Chemical Technique Research Articles

Integrating Vision-Language Models for Accelerated High-Throughput Nutrition Screening.

Addressing the critical need for swift and precise nutritional profiling in healthcare and in food industry, this study pioneers the integration of vision-language models (VLMs) with chemical analysis techniques. A cutting-edge VLM is unveiled, utilizing the expansive UMDFood-90k database, to significantly improve the speed and accuracy of nutrient estimation processes. Demonstrating a macro-AUCROC of 0.921 for lipid quantification, the model exhibits less than 10% variance compared to traditional chemical analyses for over 82% of the analyzed food items. This innovative approach not only accelerates nutritional screening by 36.9% when tested amongst students but also sets a new benchmark in the precision of nutritional data compilation. This research marks a substantial leap forward in food science, employing a blend of advanced computational models and chemical validation to offer a rapid, high-throughput solution for nutritional analysis.

Editorial of Special Issue “Current Trends in Chemistry Towards Biology”

One of the definitions of chemical biology is that it is a scientific discipline spanning the fields of chemistry, biology, and physics; it primarily involves the application of chemical techniques, tools, analyses, and often compounds (also known as chemical probes), which are produced through synthetic chemistry, in order to study and manipulate biological systems [...]

Three-dimensional high-aspect-ratio microarray thick electrodes for high-rate hybrid supercapacitors

Hybrid supercapacitors (HSCs) with facile integration and high process compatibility are considered ideal power sources for portable consumer electronics. However, as a crucial component for storing energy, traditional thin-film electrodes exhibit low energy density. Although increasing the thickness of thin films can enhance the energy density of the electrodes, it gives rise to issues such as poor mechanical stability and long electronic/ion transport pathways. Constructing a stable three-dimensional (3D) ordered thick electrode is considered the key to addressing the aforementioned contradictions. In this work, a manufacturing process combining lithography and chemical deposition techniques is developed to produce large-area and high-aspect-ratio 3D nickel ordered cylindrical array (NiOCA) current collectors. Positive electrodes loaded with nickel–cobalt bimetallic hydroxide (NiOCA/NiCo-LDH) are constructed by electrodeposition, and HSCs are assembled with NiOCA/nitrogen-doped porous carbon (NiOCA/NPC) as negative electrodes. The HSCs exhibits 55 % capacity retention with the current density ranging from 2 to 50 mA cm−2. Moreover, it maintains 98.2 % of the initial capacity after long-term cycling of 15,000 cycles at a current density of 10 mA cm−2. The manufacturing process demonstrates customizability and favorable repeatability. It is anticipated to provide innovative concepts for the large-scale production of 3D microarray thick electrodes for high-performance energy storage system.

Advances in mapping analysis of ribonucleic acid modifications through sequencing

