Hasil untuk "Analytical chemistry"

Defu He, Yongming Luo, Shibo Lu et al.

Abstract Microplastics are emerging persistent contaminants of increasing concern. Although microplastics have been extensively detected in aquatic environments, their occurrence in soil ecosystems remains largely unexplored. This review focused on recent progress in analytical methods, pollution characteristics and ecological effects of microplastics in soils. In spite of the presence of microplastics in soils, no standardized methods are available for the quantification. Uniform protocols including microplastic extraction and identification are urgently needed to develop. In soil environments, main sources of microplastics include mulching film, sludge, wastewater irrigation and atmospheric deposition. The fate of microplastics is closely related to soil physio-chemistry and biota. Existing evidence shows that microplastics can influence soil biota at different trophic levels, and even threaten human health through food chains. Therefore, further research is needed to fully reveal the fate and ecological risks of microplastics in soils; and necessary action is required to control microplastic pollution in terrestrial ecosystems.

W. Horwitz

Zhi‐Yuan Gu, Cheng‐Xiong Yang, Na Chang et al.

S. Sandberg, C. Fraser, A. Horvath et al.

P. Nowak, P. Kościelniak

Evaluation of an analytical method is a fundamental problem in analytical chemistry, and it is never straightforward. In this article we show a perspective for facing this issue using an original tool. We propose a model that allows one to evaluate any analytical method/procedure in a global manner. It refers to the RGB additive color model, and uses three primary colors to represent three main attributes of the evaluated method: analytical performance - Red, compliance with the "green" chemistry principles - Green, and productivity/practical effectiveness - Blue. A final color of the method results from the additive synthesis of the primary colors. To simplify classifications, we propose the set of nine final colors of the method (white, magenta, cyan, yellow, red, green, blue, colorless/gray, and black). The model provides also a quantitative parameter, named as the "method brilliance", which integrates all primary colors and treats them with the varying importance, adjusted to the evaluation context and subjective user preferences. The evaluation is performed using standard Excel worksheets interpretable "at a glance", and adjustable to the particular method specifications. We discuss the opportunities offered by this model, potential obstacles and related countermeasures, as well as future perspective for its utilization. The paper shows also examples of using the model for the evaluation of real methods. We believe that the model can be applied not only in analytical science, but also in other chemical sub-disciplines.

Jiace Sun, Garnet Kin-Lic Chan

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.

Mijie Pang, Jianbing Jin, Arjo Segers et al.

Atmospheric chemistry encapsulates the emission of various pollutants, the complex chemistry reactions, and the meteorology dominant transport, which form a dynamic system that governs air quality. While deep learning (DL) models have shown promise in capturing intricate patterns for forecasting individual atmospheric component - such as PM2.5 and ozone - the critical interactions among multiple pollutants and the combined influence of emissions and meteorology are often overlook. This study introduces an advanced DL-based atmospheric chemistry transport model Zeeman for multi-component atmospheric chemistry simulation. Leveraging an attention mechanism, our model effectively captures the nuanced relationships among these constituents. Performance metrics demonstrate that our approach rivals numerical models, offering an efficient solution for atmospheric chemistry. In the future, this model could be further integrated with data assimilation techniques to facilitate efficient and accurate atmospheric emission estimation and concentration forecast.

Hans Gundlach, Keeper Sharkey, Jayson Lynch et al.

For decades, computational chemistry has been posited as one of the areas in which quantum computing would revolutionize. However, the algorithmic advantages that fault-tolerant quantum computers have for chemistry can be overwhelmed by other disadvantages, such as error correction, processor speed, etc. To assess when quantum computing will be disruptive to computational chemistry, we compare a wide range of classical methods to quantum computational methods by extending the framework proposed by Choi, Moses, and Thompson. Our approach accounts for the characteristics of classical and quantum algorithms, and hardware, both today and as they improve. We find that in many cases, classical computational chemistry methods will likely remain superior to quantum algorithms for at least the next couple of decades. Nevertheless, quantum computers are likely to make important contributions in two important areas. First, for simulations with tens or hundreds of atoms, highly accurate methods such as Full Configuration Interaction are likely to be surpassed by quantum phase estimation in the coming decade. Secondly, in cases where quantum phase estimation is most efficient less accurate methods like Couple Cluster and Moller-Plesset, could be surpassed in fifteen to twenty years if the technical advancements for quantum computers are favorable. Overall, we find that in the next decade or so, quantum computing will be most impactful for highly accurate computations with small to medium-sized molecules, whereas classical computers will likely remain the typical choice for calculations of larger molecules.

