Innovative Route Research Articles

Durable polymer composites preparation with oxy-delignified banana fiber for automotive parts: A study on mechanical and thermal properties

An innovative process route has been developed to produce modified banana fiber that are used as reinforcement in polypropylene composites for automotive parts. Banana fiber (BF) is modified through, Alkaline peroxide (APF), and oxygen delignification (ODF) treatment to obtain better adhesion and enhanced thermo-mechanical properties. The fiber-reinforced polymer (FRP) composites (10–30 % loading), were prepared through a specified configuration in a co-rotating twin screw extruder followed by injection molding. The results show that the ODF treatment with a 15 % NaOH concentration resulted in an 11-kappa number, which was lower than APF and untreated fiber. The highest improvement in tensile (31.27 ± 2.56) and flexural strength (44.880 ± 1.05 MPa) was achieved for ODF polymer composite and were 20.40 % and 35.6 % higher compared to the untreated fiber. The addition of natural fiber decreased the melt flow index to 7.56 gm/10 min with a slight decrease in hydrophilicity. The thermal stability was increased with enhanced melting, crystallization temperatures, and surface morphology.

Layered high-entropy sulfides: boosting electrocatalytic performance for hydrogen evolution reaction by cocktail effects

Abstract This study explores high-entropy sulfides (HESs) as potential electrocatalysts for the hydrogen evolution reaction (HER). Novel Pa-3 and Pnma structured HESs containing Fe, Mn, Ni, Co and Mo, were synthesized via a facile mechanochemical method. Structural and chemical properties were extensively characterized using x-ray diffraction, transmission electron microscopy, energy-dispersive x-ray spectroscopy, and x-ray photoelectron spectroscopy. The electrocatalytic performance of four as-prepared HESs in alkaline electrolyte for HER reveals the remarkable outperformance compared to medium-entropy and conventional sulfides. Particularly, (Fe0.2Mn0.2Ni0.2Co0.2Mo0.2)S2 demonstrated outstanding activities, with minimal overpotentials (187 mV at 10 mA cm–2) and outstanding durability under harsh alkaline conditions (a mere polarization increase ΔE = 17 mV after 14 h via chronopotentiometry). The remarkable catalytic activities can be attributed to synergistic effects resulting from the cocktail effects within the high-entropy disulfide. The introduction of Mo contributes to the formation of a layered structure, which leads to an increased surface area and thus to a superior HER performance compared to other HES and conventional sulfides. This work demonstrates the promising potential of HES and underscores that further development for catalytic applications paves the way for innovative routes to new and more efficient active materials for HER catalysis.

Learning Strategies from Nature's Blueprint to Cyclic Carbonate Synthesis.

Nature is a remarkable source of inspiration for developing sustainable and eco-friendly synthetic procedures. In recent years, the synthesis of cyclic carbonates has garnered significant attention due to their versatile applications in various fields, including materials science, pharmaceuticals, and green chemistry. Drawing inspiration from nature, researchers have explored innovative synthetic routes that mimic biological processes to produce cyclic carbonates efficiently and sustainably. This article reviews nature-inspired synthetic procedures for cyclic carbonate formation, highlighting the key strategies and principles employed. Through biomimicry, researchers aim to harness the efficiency and selectivity observed in biological systems to develop greener and more sustainable methods for cyclic carbonate synthesis. Integrating bio-inspired strategies offers opportunities for improving synthetic efficiency and contributes to reducing the environmental impact associated with traditional chemical processes. This review underscores the potential of nature-inspired approaches in advancing the field of cyclic carbonate synthesis toward more sustainable and environmentally benign practices, focusing on recent literature.