Over 170 chemical modifications have been discovered in various types of ribonucleic acids (RNAs), including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA). These RNA modifications play crucial roles in a wide range of biological processes such as gene expression regulation, RNA stability maintenance, and protein translation. RNA modifications represent a new dimension of gene expression regulation known as the "epitranscriptome". The discovery of RNA modifications and the relevant writers, erasers, and readers provides an important basis for studies on the dynamic regulation and physiological functions of RNA modifications. Owing to the development of detection technologies for RNA modifications, studies on RNA epitranscriptomes have progressed to the single-base resolution, multilayer, and full-coverage stage. Transcriptome-wide methods help discover new RNA modification sites and are of great importance for elucidating the molecular regulatory mechanisms of epitranscriptomics, exploring the disease associations of RNA modifications, and understanding their clinical applications. The existing RNA modification sequencing technologies can be categorized according to the pretreatment approach and sequencing principle as direct high-throughput sequencing, antibody-enrichment sequencing, enzyme-assisted sequencing, chemical labeling-assisted sequencing, metabolic labeling sequencing, and nanopore sequencing technologies. These methods, as well as studies on the functions of RNA modifications, have greatly expanded our understanding of epitranscriptomics. In this review, we summarize the recent progress in RNA modification detection technologies, focusing on the basic principles, advantages, and limitations of different methods. Direct high-throughput sequencing methods do not require complex RNA pretreatment and allow for the mapping of RNA modifications using conventional RNA sequencing methods. However, only a few RNA modifications can be analyzed by high-throughput sequencing. Antibody enrichment followed by high-throughput sequencing has emerged as a crucial approach for mapping RNA modifications, significantly advancing the understanding of RNA modifications and their regulatory functions in different species. However, the resolution of antibody-enrichment sequencing is limited to approximately 100-200 bp. Although chemical crosslinking techniques can achieve single-base resolution, these methods are often complex, and the specificity of the antibodies used in these methods has raised concerns. In particular, the issue of off-target binding by the antibodies requires urgent attention. Enzyme-assisted sequencing has improved the accuracy of the localization analysis of RNA modifications and enables stoichiometric detection with single-base resolution. However, the enzymes used in this technique show poor reactivity, specificity, and sequence preference. Chemical labeling sequencing has become a widely used approach for profiling RNA modifications, particularly by altering reverse transcription (RT) signatures such as RT stops, misincorporations, and deletions. Chemical-assisted sequencing provides a sequence-independent RNA modification detection strategy that enables the localization of multiple RNA modifications. Additionally, when combined with the biotin-streptavidin affinity method, low-abundance RNA modifications can be enriched and detected. Nevertheless, the specificity of many chemical reactions remains problematic, and the development of specific reaction probes for particular modifications should continue in the future to achieve the precise localization of RNA modifications. As an indirect localization method, metabolic labeling sequencing specifically localizes the sites at which modifying enzymes act, which is of great significance in the study of RNA modification functions. However, this method is limited by the intracellular labeling of RNA and cannot be applied to biological samples such as clinical tissues and blood samples. Nanopore sequencing is a direct RNA-sequencing method that does not require RT or the polymerase chain reaction (PCR). However, challenges in analyzing the data obtained from nanopore sequencing, such as the high rate of false positives, must be resolved. Discussing sequencing analysis methods for various types of RNA modifications is instructive for the future development of novel RNA modification mapping technologies, and will aid studies on the functions of RNA modifications across the entire transcriptome.

End-of-Life Plastics Management: A Review

End-of-life plastics present a significant challenge to achieving a sustainable economy. It is crucial to develop environmentally friendly technologies to process the waste streams beyond landfilling. This review provides a detailed overview of end-of-life plastics management, covering mechanical recycling, pyrolysis and hydrocracking methods. Mechanical recycling is the predominant technique employed on a large scale in recycling end-of-life plastics, and this review discusses the technoeconomic assessment and life cycle assessment (LCA) of mechanical recycling. This review also summarises key studies concentrating on chemical recycling techniques for handling end-of-life plastics. Among these, pyrolysis and hydrocracking are discussed in depth. Recent advancements and fundamentals of these two techniques are covered, highlighting their significance in tackling the plastic waste challenge. The prospects of scaling up pyrolysis and hydrocracking technologies are interpreted in terms of technical and economic feasibility. The discussion concludes with recommendations for future research to commercialise chemical recycling of end-of-life plastics.

Innovative approaches in enhanced oil recovery: A focus on gas injection synergies with other EOR methods

