Hasil untuk "Analytical chemistry"

Cagla Celik Yoldas, Nilay Ildiz, Naim Yagiz Demir et al.

Zhuoyue Yang, Shijun Li, Hangyu Zhang et al.

The skin, the largest organ in the human body, serves as a crucial barrier against external stimuli. With the acceleration of social industrialization and the worsening of global climate change, the risk of physical, chemical and biological damage to the skin has significantly increased. Among these, surgical wounds, accidental injuries, diabetic wounds, and ultraviolet (UV)-radiation-induced photoaging are particularly common. Cutaneous wound healing is a complex and dynamic process that requires precise coordination of numerous molecular events to effectively repair damaged skin. Skin photoaging, a phenomenon of premature aging caused by long-term UV exposure, is characterized by pigmentary abnormalities, telangiectasia, epidermal roughness, wrinkle formation, and precancerous lesions, all of which seriously affect skin health and appearance. Extracellular vesicles (EVs), a class of nano-sized vesicles secreted by various cells, play important regulatory roles in tissue regeneration. Although cell-culture-medium-derived EVs (C-EVs) have been proven to effectively promote skin wound healing and photodamage repair, their origin from a single cell type and challenges in large-scale production severely limit their broad application. In contrast, EVs derived from natural biological resources, including tissue-derived EVs (Ti-EVs) and plant-derived EVs (PDEVs), have emerged as novel therapeutic strategies for skin wounds and photoaging. These EVs better reflect the physiological microenvironment and demonstrate considerably higher production efficiencies. Ti-EVs, obtained from mammalian tissues composed of multiple cell types and extracellular matrix, contain more abundant regulatory factors, thus exhibiting superior bioactivity compared with C-EVs. PDEVs have also garnered significant attention due to their favorable stability, low immunogenicity, unique natural antioxidant components, and feasibility of large-scale extraction. This review will systematically elaborate on the characteristics and isolation methods of both Ti-EVs and PDEVs, as well as their therapeutic roles and underlying mechanism in wound healing and skin photoaging.

Mennah M. Abd Elwahab, Samar Saad, Zeinab A. Sheribah et al.

Abstract White and Green Analytical Chemistry are innovative approaches in analytical chemistry that prioritize both sustainability and efficiency. Together, these approaches aim to advance scientific research while minimizing environmental impact and enhancing safety. This integration of environmental consciousness into analytical practices represents a significant step forward in achieving sustainable scientific progress. In the present study, a sensitive eco-friendly HPLC-DAD method was carried out and validated to allow concurrent determination of Donepezil HCl (DPZ) and Curcumin (CUR) in their pure form and laboratory made nano-liposome formulation. Optimum seperation was accomplished by utilising Zobrax Eclipse Plus C18 column (4.6*100 mm,5 μm) with gradient elution of the mobile phase composed of 0.02 M phosphate buffer at pH 3.2 and ethanol at flow rate of 1.5 ml/min. A diode array detector (DAD) was implemented for detection at 273 nm and 435 nm for DPZ and CUR, respectively, with the column oven set at 40 °C. The method was validated according to ICH specifications in terms of accuracy, precision, linearity range, detection and quantification limit. The calibration plots were linear with correlation coefficients (r2) = 0.999 over the range (0.1–100 µg/ml) and (0.1–100 µg/ml) for DPZ and CUR, successively. The validated HPLC-DAD approach was adopted to analyse both medications in laboratory prepared nano-liposomal formulation in which the analytes were successfully quantified with good recovery values and no disrubtion from the added excipients. The investigation of whiteness, blueness, and greenness metrics revealed a major benefit of the suggested approach over previous reported ones.

Leah Jalowy, Henry Lehmann, Patrick Rassek et al.

