphate (TPHP), and the total concentration of all groups ranged between 293 and 8324 ng/dm2-h (hour). In the case of the wristbands, the most abundant compounds were DCP, TPHP, and BDE-209, with total concentrations between 188 and 2248 ng/dm2-h. The two sampling methods appear to be complementary, as T-shirts collect coarser particles, while wristbands also capture volatile compounds. Based on normalized surface and time concentrations, the estimated daily intake (EDI) through dermal contact was calculated and carcinogenic and non-carcinogenic risks (CR and non-CR) associated with this activity assessed. The results show median CR 29 and 16 times below the threshold in CRT and grinding areas respectively. The non-CR medians were 2 and 3 times below the threshold, although in the CRT area one exceptional value surpassed the threshold, suggesting that risk can exist for some workers in the facility.

Knowledge sharing and sustainable competitive advantage: Mediating role of innovation culture and MSMEs business performance

This research aims to investigate how business performance (BP) and innovation culture (IC) mediate the relationship between knowledge sharing (KS) and sustainable competitive advantage (SCA) of MSMEs operating in Yogyakarta, Indonesia. The survey method was employed to gather the necessary data for this research. The population and sample consisted of 50 MSMEs. The unit of analysis in this study is the MSMEs fashionpreneur Jogja Fashion Dunia Incubation Program, which is represented by the owner and manager, who also serves as the respondent. The analysis method employed in this research is Partial Least Squares (PLS) using SmatPLS 4 software. The investigation results demonstrate that knowledge sharing has a significant impact on both the innovation culture and long-term competitive advantage. Additionally, the study reveals that the innovation culture significantly influences business performance and lasting competitive advantage. However, it is worth noting that business performance does not have a noticeable effect on sustainable competitive advantage. Furthermore, the study indicates that the relationship between knowledge sharing and sustainable competitive advantage is mediated by the innovation culture. On the other hand, when business performance acts as a mediator, the effect of the innovation culture and knowledge sharing on competitive advantage is indiscernible. To create exceptional customer value, policymakers and MSME management must showcase a firm dedication to innovation and connect it to supply chain agility, also known as SCA. Ultimately, this will result in comprehensive and enduring business performance.

Highly Efficient Near-Infrared Luminescent Radicals with Emission Peaks over 750 nm.

Purely organic molecules exhibiting near-infrared (NIR) emission possess considerable potential for applications in both biological and optoelectronic technological domains, owing to their inherent advantages such as cost-effectiveness, biocompatibility, and facile chemical modifiability. However, the repertoire of such molecules with emission peaks exceeding 750 nm and concurrently demonstrating high photoluminescence quantum efficiency (PLQE) remains relatively scarce due to the energy gap law. Herein, we report two open-shell NIR radical emitters, denoted as DMNA-Cz-BTM and DMNA-PyID-BTM, achieved through the strategic integration of a donor group (DMNA) onto the Cz-BTM and PyID-BTM frameworks, respectively. We found that the donor-acceptor molecular structure allows the two designed radical emitters to exhibit a charge-transfer excited state and spatially separated electron and hole levels with non-bonding characteristics. Thus, the high-frequency vibrations are effectively suppressed. Besides, the reduction of low-frequency vibrations is observed. Collectively, the non-radiative decay channel is significantly suppressed, leading to exceptional NIR PLQE values. Specifically, DMNA-Cz-BTM manifests an emission peak at 758 nm alongside a PLQE of 55%, whereas DMNA-PyID-BTM exhibits an emission peak at 778 nm with a PLQE of 66%. Notably, these represent the pinnacle of PLQE among metal-free organic NIR emitters with emission peaks surpassing 750 nm.

Highly Efficient Near‐Infrared Luminescent Radicals with Emission Peaks over 750 nm

Purely organic molecules exhibiting near‐infrared (NIR) emission possess considerable potential for applications in both biological and optoelectronic technological domains, owing to their inherent advantages such as cost‐effectiveness, biocompatibility, and facile chemical modifiability. However, the repertoire of such molecules with emission peaks exceeding 750 nm and concurrently demonstrating high photoluminescence quantum efficiency (PLQE) remains relatively scarce due to the energy gap law. Herein, we report two open‐shell NIR radical emitters, denoted as DMNA‐Cz‐BTM and DMNA‐PyID‐BTM, achieved through the strategic integration of a donor group (DMNA) onto the Cz‐BTM and PyID‐BTM frameworks, respectively. We found that the donor‐acceptor molecular structure allows the two designed radical emitters to exhibit a charge‐transfer excited state and spatially separated electron and hole levels with non‐bonding characteristics. Thus, the high‐frequency vibrations are effectively suppressed. Besides, the reduction of low‐frequency vibrations is observed. Collectively, the non‐radiative decay channel is significantly suppressed, leading to exceptional NIR PLQE values. Specifically, DMNA‐Cz‐BTM manifests an emission peak at 758 nm alongside a PLQE of 55%, whereas DMNA‐PyID‐BTM exhibits an emission peak at 778 nm with a PLQE of 66%. Notably, these represent the pinnacle of PLQE among metal‐free organic NIR emitters with emission peaks surpassing 750 nm.