Enhanced Oil Recovery (EOR) techniques have become crucial in extending the productive life of mature oil fields and maximizing resource extraction. Among these, gas injection methods, particularly those involving CO₂, nitrogen, and hydrocarbon gases, have shown significant promise. This review focuses on the innovative synergies achieved by combining gas injection with other EOR methods to enhance recovery efficiency and economic viability. Gas injection techniques work by increasing reservoir pressure and reducing oil viscosity, facilitating easier flow and extraction. When integrated with other EOR methods such as thermal, chemical, and microbial techniques, the synergistic effects can lead to even greater enhancements in oil recovery. For instance, the combination of gas injection with thermal EOR, like steam injection, can improve the displacement of heavy oils by simultaneously reducing viscosity and enhancing thermal conductivity within the reservoir. Similarly, integrating gas injection with chemical EOR methods, such as polymer flooding, can optimize the sweep efficiency by leveraging the mobility control provided by polymers and the pressure maintenance by gases. Recent advancements in monitoring and simulation technologies have further improved the effectiveness of these combined approaches. Real-time reservoir simulation and 4D seismic monitoring allow for precise tracking of gas and fluid movements, enabling dynamic adjustments to injection parameters for optimal performance. Smart well technologies, equipped with advanced downhole sensors, provide continuous data on reservoir conditions, facilitating more responsive and adaptive EOR strategies. However, these innovative synergies are not without challenges. Economic feasibility remains a significant concern, particularly given the high costs associated with gas procurement and the integration of multiple EOR techniques. Additionally, managing the complex interactions between different EOR methods and heterogeneous reservoir conditions requires sophisticated modeling and robust operational protocols. In conclusion, the integration of gas injection with other EOR methods offers a promising pathway to enhance oil recovery rates and extend the lifespan of mature reservoirs. Continued research and development, coupled with cross-industry collaboration, are essential to overcoming the economic and technical challenges associated with these innovative approaches. This review underscores the potential for gas injection synergies to revolutionize EOR practices and drive sustainable growth in the oil and gas industry.

Electrochemical behavior and theoretical studies of arylazo (1-naphthyl-2-cyanoacetamide) derivatives as new corrosion inhibitors for Inconel 800 in chloride solution.

In this study, synthesize and insight the corrosion inhibition properties of two novel derivatives of 1-naphthyl-2-cyanoacetamide (NCDs) [2-cyano-2-((5,6-dimethyl-1H-benzo[d]imidazol-2-yl) diazenyl)-N (naphthalene-1-yl)acetamide] (NCD1) and [2-Cyano-N-(naphthalene-1-yl)-2-[(4,6-dimethyl-1H-pyrazolo [3, 4-b] pyridine-3-yl) hydrazono] acetamide] (NCD2). The characterization of the synthesized NCDs was confirmed through the utilization of Mass fragmentation analysis, 1H-NMR, andIR. The corrosioninhibitionperformanceofNCDsas a novel and environmentally safe corrosion inhibitor has been investigated by electrochemical techniques, a chemical technique, and theoretical studies for its anti-corrosion behavior of Inconel 800 in chloride medium. In addition, the surface morphology and inhibitor adsorption on the Inconel 800 surface were confirmed utilizing SEM, EDX, FTIR, and AFM. The advantages of NCDs include their low toxicity, environmental friendliness, ease of preparation, low odor, contain (N, O, and π-Bonds), and the inhibition efficiency elevated with decreasing solution temperature as well as inhibitor dose increase, yielding increased efficiencies of 91.8% and 95.7% for NCD1 and NCD2, respectively, at the optimum concentration of 21 10-6 mol. L-1 and 298 K temperature. An analysis of Tafel plots reveals that NCDs adhere to a mixed and isothermal Langmuir adsorption mechanism. Density Functional Theory (DFT) and Monte Carlo (MC) simulationmanifest the two compounds of NCDs can be adsorbed at the Fe (110) surface in a paralleled way, and can have a smaller energy gap (ΔE) value and exhibit higher efficiency. The experimental and theoretical findings confirm that the synthesized compounds obtained are capable of protecting the Inconel 800 from corrosion by creating an anti-corrosion coating on the surface.

Chiral Herbicide 2,4-D Ethylhexyl Ester: Absolute Configuration, Stereoselective Herbicidal Activity, Crop Safety, and Metabolic Behavior on Maize and Flixweed.