Efficient nitrite-to-ammonia electroreduction on single Ag sites

Electroreduction of nitrite to ammonia (NO2RR) provides an innovative route for simultaneously achieving waste NO2– removal and valuable NH3 production. Herein, single-atom Ag on hexagonal BN nanosheets (Ag1@h-BN) is developed as an efficient catalyst for the NO2RR. Strikingly, Ag1@h-BN assembled in a flow cell shows the highest NH3-Faradaic efficiency of 92.04 % with the corresponding NH3 yield rate of 1523.6 μmol h−1 cm−2 at a high current density of 266.2 mA cm−2. Theoretical calculations and electrochemical spectroscopic measurements unveil the creation of Ag1-N3 site to selectively activate NO2– and boost the hydrogenation energetics of NO2–-to-NH3 pathway, consequently resulting in the substantially expedited selectivity and activity of Ag1@h-BN for the NO2RR.

Innovative routes: The impact of strategic deviance on corporate success

In this study, we examine the influence of strategic deviance (STD) on U.S. firms' innovation from 2011 to 2019. Our primary findings indicate that STD has a positive effect on a firm's innovation. Furthermore, chain mediation analysis reveals that managerial ability, industry competition, and cash holding partially mediate the impact of STD on U.S. firms' innovation. The robustness of our results is confirmed through the application of two-stage least squares (2SLS) and propensity score matching with difference-in-differences (PSM-DID) to address endogeneity concerns, along with the use of alternative measures of STD. We also find that the impact of STD on innovation is more pronounced in the eastern U.S. and varies across different industries. Our study suggests a positive correlation between STD and corporate innovation, indicating that firms should consider adopting deviant strategies to enhance innovation, thereby benefiting both themselves and the entire industry.

Carbothermal Reduction-Assisted Synthesis of a Carbon-Supported Highly Dispersed PtSn Nanoalloy for the Oxygen Reduction Reaction.

Exploring high-performance and low-platinum-based electrocatalysts to accelerate the oxygen reduction reaction (ORR) at the air cathode of zinc-air batteries remains crucial. Herein, by combining electroless deposition and carbothermal reduction, a nitrogen-doped carbon-supported highly dispersed PtSn alloy nanocatalyst (PtSn/NC) was prepared for a high-efficiency ORR process. Electrochemical measurements show that PtSn/NC exhibits excellent electrocatalytic ORR activity with a half-wave potential of 0.850 V versus reversible hydrogen electrode (RHE), which is higher than that of commercial Pt/C (0.815 V). The PtSn/NC-based (20 μgPt cm-2) rechargeable Zn-air battery exhibited astonishing performance with a maximum power density of up to 150.1 mW cm-2, as well as excellent rate performance and charge/discharge stability. Physical characterization reveals that carbothermal reduction could compel the transformation of Sn oxide into metallic Sn, which then alloys with the deposited Pt atoms to form the PtSn nanoalloy, in which electrons are transferred from Sn atoms to neighboring Pt atoms, thereby improving the ability of Pt-based active sites to catalyze the ORR process in PtSn/NC by optimizing the unoccupied d-band of Pt atoms. This work provides a reliable and innovative route for the rational design of highly dispersed Pt-based alloy ORR electrocatalysts.

Ionic Hydrogel-Based Moisture Electric Generators for Underwater Electronics.

Ubiquitous moisture is of particular interest for sustainable power generation and self-powered electronics. However, current moisture electric generators (MEGs) can only harvest moisture energy in the air, which tremendously limits the energy harvesting efficiency and practical application scenarios. Herein, the operationality of MEG from air to underwater environment, through a sandwiched engineered-hydrogel device with an additional waterproof breathable membrane layer allowing water vapor exchange while preventing liquid water penetration, is expanded. Underwater environment, the device can spontaneously deliver a voltage of 0.55V and a current density of 130µAcm-2 due to the efficient ion separation assisted by negative ions confinement in hydrogel networks. The output can be maintained even under harsh underwater environment with 10% salt concentration, 1ms-1 disturbing flow, as well as >40kPa hydraulic pressure. The engineered hydrogel used for MEG also exhibits excellent self-healing ability, flexibility, and biocompatibility. As the first demonstration of practical applications in self-powered underwater electronics, the MEG device is successfully powering a wireless emitter for remote communication in water. This new type of MEG offers an innovative route for harvesting moisture energy underwater and holds promise in the creation of a new range of innovative electronic devices for marine Internet-of-Things.