Damini D. Salunke, Ashwini A. Aher, Sunil N. Thitame

One of which is several endocrine abnormalities, which are associated with obesity due to changing the hypothalamic—pituitary hormone axis and include growth hormone insufficiency, hypothyroidism, and Cushing disease and hypogonadism. Apart from storing energy, adipose tissue is involved in numerous other critical functions that can be catalyzed by adipocytes secretion of hormones (i.e., adiponectin) and chemicals (i.e., leptin). In addition, polycystic ovarian syndrome is due to the hyperinsulinemia and contributes to Obesity, as hyperinsulinemia is the main cause of obesity, and the function of adipose tissue in hypothalamic pituitary endocrine axis. Diabetes, especially T2D can be consider as insulin resistance, compromised glucose homeostasis and beta cell dysfunction. New discoveries showing that inflammation, gut microbiota, and adipose tissue are involved in the formation of the insulin resistance (multifactorial character of insulin resistance) have been made. Furthermore, advances in the pharmaceutical therapies have shown promising results in terms of the management of obesity with bariatric surgery, SGLT2 inhibitors, and GLP-1 receptor agonists in the enhancement of glycemic control. A possible approach towards more successful interventions is provided by the integration of personalized medicine, which targets certain biological pathways and genetic variants. The current developments in the molecular causes of obesity and diabetes, as well as the changing treatment landscape, are highlighted in this review. These developments eventually open the door to better patient outcomes and the possibility of more customized therapeutic approaches.

Fatma Kurul, Beyzanur Doruk, Seda Nur Topkaya

Abstract Green chemistry is an interdisciplinary field that focuses on minimizing hazardous substances and promoting sustainable alternatives in chemical processes to conventional chemical processes and products. This review provides a comprehensive analysis of the fundamental principles, historical development, and practical applications of green chemistry with a particular emphasis on its role in advancing sustainable chemical synthesis, analytical methodologies, and industrial practices. Originating from the environmental activism of the 1960 s inspired by Rachel Carson's"Silent Spring,"green chemistry was formally established in the 1990 s through the 12 principles set by Paul Anastas and John C. Warner. These principles emphasize waste prevention, atomic economy, reducing hazardous chemicals, and using renewable raw materials. Green chemistry significantly impacts sectors such as pharmaceuticals, cosmetics, and education. In the pharmaceutical industry, it fosters environmentally safer analytical methods. The cosmetics sector benefits from biodegradable materials, while educational institutions implement sustainable waste management and laboratory practices. International conferences and academic publications have advanced global awareness of green chemistry, promoting sustainability goals like reducing environmental impacts, optimizing resource use, and minimizing waste. A key focus of this study is the green synthesis of nanoparticles which has emerged as a sustainable alternative to traditional synthesis methods that often rely on toxic reagents Plant-derived biomolecules serve as reducing and stabilizing agents in the synthesis of silver nanoparticles (AgNPs). These eco-friendly approaches eliminate the hazardous chemicals while yielding biocompatible nanoparticles with enhanced antimicrobial and catalytic properties, demonstrating their potential in nanotechnology and biomedical applications. Additionally, green analytical chemistry has revolutionized chemical monitoring by implementing solvent-free methodologies, real-time pollution tracking, and waste minimization techniques. The integration of green chemistry into academic and industrial settings has played a critical role in addressing global challenges such as environmental pollution, climate change, and resource depletion. This review highlights the necessity of widespread adoption of green chemistry principles to ensure economic sustainability, regulatory compliance, and scientific innovation. Future research should focus on optimizing green synthetic techniques, addressing scalability challenges, and fostering interdisciplinary collaboration to accelerate the transition toward a more sustainable future. Graphical abstract

Saúl Guerrero Rivero, Javier G. Iñañez, Fernando Amores Carredano et al.