This study represents the initial examination of the herbicidal efficacy, crop safety, and degradation patterns of 2,4-D ethylhexyl ester (2,4-D EHE) at the enantiomeric level. Baseline separation of 2,4-D EHE enantiomers was achieved using a superchiral R-AD column, with their absolute configurations determined through chemical reaction techniques. Evaluation of weed control efficacy against sensitive species such as sun spurge and flixweed demonstrated significantly higher inhibition rates for S-2,4-D EHE compared to R-2,4-D EHE. Conversely, no stereoselectivity was observed in the fresh-weight inhibition rates of both enantiomers on crops or nonsensitive weeds. A sensitive HPLC-MS/MS method was developed to simultaneously detect two enantiomers and the metabolite 2,4-D in plants. Investigation into degradation kinetics revealed no substantial difference in the half-lives of R- and S-2,4-D EHE in maize and flixweed. Notably, the metabolite 2,4-D exhibited prolonged persistence at elevated levels on flixweed, while it degraded rapidly on maize.

Reduction and immobilization of Cr(VI)-contaminated soil using FeSO4 combined with (NH4)2HPO4: The remediation efficiency, mechanisms, and long-term stability

The chemical reduction technique is widely used to remediate Cr(VI)-contaminated soil due to its cost-effective and convenient operation. However, it also suffers from the "yellowing" issue and re-migration of Cr(VI) after on-site remediation. This study hence investigated a new combined treatment material, (NH4)2HPO4 and FeSO4, to enhance the immobilization of Cr(VI) in soil, ultimately inhibiting the "yellowing" phenomenon. The Cr(VI) remediation efficiency, mechanisms, and the long-term stability using FeSO4 with (NH4)2HPO4 were investigated. The Cr(VI) immobilization mechanisms were elucidated using the European Community Bureau of Reference (BCR) sequential extraction procedure, X-ray diffraction (XRD) and X-ray Photoelectron Spectroscopy (XPS). The results suggested that, following the reduction of Cr(VI) to Cr(III) by FeSO4, the presence of (NH4)2HPO4 promoted the formation of residual Cr (CrPO4). At the optimal dose of FeSO4:(NH4)2HPO4:Cr(VI), 5:10:1, 88 % of the 450 mg/kg Cr(VI) in soil was reduced, all the HOAC-extractable Cr (58.67 %) disappeared, while the residual Cr was increased from 6.74 % to 50.61 %. The H2O2 oxidation and simulated rainfall experiments suggested that the extra addition of (NH4)2HPO4 significantly inhibited Cr reoxidation and leachability, possibly due to the formation of residue CrPO4 and FexCr1-x(OH)3, especially when the rainfall`s SO42-:NO3- ratio was 8:1. It is believed that the combination of FeSO4 and common synthetic fertilizer (NH4)2HPO4 is a promising method for in-situ remediation of Cr(VI)-contaminated soil due to its strong resistance to oxidation and acid rain erosion.

Synthesis of surfactant-assisted nickel ferrite nanoparticles (NFNPs@surfactant) to amplify their application as an advanced electrode material for high-performance supercapacitors.

Nickel ferrite nanoparticles (NFNPs) were synthesized in an alkaline medium (pH ∼ 11) using a wet chemical co-precipitation technique. To probe the effect of surfactants on the surface morphology, particle size and size distribution of nanoparticles; two surfactants, namely, cetyl trimethyl ammonium bromide (CTAB) and sodium dodecyl sulphate (SDS), were applied. The native and surfactant-assisted nickel ferrite NPs were characterized using Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), dynamic light scattering (DLS) and transmission electron microscopy (TEM). The addition of surfactants (CTAB/SDS) effectively controlled the secondary growth of nickel ferrite particles and reduced their size, as examined by XRD, AFM, DLS, SEM and TEM. Characterization technique results affirmed that CTAB is a more optimistic surfactant to control the clustering, dispersion and particle size (∼22 nm) of NFNPs. To identify the impact of ferrite particle size on charge storage devices, their electrochemical properties were studied by using cyclic voltammetry (CV), galvanic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) in 1 M KOH electrolyte through three-electrode assembly. NiFe2O4@CTAB showed a specific capacity of 267.1 C g-1, specific capacitance of 593.6 F g-1 and energy density of 16.69 W h kg-1, which was far better than the performances of other synthesized native NFNPs and NiFe2O4@SDS having larger surface areas.