Bioupcycling Methane and CO2 for Succinate Production by an Engineered Type I Methanotrophic Bacterium.

Methane, a byproduct of agricultural activities, has shown potential as a nonedible substrate for biomanufacturing. The production of succinate by a methanotrophic bacterium utilizing methane presents an innovative route for the sustainable synthesis of chemicals. In this study, Methylotuvimicrobium buryatense 5GB1S was genetically modified through the reconstruction of an artificial serine cycle to enable the bioconversion of both methane and CO2 into succinate. The 13C labeling analysis confirmed the CO2 fixing in M. buryatense 5GB1S, leading to a 46% improvement in carbon conversion efficiency and a 107% increase in succinate production compared to the wild-type strain. The transcriptome data on carbon metabolisms was assessed to guide future optimizations for strengthening the overall carbon flux from methane to succinate. Finally, the maximum succinate titer of 299.36 mg/L was achieved under oxygen-limited conditions in 3 L bioreactors, which resulted in the volumetric productivity of 199.60 mg/L/day, representing a 23-fold enhancement compared to the wild-type strain. This study offers a new strategy for upcycling greenhouse gases into succinate in a sustainable manner through methanotrophic-based biomanufacturing.

An approach of 2D convolutional neural network–based seismic data fault interpretation with linear annotation and pixel thinking

AbstractThis article introduces an improved method for geological fault interpretation utilizing a 2D convolutional neural network approach with a focus on coalbed horizons, dealing with the problem as an image classification task. At the beginning, linear annotations, reflecting geological fault features, are applied to multiple seismic sections. By considering texture differences between fault and non‐fault areas, we construct samples that represent these distinct zones for training deep neural networks. Initially, fault annotations are transformed into single dots to facilitate pixel‐based processing. To depict a specific dot's geological structure, we employ a matrix clipped around the point, determined by a combination of range and step parameters. Convolutional layers generate filters equivalent to seismic data transformation, streamlining the need for analysis and selection of seismic attributes. The article discusses enhancing the efficiency of 2D convolutional neural network–based fault interpretation by optimizing sample selection, data extraction and model construction procedures. Through the incorporation of data from two mining areas (totalling 27.09 km2) in sample creation, the overall accuracy exceeds 0.99. Recognition extends seamlessly to unlabelled sections, showcasing the innovative technical route and methodology of fault interpretation with linear annotation and pixel‐based thinking. This study presents a method that integrates planar and raster thinking, transitioning from vision‐oriented geological structure annotation to algorithm‐oriented pixel location. The proposed 2D convolutional neural network–based matrix‐oriented fault/non‐fault binary classification demonstrates feasibility and reproducibility, offering a new automated approach for fault detection in coalbeds through convolutional neural network algorithms.

Energy-efficient routing protocol for WSN based on relay node selection and A-star algorithm

Due to miniaturization constraints and manufacturing costs, wireless sensor networks (WSN) sensor nodes are generally outfitted with restricted resources concerning computing capability, energy, data storage capacity, and data delivery rate. These constraints encourage a significant portion of the research issues in WSNs, particularly the energy constraint, which is a fundamental issue. This paper suggests an innovative routing protocol that optimizes energy use called RNS_A-star, which combines a routing algorithm using a relay node and an improved heuristic for the A-star algorithm. The RNS_A-star protocol first applies a data routing algorithm using a relay node, which allows either using a relay node or simply sending the intra-cluster data to the CH. Then, the A-star algorithm is used to construct a multi-hop routing route between the CHs and the base station (BS) in order to find the best path for reducing energy consumption during data transmission. Simulation results show that the suggested RNS_A-star protocol performs better than ECO-BAT, LEACH-IACA, and LEACH protocols regarding energy conservation and extending network lifetime.

A Solar Pyro-Metallurgical Process for Li-ion Batteries Recycling: Proof of Concept

Recycling Li-ion batteries is a delicate but strategic operation that can be performed by either pyrometallurgy, hydrometallurgy or a combination of methods. This paper presents, for the first time, an innovative solar pyrometallurgical route that consists in three steps. They are pyrolysis, mechanical separation and smelting. The process is applied to LiNixMnyCo1-x-yO2 (NMC) cathode material. After pyrolysis at 580°C and smelting at 1000°C, the final product is a Ni-based alloy containing Co, Li and Mn.