The technological development of ceramic production during the early modern period in the Iberian Peninsula is a crucial topic in historical archaeological research. The present study analyzes pottery from Jerez de la Frontera, Andalusia, focusing on ceramic materials from the Convent of Santo Domingo (late 15th to early 17th centuries). Through the analysis of production wastes, including <i>dolia</i> and olive jars (<i>botijas</i>), this text unveils key aspects of regional ceramics practices. Using a multidisciplinary archaeometric approach, we applied petrography, X-ray diffraction (XRD), and inductively coupled plasma mass spectrometry (ICP-MS) to investigate compositional, technological, and provenance characteristics. The petrographic analysis identified clay matrix variability and mineral inclusions, indicating diverse raw material sources and production techniques. The XRD analysis confirmed key mineral phases that reflect controlled firing temperatures, while the ICP-MS analyses provided trace element profiles that were used to distinguish between local and non-local raw materials. Together, these results reveal technological shifts and resource diversity over time, challenging the assumption that Seville was the sole supplier of ceramics for Atlantic trade. This study establishes Jerez as a potential complementary production center, offering a new understanding of early globalization processes and ceramics manufacturing in southwestern Andalusia.

Haitham A. El Fiky, Mahmoud A. Tantawy, Dina A. Ahmed et al.

Abstract Solid contact electrodes are prevalent in analytical applications due to their superior performance compared to traditional electrodes. Nonetheless, these electrodes have been observed to develop a water layer, which compromises their stability. In this study, we introduce an innovative solid contact ion selective electrode designed to mitigate this issue by incorporating multi-walled carbon nanotubes. This system was utilized for potentiometric sensing of metoprolol and felodipine. Furthermore, molecular imprinted polymer was developed to enhance selectivity for determination of felodipine. The electrode modified with multi-walled carbon nanotubes was employed for the quantification of metoprolol, exhibiting a Nernstian slope of 55.23 mV/decade over a linear concentration range of 1.0 × 10− 7 to 1.0 × 10− 2 mol L− 1, at a pH of 7.0. The molecularly imprinted polymer-modified electrode was utilized for the determination of felodipine, showing slope of 56.089 mV/decade across a linear range of 1.0 × 10− 7 to 1.0 × 10− 4 mol L− 1, at a pH of 3.0. Detection limits for both sensor were less than 8.0 × 10− 8 mol L− 1. The developed sensors were successfully utilized for the quantification of the aforementioned drugs in pharmaceutical tablets, in human plasma samples and in the presence of their degradates. The proposed approach showed a better linearity range and a lower limit of detection for metoprolol quantification compared to its reported potentiometric methods. Moreover, it was the first one to use such an electrochemical technique for felodipine detection.

Robert B. Mann

One of the major developments in classical black hole thermodynamics is the inclusion of vacuum energy in the form of thermodynamic pressure. Known as Black Hole Chemistry, this subdiscipline has led to the realization that anti de Sitter black holes exhibit a broad variety of phase transitions that are essentially the same as those observed in chemical systems. Since the pressure is given in terms of a negative cosmological constant (which parametrizes the vacuum energy), the holographic interpretation of Black Hole Chemistry has remained unclear. In the last few years there has been considerable progress in developing an exact dictionary between the bulk laws of Black Hole Chemistry and the laws of the dual Conformal Field Theory (CFT). Holographic Black Hole Chemistry is now becoming an established subfield, with a full thermodynamic bulk/boundary correspondence, and an emergent understanding of CFT phase behaviour and its correspondence in the bulk. Here I review these developments, highlighting key advances and briefly discussing future prospects for further research.

Juris Kalvans, Juris Freimanis

Context. Dust grains in circumstellar envelopes are likely to have a spread-out temperature distribution. Aims. To investigate how trends in temperature distribution between small and large grains affect the hot corino chemistry of complex organic molecules (COMs) and warm carbon-chain chemistry (WCCC). Methods. A multi-grain multi-layer astrochemical code with an up-to-date treatment of surface chemistry was used with three grain temperature trends: grain temperature proportional to grain radius to the power -1/6 (Model M-1/6), to 0 (M0), and to 1/6 (M1/6). The cases of hot corino and WCCC chemistry were investigated, for a total of six models. The essence of these changes is for the main ice reservoir - small grains - having higher (M-1/6) or lower (M1/6) temperature than the surrounding gas. Results. The chemistry of COMs shows better agreement with observations in models M-1/6 and M1/6 than in Model M0. Model M-1/6 shows best agreement for WCCC because earlier mass-evaporation of methane ice from small grains induces the WCCC phenomenon at lower temperatures. Conclusions. Models considering several grain populations with different temperatures can more precisely reproduce circumstellar chemistry.