Green Synthesis of Phyllanthus Niruri Nanoparticles for the Treatment of Sickle Cell Anemia

Nanotechnology is currently the most active research area in modern materials science. While numerous chemical and physical methods exist for the synthesis of nanomaterials, the green synthesis approach is increasingly prominent. Plant-mediated synthesis of nanoparticles is a green chemical technique that integrates nanotechnology with botany. This novel method of synthesis ideally occurs at ambient temperatures, neutral pH, and is cost-effective and environmentally friendly. Given this goal, various routes have been explored for synthesizing nanomaterials. The present study aims to formulate and evaluate herbal nanoparticles derived from Phyllanthus niruri for the natural treatment of sickle cell anemia. Sickle cell anemia is characterized by the presence of sickle-shaped erythrocytes caused by abnormal hemoglobin production. This condition leads to clogging of capillaries and obstructs blood flow in the vessels, resulting in severe complications such as ischemia, hypoxia, and organ failure. While some drugs, such as hydroxyurea, are available for treating sickle cell anemia, they are often associated with severe adverse effects, limiting their frequent use. Therefore, this study focuses on designing herbal nanoparticles as an alternative treatment for sickle cell anemia. The plant material for this study was sourced from an authorized market, dried, and powdered for further processing.

Raman spectroscopic imaging – practical applications in industrial pharmacy and medical diagnostics: a review.

Currently, Raman imaging as a non-destructive technique providing knowledge on structural characterization of the investigated samples is gaining more and more interest among industrial formulation and process scientists. In the pharmaceutical sector, the creation of novel products and formulations necessitates flexible and adaptable analysis, and increasingly also imaging capabilities. In this paper, the attention is directed toward the research progress, that has occurred in the application of non-invasive Raman chemical imaging techniques in industrial pharmacy and medical diagnostics in recent years. This work aims to explore the potential of Raman imaging as a knowledge discovery method for the non-destructive evaluation of pharmaceutical formulations as well as human cells to support medical diagnostics in clinical practice. A review of the latest scientific papers indicates that the applications of Raman imaging in pharmaceutical sciences and medical diagnostics are diverse and far-reaching from ensuring the quality of pharmaceutical formulations to studying complex drug delivery systems, monitoring manufacturing processes, and medical diagnostics of cancers and other diseases. As technology continues to evolve, the integration of Raman imaging into pharmaceutical and clinical practices is expected to expand, providing new insights and solutions to the challenges faced by the pharmaceutical industry and medical diagnostics.

A REVIEW OF AQUATIC PLANT BIOMASS PRETREATMENT METHODS FOR BIOGAS PRODUCTION

The increasing global demand for renewable energy sources has led to interest in generating biogas from aquatic plant biomass. This research examines the pretreatment methods of biomass, aiming to enhance the efficiency of biogas production processes. The analysis presents mechanical, chemical, biological, or combined pretreatment techniques, assessing their respective advantages, limitations, and potential synergies. The review extends beyond individual methodologies to identify potential synergies or sequential applications that could maximize biogas production efficiency. This study ultimately facilitates moving the field forward, contributes to the transition to more sustainable energy solutions, identifies gaps in existing researches, paving the way for future investigations and combat to solve upcoming energy problems.

Hydrophobization of Cold Plasma Activated Glass Surfaces by Hexamethyldisilazane Treatment.