Enhanced ultra-cryogenic impact toughness in 9 wt% Ni steel through lamellar microstructure refinement

The research aims to effectively enhance the low-temperature toughness of 9 wt% Ni steel, which is used in storage containers for alternative energy sources such as liquefied natural gas. To achieve this, a lamellarizing heat treatment was applied to 9 wt% Ni steel, initially manufactured using the conventional quenching-tempering (QT) process, thereby introducing a quenching-lamellarizing-tempering (QLT) process. The Charpy impact toughness of the 9 wt% Ni steel was then evaluated under two extreme cryogenic conditions: 196 °C and −253 °C. The 9 wt% Ni steels subjected to the QLT treatment demonstrated exceptional Charpy impact toughness values of 238 J at −196 °C and 217 J at −253 °C. This study presents an examination of the microstructural and micro-hardness evolution throughout the various stages of the QLT heat treatment process. A comparative investigation was undertaken by contrasting these results with samples treated using quenching (Q), quenching-tempering (QT), and quenching-lamellarizing (QL) treatments. The QLT treatment induces a substantial volume fraction of retained austenite, combined with a strategically distributed micro-hardness profile. In this profile, the soft phase interspersed among hard phases can alter the crack propagation path and absorb energy, thereby enhancing toughness. This synergy contributes to the exceptional Charpy impact toughness observed at −253 °C. These results suggest that the introduction of the QLT heat treatment is an effective method for enhancing the cryogenic impact toughness of 9 wt% Ni steel at temperatures below −196 °C, compared to the conventional QT process.

Reproductive Morphology and Success in Annual versus Perennial Legumes: Evidence from Astragalus and the Fabeae (Papilionoideae).

The third largest angiosperm family, Leguminosae, displays a broad range of reproductive strategies and has an exceptional practical value. Whereas annual legume species are mostly planted as crops, there is a significant interest in breeding and cultivating perennials. It is therefore of importance to compare reproductive traits, their interactions and the resulting productivity between related annual and perennial species. Two highly variable taxa were chosen for this purpose, the Fabeae tribe, including numerous temperate crops, and the largest angiosperm 'megagenus' Astragalus. A dataset of quantitative reproductive traits was composed of both originally obtained and previously published data. As a result of statistical analysis, we found that perennials in both groups tend to produce more flowers per axillary racemose inflorescence as well as more ovules per carpel. Perennial Astragalus also have larger flowers. Only a part of the developing flowers and ovules gives rise to mature pods and seeds. This difference is especially pronounced in small populations of rare and threatened perennials. Numerous reasons underlie the gap between potential and real productivity, which may be potentially bridged in optimal growing conditions.

High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.

Nucleophilic index (NNu) as a significant parameter plays a crucial role in screening of amine catalysts. Indeed, the quantity and variety of amines are extensive. However, only limited amines exhibit an NNu value exceeding 4.0 eV, rendering them potential nucleophiles in chemical reactions. To address this issue, we proposed a computational method to quickly identify amines with high NNu values by using Machine Learning (ML) and high-throughput Density Functional Theory (DFT) calculations. Our approach commenced by training ML models and the exploration of Molecular Fingerprint methods as well as the development of quantitative structure-activity relationship (QSAR) models for the well-known amines based on NNu values derived from DFT calculations. Utilizing explainable Shapley Additive Explanation plots, we were able to determine the five critical substructures that significantly impact the NNu values of amine. The aforementioned conclusion can be applied to produce and cultivate 4920 novel hypothetical amines with high NNu values. The QSAR models were employed to predict the NNu values of 259 well-known and 4920 hypothetical amines, resulting in the identification of five novel hypothetical amines with exceptional NNu values (>4.55 eV). The enhanced NNu values of these novel amines were validated by DFT calculations. One novel hypothetical amine, H1, exhibits an unprecedentedly high NNu value of 5.36 eV, surpassing the maximum value (5.35 eV) observed in well-established amines. Our research strategy efficiently accelerates the discovery of the high nucleophilicity of amines using ML predictions, as well as the DFT calculations.

Internet of things and optimized knn based intelligent transportation system for traffic flow prediction in smart cities

The rapid expansion of urban areas and the increasing number of vehicles on the road have resulted in accidents, traffic congestion, economic repercussions, environmental deterioration, and excessive fuel consumption. A dependable traffic management system is necessary to anticipate and regulate urban traffic patterns. Traffic forecast aids in the prevention of traffic issues. Urban traffic predictions often utilise historical and current traffic flow data to forecast road conditions. This article presents a traffic flow prediction system that utilises the Internet of Things (IoT), machine learning, and feature selection. Internet of Things (IoT) devices located on highways or within cars gather sensor data in real-time. The input data set comprises both real-time Internet of Things (IoT) data and historical traffic statistics. The input data is stored in a centralized cloud. The data is subjected to preprocessing in order to eliminate any unwanted interference and identify any exceptional values. The accuracy and root mean square error are contingent upon the process of feature selection. Particle swarm optimization identifies and extracts crucial features from input data. The classification model is constructed using K Nearest Neighbor, Multi layer Perceptron, and Bayes network approaches. The UCI traffic data is used for conducting experiments. The dataset has 47 attributes and 2102 occurrences. The accuracy of traffic flow prediction using PSO KNN is 96 %. The PSO KNN algorithm achieved a Mean Square Error (MSE) of 0.00289 and a Root Mean Square Error (RMSE) of 0.0595.