Hiroki Sayama

Hash Chemistry, a minimalistic artificial chemistry model of open-ended evolution, has recently been extended to non-spatial and cellular versions. The non-spatial version successfully demonstrated continuous adaptation and unbounded growth of complexity of self-replicating entities, but it did not simulate multiscale ecological interactions among the entities. On the contrary, the cellular version explicitly represented multiscale spatial ecological interactions among evolving patterns, yet it failed to show meaningful adaptive evolution or complexity growth. It remains an open question whether it is possible to create a similar minimalistic evolutionary system that can exhibit all of those desired properties at once within a computationally efficient framework. Here we propose an improved version called Structural Cellular Hash Chemistry (SCHC). In SCHC, individual identities of evolving patterns are explicitly represented and processed as the connected components of the nearest neighbor graph of active cells. The neighborhood connections are established by connecting active cells with other active cells in their Moore neighborhoods in a 2D cellular grid. Evolutionary dynamics in SCHC are simulated via pairwise competitions of two randomly selected patterns, following the approach used in the non-spatial Hash Chemistry. SCHC's computational cost was significantly less than the original and non-spatial versions. Numerical simulations showed that these model modifications achieved spontaneous movement, self-replication and unbounded growth of complexity of spatial evolving patterns, which were clearly visible in space in a highly intuitive manner. Detailed analysis of simulation results showed that there were spatial ecological interactions among self-replicating patterns and their diversity was also substantially promoted in SCHC, neither of which was present in the non-spatial version.

Ali Sahunie

Both rosemary (Rosmarinus officinalis) and marjoram (Origanum majorana) are abundant in phenolic compounds, exhibiting exceptional antioxidant activity. This study aims to assess the impact of rosemary and marjoram extracts on the stability of sunflower oil during storage and repeated heating. Sunflower oil supplemented with herbal extracts or butylated hydroxytoluene (BHA) at a concentration of 200 ​ppm was stored for six months under light and dark conditions at room temperature. Peroxide value (PV), p-anisidine value (An-V), and total oxidation (TOTOX) value were measured to monitor lipid oxidation progression. A significant difference (P ​< ​0.05) was observed between light and dark storage for all studied samples regarding oxidation parameters. The ethanolic extract of rosemary exhibited higher antioxidant activity compared to BHA and other extracts. Furthermore, sunflower oil supplemented with the ethanolic extract of rosemary underwent weekly treatment at 100 ​°C for 30 ​min over four consecutive weeks. Although all oxidation indicators increased during repeated heating, the addition of rosemary and marjoram extracts as well as BHA significantly reduced these indicators. These findings demonstrate that both rosemary extracts and marjoram extracts can serve as natural antioxidants in edible oils.

David K. Cook, Guy Lalonde, Michael J. Oldham et al.

Electronic nicotine delivery systems (ENDSs) are designed as a non-combustible alternative to cigarettes, aiming to deliver nicotine without the harmful byproducts of tobacco combustion. As the category evolves and new ENDS products emerge, it is important to continually assess the levels of toxicologically relevant chemicals in the aerosols and characterize any related toxicology. Herein, we present a proposed framework for characterizing novel ENDS products (i.e., devices and formulations) and determining the reduced risk potential utilizing analytical chemistry and in vitro toxicological studies with a qualitative risk assessment. To demonstrate this proposed framework, long-term stability studies (12 months) analyzing relevant toxicant emissions from six formulations of a next-generation product, JUUL2, were conducted and compared to reference combustible cigarette (CC) smoke under both non-intense and intense puffing regimes. In addition, in vitro cytotoxicity, mutagenicity, and genotoxicity assays were conducted on aerosol and smoke condensates. In all samples, relevant toxicants under both non-intense and intense puffing regimes were substantially lower than those observed in reference CC smoke. Furthermore, neither cytotoxicity, mutagenicity, nor genotoxicity was observed in aerosol condensates generated under both intense and non-intense puffing regimes, in contrast to results observed for reference cigarettes. Following the proposed framework, the results demonstrate that the ENDS products studied in this work generate significantly lower levels of toxicants relative to reference cigarettes and were not cytotoxic, mutagenic, or genotoxic under these in vitro assay conditions.