Lithium-ion batteries (LIBs) are vital for modern energy storage applications. Lithium iron phosphate (LFP) is a promising cathode material due to its safety, low cost, and environmental friendliness compared to the widely used nickel manganese cobalt oxide (NMC), which contains hazardous nickel and cobalt compounds. However, challenges remain in enhancing the performance of LFP cathodes due to their low electronic and ionic conductivity. To improve both the safety and sustainability of the battery, this work presents a water-based LFP cathode utilizing the bio-based binder carboxymethyl cellulose (CMC), eliminating the need for polyvinylidene fluoride (PVDF) and the toxic solvent N-methyl-2-pyrrolidone (NMP). This study investigates the impact of different dispersing methods—dissolver mixing and wet jet milling—on slurry properties, electrode morphology, and battery performance. Slurries were characterized by rheology, particle size distribution, and sedimentation behavior, while coated and calendered electrodes were examined via thickness measurements and scanning electron microscopy (SEM). Electrochemical performance of the electrodes was evaluated by means of C-Rate testing. The results reveal that dispersing methods significantly influence slurry characteristics but marginally affect electrochemical performance. Compared to dissolver mixing, wet jet milling reduced the median particle size by 39% (ΔD50 = 3.1 µm) and lowered viscosity by 96% at 1 s⁻¹, 80% at 105 s⁻¹, and 64% at 1000 s⁻¹. In contrast, the electrochemical performance of the resulting electrodes differed only slightly, with discharge capacity varying by approximately 12.8% at 1.0 C (Δcapacity = 10.7 mAh g⁻¹). This research highlights the importance of optimizing not only material selection but also processing techniques to advance safer and more sustainable energy storage solutions.

Huda Salem AlSalem, Sara Naif Alharbi, Mohamed A Abdel-Lateef et al.

The increasing use of industrial chemicals has raised major concerns about their environmental and health impacts, with bisphenol A (BPA) being one of the most widely studied contaminants. In this work, we introduce a proof-of-concept approach that combines the peroxidase-like catalytic activity of silver nanowires (AgNWs) with a salting-out assisted liquid–liquid extraction (SALLE) strategy for BPA detection. AgNWs catalyze the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) in an acidic environment, producing a measurable color change that is effectively suppressed in the presence of BPA. This inhibition enables a simple colorimetric quantification of BPA with a detection limit of 31.62 ng/mL (LOQ = 95.83 ng/mL). The method demonstrated a practical linear response within the range of 200–700 ng/mL, making it suitable for screening moderately contaminated water samples. Furthermore, the work offers good recovery values for the extraction of BPA from spiked environmental water samples. Integrating AgNWs nanoenzyme activity with an eco-friendly pre-concentration step provides a promising low-cost, straightforward, and rapid alternative to conventional chromatographic methods, particularly suited for preliminary screening of contaminated waters.

Zonglin Yang, Wanhao Liu, Ben Gao et al.

Scientific discovery plays a pivotal role in advancing human society, and recent progress in large language models (LLMs) suggests their potential to accelerate this process. However, it remains unclear whether LLMs can autonomously generate novel and valid hypotheses in chemistry. In this work, we investigate whether LLMs can discover high-quality chemistry hypotheses given only a research background-comprising a question and/or a survey-without restriction on the domain of the question. We begin with the observation that hypothesis discovery is a seemingly intractable task. To address this, we propose a formal mathematical decomposition grounded in a fundamental assumption: that most chemistry hypotheses can be composed from a research background and a set of inspirations. This decomposition leads to three practical subtasks-retrieving inspirations, composing hypotheses with inspirations, and ranking hypotheses - which together constitute a sufficient set of subtasks for the overall scientific discovery task. We further develop an agentic LLM framework, MOOSE-Chem, that is a direct implementation of this mathematical decomposition. To evaluate this framework, we construct a benchmark of 51 high-impact chemistry papers published and online after January 2024, each manually annotated by PhD chemists with background, inspirations, and hypothesis. The framework is able to rediscover many hypotheses with high similarity to the groundtruth, successfully capturing the core innovations-while ensuring no data contamination since it uses an LLM with knowledge cutoff date prior to 2024. Finally, based on LLM's surprisingly high accuracy on inspiration retrieval, a task with inherently out-of-distribution nature, we propose a bold assumption: that LLMs may already encode latent scientific knowledge associations not yet recognized by humans.

Christian Guzman Ruiz, Matthew Dawson, Mario C. Acosta et al.

Atmospheric models demand a lot of computational power and solving the chemical processes is one of its most computationally intensive components. This work shows how to improve the computational performance of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH), a chemical weather prediction system developed by the Barcelona Supercomputing Center. The model implements the new flexible external package Chemistry Across Multiple Phases (CAMP) for the solving of gas- and aerosol-phase chemical processes, that allows multiple chemical processes to be solved simultaneously as a single system. We introduce a novel strategy to simultaneously solve multiple instances of a chemical mechanism, represented in the model as grid-cells, obtaining a speedup up to 9x using thousands of cells. In addition, we present a GPU strategy for the most time-consuming function of CAMP. The GPU version achieves up to 1.2x speedup compared to CPU. Also, we optimize the memory access in the GPU to increase its speedup up to 1.7x.