Sustainable (-)-Ambrox Production: Chemistry Meets Biocatalysis.

(-)-Ambrox, the most prominent olfactive component of ambergris, is one of the most widely used biodegradable fragrance ingredients. It is traditionally produced from the diterpene sclareol chemically modified and cyclized into (-)-ambrox. The availability of the new feedstock (E)-β-farnesene produced by fermentation opened new routes to (E,E)-homofarnesol as a precursor to (-)-ambrox. Combining the chemical transformation of (E)-β-farnesene to (E,E)-homofarnesol and its enzymatic cyclization with an engineered Squalene Hopene Cyclase provided a new sustainable route for the production of (-)-ambrox at industrial scale. Compared to the traditional synthesis from sclareol, the new and innovative route from (E)-β-farnesene improves atom and step economy, reduces waste production, solvent and energy consumption.

Exploring Stimuli-Responsive Natural Processes for the Fabrication of High-Performance Materials.

Climate change and environmental pollution have underscored the urgency for more sustainable alternatives in synthetic polymer production. Nature's repertoire of biopolymers with excellent multifaceted properties alongside biodegradability could inspire next-generation innovative green polymer fabrication routes. Stimuli-induced processing, driven by changes in environmental factors, such as pH, ionic strength, and mechanical forces, plays a crucial role in natural polymeric self-assembly process. This perspective aims to close the gap in understanding biopolymer formation by highlighting the essential role of stimuli triggers in facilitating the bottom-up fabrication, allowing for the formation of intricate hierarchical structures. In particular, this perspective will delve into the stimuli-responsive processing of high-performance biopolymers produced by mussels, caddisflies, velvet worms, sharks, whelks, and squids, which are known for their robust mechanical properties, durability, and wet adhesion capabilities. Finally, we provide an overview of current advancements and challenges in understanding stimuli-induced natural formation pathways and their translation to biomimetic materials.

One‐Pot Cascade Reaction from Epoxide to Carboxylic Acids Using Bifunctional Fe‐ZSM‐5

AbstractThe quest for sustainable synthesis of carboxylic acids has led to the exploration of innovative routes and catalysts for the oxidative cleavage of carbon−carbon double bonds, prevalent in bio‐derived molecules. This process involves multiple steps including epoxidation, hydrolysis and vicinal diol cleavage, often catalysed by unsustainable homogeneous or noble‐metal catalysts. In this study, we present the utilization of Fe‐ZSM‐5 as a versatile bifunctional catalyst capable of catalysing both hydrolysis and vicinal diol cleavage steps, utilizing propylene oxide as model compound and H2O2 as oxidizing agent. The prepared Fe‐ZSM‐5 features the zeolite intrinsic Lewis and Brønsted acidity functions, essential for the hydrolysis step, as well as high fractions of monomeric FeOx species, crucial for the subsequent vicinal diol cleavage, leading to streamlined carboxylic acids formation in a one‐pot, two‐step process. Moreover, by combining Fe‐ZSM‐5 with TS‐1, renowned for its epoxidation activity, we demonstrate the complete cascade reaction in one pot, under mild conditions, starting from ethylene. Our study expands the utility of cost‐effective zeolite‐based catalysts enriched with abundant Fe metal for the one‐pot oxidative cleavage of C=C double bonds, offering a promising pathway towards sustainable carboxylic acid synthesis.

