The development and production of non-noble metal electrocatalysts with exceptional activity and stability for water electrolysis was essential for energy conversion and storage. An optimized working electrode of core-shell nanosphere Fe 2 Co 8 HCF on nickel foam exhibits a small overpotential of 241 mV (63 mV/dec) for OER and 158 mV (92 mV/dec) for HER at 10 mA/cm 2 (without iR correction) in 1.0 M KOH. Fe 2 Co 8 HCF shows ultra-stability (150 h) with loss of 2.9 % and 3.1 % for OER and HER, respectively. The interaction between Fe, Co and HCF that resulted in the formation of core-shell nanostructure was highly beneficial for reaction kinetics. The active bifunctional Fe 2 Co 8 HCF/NF electrode pair aids in the development of a water electrolyzer that provides 10 mA/cm 2 at 1.63 V. The Fe 2 Co 8 HCF/NF//Fe 2 Co 8 HCF/NF displays great durability (over 150 h) with loss of 4.2 %. The solar-driven water electrolysis at 1.63 V demonstrates the enhanced efficiency of an optimized electrocatalyst. These results imply that Fe 2 Co 8 HCF/NF// Fe 2 Co 8 HCF/NF can be utilized to generate a huge amount of hydrogen at low cost.

The oxygen (OER) evolution reaction plays a crucial role for storage of renewable energy sources but, active sites of the active electrocatalysis remain in challengeable. In this work, we have developed sulfonated polyaniline (SPANI) coordinated with Co sites to investigate the OER process. To improve the electrical conductivity and electrocatalytic efficiency towards OER herein, we report Co@SPANI synthesized by solvothermal method. The different physical characterization (SEM, TEM, XRD, IR, XPS and UV‐DRS) and electrochemical methods (voltammetry, chronopotentiometry and EIS) have been used to characterize Co@SPANI materials and examined the correlation of materials with activity. The cobalt doped SPANI (Co@SPANI‐800) exhibits higher electrocatalytic activity, showing smaller Tafel slope of 167 mV dec−1 with lower overpotential of 312 mV at 10 mA cm−2 in 1 M KOH, which reveal that abundant Co‐metal sites remarkably supporting the OER activity. Co@SPANI‐800 exhibits exceptional OER performances and durability over 200 h with loss of <3.5 % in alkaline medium. At 1.54 V, solar powered water electrolysis confirmed the effectiveness of newborn electrocatalyst in solar energy to hydrogen energy conversion. Therefore, this work offered new path for designing materials as self‐supporting electrode for water splitting and for other potential applications.

No abstract

The open communication medium of the Internet of Things (IoT) is more vulnerable to security attacks. As the IoT environment consists of distributed power limited units, the routing protocol used for distributed routing should be light-weighted compared to other centralized networks. In this situation, complex security algorithms and routing mechanisms affect the generic data communications in IoT platforms. To handle this problem, this proposed system develops a cooperative and feedback-based trustable energy-efficient routing protocol (CFTEERP). This protocol calculates local trust value (LTV) and global trust value (GTV) of each node using node attributes and K-means-based feedback evaluation procedures. The K-means clustering algorithm leaves out the distorted node routing metrics and misbehaving node metrics for all channels. This proposed CFTEERP uses the nearest secure node costs to increase the network lifetime without selecting the nearest nodes for routing the data. In this work, secure routing is initiated using multipath routing strategy that analyses LTV, GTV, next trustable node, average throughput, energy consumption, average packet delivery ratio (PDR) and traffic various metrics of entire IoT communication. The technical aspects of proposed system are implemented to solve different existing techniques' limitations.In the comparative experiment, the proposed method provides 90% of PDR and a minimal energy consumption rate of 25% lesser than the existing systems against different malicious attacks.

Biomedical engineering involves ideologies and problem-solving methods of engineering to biology and medicine. Malaria is a life-threatening illness, which has gained significant attention among researchers. Since the manual diagnosis of malaria in a clinical setting is tedious, automated tools based on computational intelligence (CI) tools have gained considerable interest. Though earlier studies were focused on the handcrafted features, the diagnostic accuracy can be boosted through deep learning (DL) methods. This study introduces a new Barnacles Mating Optimizer with Deep Transfer Learning Enabled Biomedical Malaria Parasite Detection and Classification (BMODTL-BMPC) model. The presented BMODTL-BMPC model involves the design of intelligent models for the recognition and classification of malaria parasites. Initially, the Gaussian filtering (GF) approach is employed to eradicate noise in blood smear images. Then, Graph cuts (GC) segmentation technique is applied to determine the affected regions in the blood smear images. Moreover, the barnacles mating optimizer (BMO) algorithm with the NasNetLarge model is employed for the feature extraction process. Furthermore, the extreme learning machine (ELM) classification model is employed for the identification and classification of malaria parasites. To assure the enhanced outcomes of the BMODTL-BMPC technique, a wide-ranging experimentation analysis is performed using a benchmark dataset. The experimental results show that the BMODTL-BMPC technique outperforms other recent approaches.

Now-a-days, almost all music can be easily accessed via the Internet, but at the same time music can be hard to find. This has created the demand for intelligent music retrieval which allows the user to access the songs that he or she likes. The idea of music information retrieval is basically used in music search systems. In a music search system there will be a huge database of songs. For an efficient music search system, when a particular song in the database is requested, the song has to be correctly identified and retrieved from the database. Music information retrieval for polyphonic music is presented here.

No abstract

Water electrolysis focused with electricity or sunlight is one of the sustainable methods to produce hydrogen; this helps to address the global energy demand whereas sluggish OER and HER kinetic barriers hamper this process. Here, we report an earth abundant Co(OH)2 spindle nanosheet electrocatalyst synthesized via surfactant with boron‐assisted release/oxidize mechanistic process and employed it as a bifunctional electrocatalyst (OER/HER) with small overpotential (258 mV/156 mV), low Tafel slope (78 mV dec−1/71 mV dec−1), higher turnover frequency (0.235 s−1/0.100 s−1) and low charge transfer resistance (4.7 Ω). The higher electrochemical active surface area (45 cm2) of the catalyst exploits the potential electrocatalyst nature with overall cell voltage 1.64 V at 10 mA cm−2.