LI Beibei, WANG Wei, JIANG Feng et al.

Objective： This study aimed to develop an ion chromatography-tandem mass spectrometry (IC-MS/MS) for the analysis of glyphosate and its metabolite amino methyl phosphoric acid (AMPA) residues in tea without derivatization. Methods： Tea samples were ultrasonically extracted with 20 mmol/L NaOH aqueous solution and cleaned up by dispersive solid-phase extraction (150 mg primary-secondary amine (PSA), 15 mg C₁₈, 15 mg graphitized carbon black (GCB)). The samples were separated on an ion chromatographic column AS11-HC-4 μm (2 mm×250 mm) by using an isometric elution procedure of 35 mmol/L aqueous solution of sodium hydroxide as mobile phase. A multiple reactions monitoring (MRM) model was used to obtain the sensitivity of the method, and the isotopically labeled internal standards were applied in the calibration process. Good linearities and recoveries were obtained in the validation process. Results: The correlation coefficients <i>R</i>² were 0.999 8 and 0.998 2, respectively. The detection limits of glyphosate and AMPA in tea were both 0.05 mg/kg, and the quantification limits were both 0.10 mg/kg. The average recoveries of glyphosate and AMPA were 61.2%～104.9% and 61.5%～83.2%, respectively with RSDs less than 20%. Conclusion: This method meets the requirements of green analytical chemistry and can be used for routine detection of glyphosate and aminomethylphosphoric acid residues in tea.

Gita Das

Aim: This study was done for the efficacy assessment of cognitive behavioral therapy (CBT) and various relaxation techniques in patients with suicidal tendencies. Methodology: The study was conducted among 150 patients of attempted suicide for a period of 2 years (January 2017 to January 2019). The participants were randomly allocated into three groups, with 50 patients each receiving CBT, JPMR, and combined treatment (groups I, II, and III, respectively). The Beck Scale for Suicide Ideation (BSI) and the Columbia-Suicide Severity Rating Scale (C-SSRS) score were used for pre- and postassessment of depression in the patients. Student's t- and Chi-square tests were used for analyzing the data recorded. Results: We observed that in group II, the index scores did not change after a period of 2 years with a P > 0.05. However, in groups I and II, the scores significantly decreased with P < 0.001. Conclusion: A combination of relaxation techniques and CBT will help improve the depression related to suicidal tendencies.

Khadiga M. Kelani, Yasmin Mohammed Fayez, Asmaa G. Gad et al.

Abstract A disposable screen-printed sensor has been crafted specifically for therapeutic drug monitoring purposes, particularly for detecting ofloxacin in biological fluids. To enhance selectivity toward ofloxacin, a supramolecular calix [6] arene serves as the ionophore of choice. The sensor incorporates a graphene nanocomposite as an ion-to-electron transducer layer, which not only boosts potential stability but also mitigates potential drift. The developed ofloxacin sensor underwent rigorous characterization following IUPAC guidelines. The linearity range spans from 1 × 10–6 to 1 × 10–2 M, with a measured slope of 59.0 mV/decade. Impressively, it boasts a percentage recovery of 100.18 ± 1.60 and a low detection limit (LOD) of 6 × 10–7 M. Stability assessments indicate reliable performance over an extended period of 8 weeks. The versatility of this sensor extends to various applications, including the determination of ofloxacin in pharmaceutical formulations, bulk powder, and biological fluids. Notably, it has demonstrated efficacy post-bioanalysis validation, adhering to Food and Drug Administration regulations. This advancement holds promise for personalized therapeutic drug monitoring in clinical pharmacy studies and quality control laboratories, thereby optimizing patient care at the point-of-care. Graphical abstract