A large-scale hydrological and hydrodynamic coupled model for flow routing in the Yangtze-Dongting system

In lowland alluvial river systems consisting of mainstream, distributaries, and floodplain lakes, the flow dynamics are characterized by changing backwater effects and seasonal water storage and release, and the bed morphology is unstable due to frequent sediment deposition and erosion. Hence, models that can accurately and efficiently simulate hydraulic interactions with low topographic data demands are required for such water systems. In this study, we present a coupled flow routing model for the Yangtze River-Dongting Lake system by coupling a 1D hydrodynamic model for the mainstream with hydrological models for distributaries and the lake. A new approach is proposed to generate a set of rating curves to represent the combined impacts of the inflow and outlet stage on the lake storage volume, thereby an innovative hydrological routing method fully considering backwater effects is established. Additionally, an implicit fully coupled algorithm is presented to integrate the hydrodynamic and hydrological models, which demonstrates ideal numerical stability and high computational efficiency. The coupled model is applied to flow routing in the Yangtze-Dongting system, with the Nash-Sutcliffe efficiency coefficients above 0.960, and most of the mean absolute error below 0.4 m (1000 m3/s) for stage (discharge). The model is also used to evaluate the impact of topographic changes during 1998–2016 on the flow process. The results indicate that the mainstream stage has decreased notably, while the reduction of the storage capacity of the lake is not yet remarkable. For the model proposed in this paper, only hydrological data and mainstream topographic data are necessary during model development, calibration, and application. In the context of continuous channel/lake bed adjustment in the middle reach of the Yangtze River Basin, the coupled model provides an effective tool for quantitatively evaluating the hydrological regime and flood process of a river system at a full scale.

Local pH variability scenario: Prebiotic synthesis of cyclic dipeptides via prolinamide on the Hadean Earth

Small pools near early volcanoes are recognized as optimal field for the origin of life. However, the significance of pH variability in the polymerization of biomolecules has been undervalued. Within a simulated “warm little pond,” our study illustrates that a pH variability scenario provides an effective and innovative route for the generation of cyclic dipeptides from prolinamide and free amino acids, obviating the necessity for a catalyst. Subsequent investigations reveal the influential roles of activator (trimetaphosphate, abbreviated as P3m), clay minerals such as montmorillonite, calcite, magnetite, and metal ions including Ca2+, Mg2+, Mn2+, which might have been prevalent in the early Earth's environmental conditions, in facilitating this prebiotic synthetic process. In conclusion, this research provides valuable insights into the possible mechanisms of prebiotic cyclic peptide synthesis, which is a crucial step in understanding the origin of life. The proposed pH variability model offers a plausible explanation for how these peptides could have formed under early Earth conditions.

Multifunctional Biocomposites: Synthesis, Characterization, and Prospects for Regenerative Medicine and Controlled Drug Delivery.

This article presents a new method for preparing multifunctional composite biomaterials with applications in advanced biomedical fields. The biomaterials consist of dicalcium phosphate (DCPD) and bioactive silicate glasses (SiO2/Na2O and SiO2/K2O), containing the antibiotic streptomycin sulfate. Materials were deeply characterized by X-ray diffraction and attenuated total reflectance Fourier transform infrared spectroscopy, and zeta potential analysis, UV-visible spectrophotometry, and ion-exchange measurement were applied in a simulating body fluid (SBF) solution. The main results include an in situ chemical transformation of dicalcium phosphate into an apatitic phase under the influence of silicate solutions and the incorporation of the antibiotic. The zeta potential showed a decrease in surface charge from ζ = -24.6 mV to ζ = -16.5 mV. In addition, a controlled and prolonged release of antibiotics was observed over a period of 37 days, with a released concentration of up to 755 ppm. Toxicity tests in mice demonstrated good tolerance of the biomaterials, with no significant adverse effects. Moreover, these biomaterials have shown potent antibacterial activity against various bacterial strains, including Listeria monocytogenes, Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa, suggesting their potential use in tissue engineering, drug delivery, and orthopedic and dental implants. By integrating the antibiotic into the biomaterial composites, we achieved controlled release and prolonged antibacterial efficacy. This research contributes to advancing biomaterials by exploring innovative synthetic routes and showcasing their promise in regenerative medicine and controlled drug delivery.

Catalytic Hydrolysis-Oxidation of Halogenated Methanes over Phase- and Defect-Engineered CePO4: Halogenated Byproduct-Free and Stable Elimination.

