Efficient Piezoelectric Energy Harvesting from a Discrete Hybrid Bismuth Bromide Ferroelectric Templated by Phosphonium Cation

Bismuth containing hybrid molecular ferroelectrics are receiving tremendous attention in recent years owing to their stable and non-toxic composition. However, these perovskite-like structures are primarily limited to ammonium cations. Herein, we report a new phosphonium based discrete perovskite-like hybrid ferroelectric with a formula [Me(Ph)₃P]₃[Bi₂Br₉] ( MTPBB ) and its mechanical energy harvesting capability. The Polarization-Electric field (P-E) measurements resulted in a well-defined ferroelectric hysteresis loop with a remnant polarization value of 2.1 μC cm⁻². Piezoresponse force microscopy experiments enabled visualization of the ferroelectric domain structure and evaluation of the piezoelectric strain coefficient (d₃₃) for an MTPBB single crystal and thin film sample. Furthermore, flexible devices incorporating MTPBB in polydimethylsiloxane (PDMS) matrix at various concentrations were fabricated and explored for their mechanical energy harvesting properties. The champion device with 20 wt % of MTPBB in PDMS rendered a maximum peak-to-peak open-circuit voltage of 22.9 V and a maximum power density of 7 μW cm⁻² at an optimal load of 4 MΩ. Moreover, the potential of MTPBB -based devices in low power electronics was demonstrated by storing the harvested energy in various electrolytic capacitors.     

Ammonia Oxidation Enhanced by Photopotential Generated by Plasmonic Excitation of a Bimetallic Electrocatalyst

We study how visible light influences the activity of an electrocatalyst composed of Au and Pt nanoparticles. The bimetallic composition imparts a dual functionality: the Pt component catalyzes the electrochemical oxidation of ammonia to liberate hydrogen and the Au component absorbs visible light by the excitation of localized surface plasmon resonances. Under visible-light excitation, this catalyst exhibits enhanced electrochemical ammonia oxidation kinetics, outperforming previously reported electrochemical schemes. We trace the enhancement to a photochemical potential resulting from electron–hole carriers generated in the electrocatalyst by plasmonic excitation. The photopotential responsible for enhanced kinetics scales linearly with the light intensity—a general design principle for eliciting superlative photoelectrochemical performance from catalysts comprised of plasmonic metals or hybrids. We also determine a photochemical conversion coefficient.     

Validated LC–MS/MS method for quantitation of a selective JAK1 inhibitor,filgotinib in rat plasma,and its application to a pharmacokinetic study in rats

Filgotinib is a selective JAK1 (Janus kinase) inhibitor, filed in Japan for the treatment of rheumatoid arthritis. In this paper, we report a validated liquid chromatography coupled with tandem mass spectrometry for the quantification of filgotinib in rat plasma using tofacitinib as an internal standard (IS) as per the Food and Drug Administration regulatory guidelines. Filgotinib and the IS were extracted from rat plasma using ethyl acetate as an extraction solvent and chromatographed using an isocratic mobile phase (0.2% formic acid:acetonitrile; 20:80, v/v) at a flow rate of 0.9 mL/min on a Gemini C₁₈ column. Filgotinib and the IS were eluted at ~1.31 and 0.89 min, respectively. The MS/MS ion transitions monitored were m/z 426.3 → 291.3 and m/z 313.2 → 149.2 for filgotinib and the IS, respectively. The calibration range was 0.78–1924 ng/mL. No matrix effect and carryover were observed. Intra- and inter-day accuracies and precisions were within the acceptance range. Filgotinib was stable for three freeze–thaw cycles: on bench-top up to 6 h, in an autosampler up to 21 h, and at −80 ° C for 1 month. This novel method has been applied to a pharmacokinetic study in rats.     

Enantioselective LC–ESI–MS/MS method for quantitation of (−)-lumefantrine and (+)-lumefantrine in mice plasma and application to a pharmacokinetic study

We developed and validated a simple, sensitive, selective, and reliable LC–MS/MS–ESI method for the direct quantitation of lumefantrine (LFN) enantiomers [(−)-LFN and (+)-LFN] in mice plasma as per regulatory guideline. LFN enantiomers and carbamazepine (internal standard) were extracted from mice plasma using Strata X SPE (solid-phase extraction) cartridges. Good resolution between enantiomers was achieved on a Chiralpak IA-3 column using an isocratic mobile phase (0.1% of diethyl amine in methanol), which was delivered at a flow rate of 0.8 mL/min. Detection and quantitation were performed using multiple reaction monitoring mode following the transitions m/z 530.27 → 512.30 and 237.00 → 194.00 for LFN enantiomers and the internal standard, respectively, in the positive-ionization mode. The proposed method provided accurate and reproducible results over the linearity range of 2.39–895 ng/mL for each enantiomer. The intra- and inter-day precisions were in the range of 1.03–6.14 and 6.36–8.70 and 2.03–4.88 and 5.82–11.5 for (−)-LFN and (+)-LFN, respectively. Both (−)-LFN and (+)-LFN were found to be stable under different stability conditions. The method was successfully used to delineate stereoselective pharmacokinetics of LFN enantiomers in mice after an oral administration of rac-LFN (20 mg/kg). The pharmacokinetic results indicated that the disposition of LFN enantiomers was stereoselective in mice.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