Javiera K. Díaz-Berríos, Viviana V. Guzmán, Catherine Walsh et al.

Most stars are born in stellar clusters and their protoplanetary disks, which are the birthplaces of planets, can therefore be affected by the radiation of nearby massive stars. However, little is known about the chemistry of externally irradiated disks, including whether or not their properties are similar to the so-far better-studied isolated disks. Motivated by this question, we present ALMA Band 6 observations of two irradiated Class II protoplanetary disks in the outskirts of the Orion Nebula Cluster (ONC) to explore the chemical composition of disks exposed to (external) FUV radiation fields: the 216-0939 disk and the binary system 253-1536A/B, which are exposed to radiation fields of $10^2-10^3$ times the average interstellar radiation field. We detect lines from CO isotopologues, HCN, H$_2$CO, and C$_2$H toward both protoplanetary disks. Based on the observed disk-integrated line fluxes and flux ratios, we do not find significant differences between isolated and irradiated disks. The observed differences seem to be more closely related to the different stellar masses than to the external radiation field. This suggests that these disks are far enough away from the massive Trapezium stars, that their chemistry is no longer affected by external FUV radiation. Additional observations towards lower-mass disks and disks closer to the massive Trapezium stars are required to elucidate the level of external radiation required to make an impact on the chemistry of planet formation in different kinds of disks.

J Jagadeeswari, V Sabari, A Priyadarsini et al.

Nihar Gami, Krutarth Shukla, Ishan Patel et al.

Background: Significant morbidity and death are linked to sleep apnea (SP), a prevalent sleep disease. For successful management, it is essential to comprehend its prevalence and the risk factors that are linked with it. The purpose of this study was to look at the prevalence of SP in a large patient group that was visiting a tertiary care facility and to discover risk variables that are connected with it. Methods: 500 volunteers were gathered from a tertiary care center to participate in cross-sectional research. Polysomnography, clinical evaluations, and standardized questionnaires were utilized to diagnose SP and gather pertinent information. A statistical study was conducted to evaluate the correlation between different risk factors and SP. Results: 35% of people had SP, with men between the ages of 40 and 60 having a greater frequency. It has been determined that smoking, obesity, and high blood pressure are important risk factors for SP. Compared to those with mild or moderate SP, individuals with severe SP had greater rates of smoking, hypertension, and obesity (BMI > 30). Conclusion: This study emphasizes how common SP is in tertiary care settings and how it is linked to smoking, obesity, and hypertension. Improving patient outcomes and lessening the impact of SP need early identification and management techniques that address these modifiable risk factors.

Guglielmo Mazzola

This Perspective focuses on the several overlaps between quantum algorithms and Monte Carlo methods in the domains of physics and chemistry. We will analyze the challenges and possibilities of integrating established quantum Monte Carlo solutions in quantum algorithms. These include refined energy estimators, parameter optimization, real and imaginary-time dynamics, and variational circuits. Conversely, we will review new ideas in utilizing quantum hardware to accelerate the sampling in statistical classical models, with applications in physics, chemistry, optimization, and machine learning. This review aims to be accessible to both communities and intends to foster further algorithmic developments at the intersection of quantum computing and Monte Carlo methods. Most of the works discussed in this Perspective have emerged within the last two years, indicating a rapidly growing interest in this promising area of research.

Victor P. Debattista, David J. Liddicott, Oscar A. Gonzalez et al.

In Paper I we showed that clumps in high-redshift galaxies, having a high star formation rate density (Σ_SFR), produce disks with two tracks in the [Fe/H]-[α/Fe] chemical space, similar to that of the Milky Way's (MW's) thin + thick disks. Here we investigate the effect of clumps on the bulge's chemistry. The chemistry of the MW's bulge is comprised of a single track with two density peaks separated by a trough. We show that the bulge chemistry of an N-body + smoothed particle hydrodynamics clumpy simulation also has a single track. Star formation within the bulge is itself in the high-Σ_SFR clumpy mode, which ensures that the bulge's chemical track follows that of the thick disk at low [Fe/H] and then extends to high [Fe/H], where it peaks. The peak at low metallicity instead is comprised of a mixture of in-situ stars and stars accreted via clumps. As a result, the trough between the peaks occurs at the end of the thick disk track. We find that the high-metallicity peak dominates near the mid-plane and declines in relative importance with height, as in the MW. The bulge is already rapidly rotating by the end of the clump epoch, with higher rotation at low [α/Fe]. Thus clumpy star formation is able to simultaneously explain the chemodynamic trends of the MW's bulge, thin + thick disks and the Splash.