Catalytic elimination of halogenated volatile organic compound (HVOC) emissions was still a huge challenge through conventional catalytic combustion technology, such as the formation of halogenated byproducts and the destruction of the catalyst structure; hence, more efficient catalysts or a new route was eagerly desired. In this work, crystal phase- and defect-engineered CePO4 was rationally designed and presented abundant acid sites, moderate redox ability, and superior thermal/chemical stability; the halogenated byproduct-free and stable elimination of HVOCs was achieved especially in the presence of H2O. Hexagonal and defective CePO4 with more structural H2O and Brønsted/Lewis acid sites was more reactive and durable compared with monoclinic CePO4. Based on the phase and defect engineering of CePO4, in situ diffuse reflectance infrared Fourier transform spectra (DRIFTS), and kinetic isotope effect experiments, a hydrolysis-oxidation pathway characterized by the direct involvement of H2O was proposed. Initiatively, an external electric field (5 mA) significantly accelerated the elimination of HVOCs and even 90% conversion of dichloromethane could be obtained at 170 °C over hexagonal CePO4. The structure-performance-dependent relationships of the engineered CePO4 contributed to the rational design of efficient catalysts for HVOC elimination, and this pioneering work on external electric field-assisted catalytic hydrolysis-oxidation established an innovative HVOC elimination route.

One-pot preparation of one-dimensional hierarchically porous carbon@SnO2 nanocomposites for flexible fabric-based supercapacitor electrodes

The design of functional energy storage materials with superior performances has become the focus topic with the growing energy crisis in recent years. Herein, porous carbon nanofibers@tin dioxide (PCNFs@SnO2) composites are prepared by one-pot electrospinning and followed by carbonization. The PCNFs@SnO2 possesses a hierarchically porous structure containing mesopores and micropores. The specific surface area is as high as ∼ 559.4 m2 g−1, and the total pore volume can reach 0.28 cm3 g−1. Meanwhile, the nonwoven fabric surface is coated with a silver layer through the screen printing technique to obtain silver-coated nonwoven fabric (SNF). Importantly, PCNFs@SnO2 and SNF are combined to obtain flexible fabric-based functional materials. As a primary energy application, the prepared PCNFs@SnO2/SNF electrode has a high mass specific capacitance of 583.1 F g−1 at 1 A g−1, a high area specific capacitance of 933 mF cm−2 at 1 mA cm−2, and a good rate capability (70 % at 10 A g−1). The supercapacitor device with two PCNFs@SnO2/SNF electrodes also shows outstanding cycling durability, capacitor retention is as high as ∼ 91.52 %, after 10000 charging/discharging cycles. In brief, our study may provide an innovative route for designing hierarchically porous one-dimensional carbon nanocomposites for supercapacitors with high performances.

Adaptive Location-based Routing Protocols for Dynamic Wireless Sensor Networks in Urban Cyber-physical Systems

This study investigates the development and enhancement of adaptive location-based routing protocols within dynamic wireless sensor networks (WSNs) in urban cyber-physical systems, recommending the implementation of the study’s innovative Urban Adaptive Location-based Routing Protocol (UALRP). This innovative protocol integrates real-time data analytics and adaptive machine learning models into its algorithmic framework to dynamically optimize routing decisions based on continuously changing urban conditions. Through the utilization of data-driven simulation models and machine learning techniques, the research sought to significantly improve the efficiency, reliability, and scalability of urban WSNs. Existing protocols such as Geographic Adaptive Fidelity (GAF), Greedy Perimeter Stateless Routing (GPSR), and Dynamic Source Routing (DSR) were critically assessed under urban settings using extensive datasets detailing New York City's traffic patterns and environmental variables. The analysis demonstrated that while GPSR showed superior performance in terms of latency, throughput, and energy efficiency among the traditional protocols, the introduction of UALRP, with its advanced predictive and adaptive capabilities, can further optimize these metrics. The study affirms the critical role of enhancing location accuracy and the ongoing advancement of machine learning models within urban routing protocols. These insights advocate for the broader implementation of adaptive strategies like UALRP to foster the development of more resilient and efficient urban cyber-physical systems.