The objective of this study was to investigate the modification of glass surfaces by the synergistic combination of cold plasma and chemical surface modification techniques. Glass surface hydrophobicity was obtained as a result of various plasma and deposition operational conditions. The mechanisms governing the hydrophobization process were also studied. Glass plates were activated with plasma using different gases (oxygen and argon) at different treatment times, ranging from 30 to 1800 s. Then, the plasma-treated surfaces were exposed to hexamethyldisilazane vapors at different temperatures, i.e., 25, 60, and 100 °C. Complete characterization, including contact angle measurements, surface free energy calculations, 3D profilometry, X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, and scanning electron microscopy, was accomplished. It was found that the extent of the hydrophobicity effect depends on both the plasma pre-treatment and the specific conditions of the hexamethyldisilazane deposition process. Plasma activation led to the formation of active sites on the glass surface, which promoted the adsorption and reaction of hexamethyldisilazane species, thereby inducing surface chemical modification. Longer plasma pre-treatment resulted in stronger modification on the glass surface, resulting in changes in the surface roughness. The largest water contact angle of ≈100° was obtained for the surface activated by argon plasma for 1800 s and exposed to hexamethyldisilazane vapors at 25 °C. The changes in the surface properties were caused by the introduction of the hydrophobic trimethylsilyl groups onto the glass surface as well as roughness development.

RVDR-YOLOv8: A Weed Target Detection Model Based on Improved YOLOv8

Currently, weed control robots that can accurately identify weeds and carry out removal work are gradually replacing traditional chemical weed control techniques. However, the computational and storage resources of the core processing equipment of weeding robots are limited. Aiming at the current problems of high computation and the high number of model parameters in weeding robots, this paper proposes a lightweight weed target detection model based on the improved YOLOv8 (You Only Look Once Version 8), called RVDR-YOLOv8 (Reversible Column Dilation-wise Residual). First, the backbone network is reconstructed based on RevCol (Reversible Column Networks). The unique reversible columnar structure of the new backbone network not only reduces the computational volume but also improves the model generalisation ability. Second, the C2fDWR module is designed using Dilation-wise Residual and integrated with the reconstructed backbone network, which improves the adaptive ability of the new backbone network RVDR and enhances the model’s recognition accuracy for occluded targets. Again, GSConv is introduced at the neck end instead of traditional convolution to reduce the complexity of computation and network structure while ensuring the model recognition accuracy. Finally, InnerMPDIoU is designed by combining MPDIoU with InnerIoU to improve the prediction accuracy of the model. The experimental results show that the computational complexity of the new model is reduced by 35.8%, the number of parameters is reduced by 35.4% and the model size is reduced by 30.2%, while the mAP50 and mAP50-95 values are improved by 1.7% and 1.1%, respectively, compared to YOLOv8. The overall performance of the new model is improved compared to models such as Faster R-CNN, SSD and RetinaNet. The new model proposed in this paper can achieve the accurate identification of weeds in farmland under the condition of limited hardware resources, which provides theoretical and technical support for the effective control of weeds in farmland.

Structural and dielectric characteristics of doped nickle oxide polyaniline composites

ABSTRACT The PANI-NiO composites were synthesized by employing an in situ chemical polymerization technique, with varying weight percentages of NiO dopant (PANI-5%NiO and PANI-10%NiO). Additionally, AC conductivity, dielectric constant and dielectric loss were investigated within a frequency range from 20 Hz to 1 MHz. XRD confirmed the phase purity and high crystallinity. SEM reveals the granular shape with a porous surface. In addition, the incorporation of NiO with different concentrations influences the composite’s dielectric properties. All samples exhibited frequency-dependent dielectric properties in line with the Maxwell–Wagner model. Notably, the AC conductivity of PANI-10% NiO composite increased as the frequency increased, this behaviour was certified with Jonscher’s power law. The I–V characteristics confirm the ohmic nature of all synthesized samples. Therefore, the potential of PANI and PANI-NiO composites, as efficient dielectric materials, has been explored and can be useful for device applications in diverse fields.