MONITORING OF LIGHT POLLUTION IN THE TRANSCARPATHIAN REGION

Light pollution first gained attention when people realized they could no longer see the night sky as they once did due to excess visible and ultraviolet light from cities. However, in recent years, it has become clear that artificial night lighting worries not only astronomers. Studies have shown that artificial night lighting harms a variety of animals. To preserve the natural darkness of the sky in the world, parks of the dark (or starry) sky are created, which are the areas of a unique natural environment that protect the natural night darkness from pollution by artificial light. They are the equivalent of nature reserves — territories with exceptional natural value. They perform protective functions for the darkest corners of our planet, where the night environment is not dis- turbed by artificial light. These parks perform not only ecological but also educational functions. Darkness protection is slowly being incorporated into existing conservation areas such as national parks. Darkness is a natural resource that needs protection. In 2016, Transcarpathian Dark Sky Park was created. For its registration and entry into the International Association of Dark Sky Parks, the brightness of the night sky was measured in different places in this park to determine the state of light pollution in this area. The results of the measurements fully satisfied the requirements for dark sky parks. In all places of the Transcarpath- ian Dark Sky Park where we performed measurements, the average value of the background of the night sky was ~21.50 mag/ arcsec 2 . In 2021, an application for registration of Transcarpathian Dark Sky Park in the International Association of Dark Sky Parks was accepted. Research into the state of light pollution on the outskirts of the Dark Sky Park is also ongoing, namely at two optical observation stations — Uzhhorod and Derenivka. The results of changes in the background of the night sky in these places over a 40-year time interval are presented.

Harmonized Interphase Refinement for Robust Garnet Solid‐State Batteries

AbstractGarnet electrolyte Li6.5La3Zr1.5Ta0.5O12 (LLZTO) has been identified as a promising candidate for solid‐state batteries (SSBs). However, the implementation of garnet‐based SSBs is severely restricted owing to the Li dendrite originating from the uneven Li+ deposition and the electron leakage. Herein, one high‐performance garnet‐based SSB is proposed through the enhancement of interfacial dynamics and the inhibition of electron penetration, induced by an artificial harmonized interphase (LSF). The formation of a tightly bonded LLZTO|Li interface is facilitated by the Li3Sb with lower interfacial energies against LLZTO and Li, elucidated by the density functional theory (DFT) calculations. Furthermore, electron leakage and dendrite infiltration are effectively suppressed by the LiF with the electron‐insulating nature and an exceptional γE value. Therefore, a low interfacial resistance of 4.8 Ω cm2 is successfully achieved by the utilization of the functional LSF interphase layer, and the Li|LLZTO‐LSF|Li symmetric cell displayed prolonged Li plating/stripping stability over 1200 h at 0.3 mA cm−2. Moreover, the LFP|LLZTO‐LSF|Li full cell also exhibited notable cycling performance (93.1% capacity retention after 200 cycles at 1 C). The utilization of a synergistic interlayer has been identified as an effective strategy for the advancement of garnet‐based solid‐state lithium batteries.

Promising porous spherical PbI2/poly-2-aminobenzenethiol nanocomposite as a photocathode for hydrogen generation from Red Sea water

A highly efficient porous spherical nanocomposite photocathode, known as PbI2/poly-2-amino benzene thiol (PbI2/P2ABT), is created through a two-step reaction process involving the oxidation of 2-amino benzene thiol with iodine, followed by a double displacement reaction. The resulting nanocomposite displays outstanding morphology, comprising spherical particles with a diameter of 500 nm and featuring nanoscale porosity with pore sizes around 5 nm. Notably, the hydrogen production estimate reaches 9.6 μmole/h·10 cm2, a promising outcome attributed to the environmentally friendly and cost-effective use of natural Red Sea water. The quantification of hydrogen gas is accomplished by assessing the photogenerated carriers using the current density relationship. The calculated Jph value experiences a substantial increase to −0.122 mA.cm−2 compared to a minimal 0.07 mA.cm−2 in the absence of light. Furthermore, the optical assessment reveals exceptional Jph values under 340 nm, reaching 0.121 mA.cm−2, which extends to the visible spectrum with a value of 0.112 mA.cm−2. The remarkable features of this nanocomposite include its cost-effectiveness, ease of fabrication, and scalability for mass production. These qualities collectively enable the conversion of Red Sea water into hydrogen gas, offering a practical and efficient solution aligned with eco-friendly and economically viable practices. This nanocomposite shows significant potential for advancing clean energy technologies and contributing to sustainable hydrogen production from natural water sources.