Fabio J. Cortes Rodriguez, Gianfranco Frattini, Fernando Teixeira Pinto Meireles et al.

MolecularWebXR is our new website for education, science communication and scientific peer discussion in chemistry and biology built on WebXR. It democratizes multi-user, inclusive virtual reality (VR) experiences that are deeply immersive for users wearing high-end headsets, yet allow participation by users with consumer devices such as smartphones, possibly inserted into cardboard goggles for immersivity, or even computers or tablets. With no installs as it is all web-served, MolecularWebXR enables multiple users to simultaneously explore, communicate and discuss chemistry and biology concepts in immersive 3D environments, manipulating objects with their bare hands, either present in the same real space or scattered throughout the globe thanks to built-in audio features. A series of preset rooms cover educational material on chemistry and structural biology, and an empty room can be populated with material prepared ad hoc using moleculARweb's VMD-based PDB2AR tool. We verified ease of use and versatility by users aged 12-80 in entirely virtual sessions or mixed real-virtual sessions at science outreach events, student instruction, scientific collaborations, and conference lectures. MolecularWebXR is available for free use without registration at https://molecularwebxr.org, and a blog post version of this preprint with embedded videos is available at https://go.epfl.ch/molecularwebxr-blog-post.

Veena Paul, T Aby Mathew, Nazia Rasheed et al.

Aims: To compare and evaluate the degree of osseointegration of UV-treated (photo functionalized) and non-treated dental implants surface coated with Calcium phosphate using the Resorbable Blast Media (RBM) technique in an animal model. Settings and Design: Evaluative-Animal study design. Materials and Methods: Six titanium dental implants of diameter 3.2 mm and length of 8 mm with Calcium phosphate coated surface using RBM or resorbable blast media technology (Implant Genesis: Genesis Normo Implant system) were placed epicrestally into the proximal femoral condyle of New Zealand white female rabbits such that each animal received two implants. Before implantation, one out of the two dental implants was photo functionalized with intense UV light for 15 minutes. After twelve weeks of healing, the animals were euthanized and the harvested specimens were analyzed using histomorphometric light microscopy to assess two parameters bone-implant contact and bone volume density. Statistical Analysis Used: SPSS version 23. P less than 0.05 is considered statistically significant. Tests used ANOVA followed by Tukey post hoc test. Results: All six dental implants were osseointegrated. The overall mean bone-implant contact area (BIC) was 57.76% for non-UV treated whereas 88.4367% for UV-treated dental implants. The overall mean bone volume density (BVD) was 32.2333% for non-UV treated whereas 67.7533% for UV-treated dental implants. Conclusion: Significant effects were observed on the osseointegration of dental titanium implants within twelve weeks after UV photo functionalization. The UV photo functionalization of dental titanium implants in the current study significantly altered the BIC and bone density on osseointegration when observed over twelve weeks.

Jenny K. Calahan, Edwin A. Bergin, Arthur D. Bosman et al.

The chemical reservoir within protoplanetary disks has a direct impact on planetary compositions and the potential for life. A long-lived carbon-and nitrogen-rich chemistry at cold temperatures (<=50K) is observed within cold and evolved planet-forming disks. This is evidenced by bright emission from small organic radicals in 1-10 Myr aged systems that would otherwise have frozen out onto grains within 1 Myr. We explain how the chemistry of a planet-forming disk evolves from a cosmic-ray/X-ray-dominated regime to an ultraviolet-dominated chemical equilibrium. This, in turn, will bring about a temporal transition in the chemical reservoir from which planets will accrete. This photochemical dominated gas phase chemistry develops as dust evolves via growth, settling and drift, and the small grain population is depleted from the disk atmosphere. A higher gas-to-dust mass ratio allows for deeper penetration of ultraviolet photons is coupled with a carbon-rich gas (C/O > 1) to form carbon-bearing radicals and ions. This further results in gas phase formation of organic molecules, which then would be accreted by any actively forming planets present in the evolved disk.

Maria Zamyatina, Éric Hébrard, Benjamin Drummond et al.