Iron ore rock classification and mine remote sensing inversion based on spectroscopy and improved extreme learning machine

The classification of iron ore rock plays a crucial role in assisting the mine to develop scientifically sound mining strategies. Given the limitations of traditional manual identification and chemical techniques in terms of cost and detection time, it is crucial to develop an economical, high-precision, and efficient classification method for iron ore rocks. This paper takes an iron mine in Anshan as the research center and aims to establish an iron ore rock classification model by combining the improved extreme learning machine (ELM) with near-infrared spectra (NIRS). The NIRS of iron ore rock is denoised and feature extracted using the Savitzky–Golay filter and competitive adaptive reweighted sampling (CARS) methods, respectively. In this paper, we propose the IAdaBoost algorithm by introducing the sample similarity relationship into the weight-updating strategy of the AdaBoost integration algorithm. The weighted extreme learning machine (WELM) is adopted as the base learner for the IAdaBoost algorithm. Furthermore, we employ a multi-strategy improved gray wolf optimization (IGWO) algorithm to optimize the learning rate and the number of integrated base learners in the IAdaBoost algorithm. Consequently, we propose the IGWO-IAdaBoost-WELM model. Compared to other machine learning models, our proposed model performs better and can classify iron ore rocks consistently and efficiently. Meanwhile, we also used the model to invert the remote sensing images of the iron ore mining area, and the results show that the model can achieve fast, efficient, and large-scale iron ore rock classification, which provides an important reference for mining.

Preparation of Au–Ni bimetallic-coated monodisperse PS@Ni/Au microspheres with excellent conductivity and their application in acrylate-based anisotropic conductive adhesives

Anisotropic conductive adhesives (ACAs) provide an efficient and easy method of interconnecting small electronic devices compared to traditional solder joint connections. In this paper, PS@Ni/Au metal composite microspheres with excellent electrical conductivity in the size of 2.76 μm were prepared by chemical plating technique and in situ redox method. The effects of PS@Ni metal composite microspheres with different shell thicknesses and compactness on the preparation of Ni–Au bimetallic shell layers were investigated, and the effects of different Au:PS@Ni mass ratios on the volumetric conductivity of PS@Ni/Au metal composite microspheres were discussed. The composite microspheres were characterized by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), energy spectrometry (EDS), and X-ray diffraction (XRD). Thick and compact Ni metal shells are the key to preparing PS@Ni/Au metal composite microspheres with the complete degree of encapsulation. When the mass ratio of Au:PS@Ni was 0.15:1, the conductivity was as high as 1.3 × 105 S cm−1. The acrylate pressure-sensitive containing 3.1–8.3 vol% conductive particles presented an obvious anisotropy. When the mass ratio of the conductive particles was higher than 8.3 vol%, the conductive particles appear to be significantly aggregated. The research ideas and methods have great application potential for replacing the traditional solder joint connections.

Study of The Optical Properties of Copper Oxide Thin Films Prepared by Chemical Spray Pyrolysis Technique

Study of The Optical Properties of Copper Oxide Thin Films Prepared by Chemical Spray Pyrolysis Technique

Paracoccus kondratievae produces poly(3-hydroxybutyrate) under elevated temperature conditions.

As part of ongoing efforts to discover novel polyhydroxyalkanoate-producing bacterial species, we embarked on characterizing the thermotolerant species, Paracoccus kondratievae, for biopolymer synthesis. Using traditional chemical and thermal characterization techniques, we found that P. kondratievae accumulates poly(3-hydroxybutyrate) (PHB), reaching up to 46.8% of the cell's dry weight after a 24-h incubation at 42°C. Although P. kondratievae is phylogenetically related to the prototypical polyhydroxyalkanoate producer, Paracoccus denitrificans, we observed significant differences in the PHB production dynamics between these two Paracoccus species. Notably, P. kondratievae can grow and produce PHB at elevated temperatures ranging from 42 to 47°C. Furthermore, P. kondratievae reaches its peak PHB content during the early stationary growth phase, specifically after 24 h of growth in a flask culture. This is then followed by a decline in the later stages of the stationary growth phase. The depolymerization observed in this growth phase is facilitated by the abundant presence of the PhaZ depolymerase enzyme associated with PHB granules. We observed the highest PHB levels when the cells were cultivated in a medium with glycerol as the sole carbon source and a carbon-to-nitrogen ratio of 10. Finally, we found that PHB production is induced as an osmotic stress response, similar to other polyhydroxyalkanoate-producing species.