Study of degradation behavior of besifloxacin,characterization of its degradation products by LC–ESI–QTOF–MS and their in silico toxicity prediction

Knowledge and understanding of the stability profile of a drug is important as it affects its safety and efficacy. In the present work, besifloxacin, a new, fourth‐generation fluoroquinolone antibiotic, was subjected to different forced‐degradation conditions as per International Conference on Harmonization (ICH) guidelines such as hydrolysis (acid, base and neutral), oxidation, thermal and photolysis. The drug degraded under acidic, basic, oxidative and photolytic conditions while it was found to be stable under dry heat and neutral hydrolytic conditions. In total, five degradation products (DPs) were formed under different conditions—DP1 and DP2 (photolysis), DP3 (oxidation), DP4 (acidic), DP3 and DP5 (basic). The chromatographic separation of besifloxacin and its degradation products was achieved on a Sunfire C₁₈ (250 mm × 4.6 mm, 5 μm) column with 0.1% aqueous formic acid–acetonitrile as a mobile phase. The gradient RP‐HPLC method was developed and validated as per ICH guidelines. The degradation products were characterized with the help of LC–ESI–QTOF mass spectrometric studies and the most likely degradation pathway of the drug was proposed. In silico toxicity assessment of the drug and its degradation products was carried out, which indicated that DP3 and DP4 carry a mutagenicity alert.     

Effective removal of 4-Aminophenol from aqueous environment by pea (Pisum sativum) shells activated with sulfuric acid: Characterization,isotherm, kinetics and thermodynamics

The threat of phenol contamination in aquatic ecosystems is significant for the health of the earth's water systems as well as all humans on it. The present study was conducted to synthesize a cost-effective adsorbent (pea shells activated with sulfuric acid, PSASA) from agriculture waste (pea shells) and its use for effective removal of toxic 4-Aminophenol (4-AP). Newly designed PSASA exhibited significant adsorption of 4-AP which was confirmed by SEM, FT-IR, and XRD analysis. Surface topography confirmed high unevenness of the PSASA surface and the macroporous feature of the PSASA was confirmed by BET analysis. . Multiple testing was done to see how various factors affected adsorption such as adsorbent dose, temperature, pH, PZC, the effect of KCl and urea addition and the effect of the initial concentration of 4-AP. A drop in adsorption uptake of 4-AP was observed as the temperature increases from 25 °C to 45 °C. Maximum adsorption uptake (q_m) was found to be 106.11 mg/g at an optimum pH of 7.0 and 25 °C. Among various adsorption isotherm models tested, Langmuir Isotherm gave the best explanation with high R² values of experimental data. The pseudo-first-order model was found to explain the kinetics of adsorption well. The thermodynamic finding confirms the adsorption process was physical and exothermic. The adsorption of 4-AP was primarily governed by electrostatic interaction, hydrogen-bonding and π-π exchange mechanism. Because of the positive outcomes of the present research, we can use the PSASA as a cost-effective adsorbent for removing phenolic compounds.     

Multi-objective Geometry Optimization of a Gas Cyclone Using Triple-Fidelity Co-Kriging Surrogate Models

Cyclone separators are widely used in a variety of industrial applications. A low-mass loading gas cyclone is characterized by two performance parameters, namely the Euler and Stokes numbers. These parameters are highly sensitive to the geometrical design parameters defining the cyclone. Optimizing the cyclone geometry therefore is a complex problem. Testing a large number of cyclone geometries is impractical due to time constraints. Experimental data and even computational fluid dynamics simulations are time-consuming to perform, with a single simulation or experiment taking several weeks. Simpler analytical models are therefore often used to expedite the design process. However, this comes at the cost of model accuracy. Existing techniques used for cyclone shape optimization in literature do not take multiple fidelities into account. This work combines cheap-to-evaluate well-known mathematical models of cyclones, available data from computational fluid dynamics simulations and experimental data to build a triple-fidelity recursive co-Kriging model. This model can be used as a surrogate with a multi-objective optimization algorithm to identify a Pareto set of a finite number of solutions. The proposed scheme is applied to optimize the cyclone geometry, parametrized by seven design variables.