Transport-induced quenching, i.e., the homogenisation of chemical abundances by atmospheric advection, is thought to occur in the atmospheres of hot gas giant exoplanets. While some numerical modelling of this process exists, the three-dimensional nature of transport-induced chemistry is underexplored. Here we present results of 3D cloud- and haze-free simulations of the atmospheres of HAT-P-11b, HD 189733b, HD 209458b, and WASP-17b including coupled hydrodynamics, radiative transfer and chemistry. Our simulations were performed with two chemical schemes: a chemical kinetics scheme, which is capable of capturing transport-induced quenching, and a simpler, more widely used chemical equilibrium scheme. We find that transport-induced quenching is predicted to occur in atmospheres of all planets in our sample; however, the extent to which it affects their synthetic spectra and phase curves varies from planet to planet. This implies that there is a "sweet spot" for the observability of signatures of transport-induced quenching, which is controlled by the interplay between the dynamics and chemistry.

Grigorii V. Smirnov-Pinchukov, Tamara Molyarova, Dmitry A. Semenov et al.

Aims. With the large amount of molecular emission data from (sub)millimeter observatories and incoming James Webb Space Telescope infrared spectroscopy, access to fast forward models of the chemical composition of protoplanetary disks is of paramount importance. Methods. We used a thermo-chemical modeling code to generate a diverse population of protoplanetary disk models. We trained a K-nearest neighbors (KNN) regressor to instantly predict the chemistry of other disk models. Results. We show that it is possible to accurately reproduce chemistry using just a small subset of physical conditions, thanks to correlations between the local physical conditions in adopted protoplanetary disk models. We discuss the uncertainties and limitations of this method. Conclusions. The proposed method can be used for Bayesian fitting of the line emission data to retrieve disk properties from observations. We present a pipeline for reproducing the same approach on other disk chemical model sets.

Mona A. Abdel Rahman, Mohamed R. Elghobashy, Hala E. Zaazaa et al.

Abstract Etoricoxib (ETO), Paracetamol (PCM), and two toxic impurities for Paracetamol impurity K (4-aminophenol (PAP)) and impurity E (para-hydroxy acetophenone (PHA)) were separated using a simple and selective HPLC method that was tested for the first time. PCM is a commonly used analgesic and antipyretic medication that has recently been incorporated into COVID-19 supportive treatment. Pharmaceuticals containing PCM in combination with other analgesic-antipyretic drugs like ETO help to improve patient compliance. The studied drugs and impurities were separated on a GL Sciences Inertsil ODS-3 (250 × 4.6) mm, 5.0 µm column, and linear gradient elution was performed using 50 mM potassium dihydrogen phosphate adjusted to pH 4.0 with ortho-phosphoric acid and acetonitrile as mobile phase at 2.0 mL/min flow rate at 25 °C and UV detection at 220 nm. The linearity range was 1.5–30.0 µg/mL for ETO and PCM while 0.5–10.0 µg/mL for PAP and PHA, with correlation coefficients (r) for ETO, PCM, PAP, and PHA of 0.9999, 0.9993, 0.9996, and 0.9998, respectively. The proposed method could be used well for routine analysis in quality control laboratory.

Dong Long

Jarrod R. McClean, Nicholas C. Rubin, Joonho Lee et al.

With the rapid development of quantum technology, one of the leading applications is the simulation of chemistry. Interestingly, even before full scale quantum computers are available, quantum computer science has exhibited a remarkable string of results that directly impact what is possible in chemical simulation with any computer. Some of these results even impact our understanding of chemistry in the real world. In this perspective, we take the position that direct chemical simulation is best understood as a digital experiment. While on one hand this clarifies the power of quantum computers to extend our reach, it also shows us the limitations of taking such an approach too directly. Leveraging results that quantum computers cannot outpace the physical world, we build to the controversial stance that some chemical problems are best viewed as problems for which no algorithm can deliver their solution in general, known in computer science as undecidable problems. This has implications for the predictive power of thermodynamic models and topics like the ergodic hypothesis. However, we argue that this perspective is not defeatist, but rather helps shed light on the success of existing chemical models like transition state theory, molecular orbital theory, and thermodynamics as models that benefit from data. We contextualize recent results showing that data-augmented models are more powerful rote simulation. These results help us appreciate the success of traditional chemical theory and anticipate new models learned from experimental data. Not only can quantum computers provide data for such models, but they can extend the class and power of models that utilize data in fundamental ways. These discussions culminate in speculation on new ways for quantum computing and chemistry to interact and our perspective on the eventual roles of quantum computers in the future of chemistry.