Hasil untuk "Analytical chemistry"

Charlie Fynn Perkins, Marcus Webb, Fred J. Currell

Understanding the spatio-temporal evolution of radiolytic species created by high-energy electrons in water underpins key applications from radiotherapy and nuclear safety to environmental processing and electron microscopy. Here, using the Manchester Inhomogeneous Radiation Chemistry by Linear Expansions (MIRaCLE) toolkit, we introduce and benchmark a novel approach to simulating these processes. Although the initial conditions are determined stochastically, the subsequent time evolution is calculated deterministically using a continuum representation, derived from those initial conditions. This hybrid approach essentially averages over many chemistry ``trajectories'' simultaneously, often converging to the 1% level in one shot, not requiring multiple runs. We demonstrate this new approach through the calculation of time-dependent G-values for e_{aq}^-$, \dot{\mathrm{OH}} and other radiolytic products, including at unprecedented dose rates where calculations which would take years with a conventional Monte Carlo approach can be performed in mere hours on a commercial laptop. We demonstrate that the main artifact of continuum modelling can be mitigated by a correction term. These results establish MIRaCLE as a flexible and efficient platform for modelling long-timescale radiolysis, providing a bridge between Monte Carlo approaches and macroscopic reaction--diffusion schemes, with broad implications for radiation chemistry in medicine, energy, and materials science.

Othmane Essoubaiy, Adnane Hakem, Faiza Chbel et al.

Background/Objectives: The Casablanca-Settat region of Morocco, located at the interface between Arab and Amazigh cultural zones, has only recently been investigated using autosomal short tandem repeat (STR) markers. The objective of this study was to characterize the genetic diversity and forensic efficiency of 15 autosomal STR loci in the Casablanca-Settat population and to evaluate its genetic relationships with other Moroccan populations. Methods: Fifteen autosomal STR loci were genotyped in 138 unrelated Arabic-speaking individuals from the Casablanca-Settat region. Allele frequencies, Hardy–Weinberg equilibrium, and standard forensic parameters were calculated. The genetic structure of the population was further examined through comparative analyses with 12 previously published Moroccan reference populations using multivariate and phylogenetic approaches. Results: A total of 146 distinct alleles were identified across the 15 loci. D18S51 was the most polymorphic marker (Ho = 0.9203), whereas D3S1358, TPOX, D5S818, and D16S539 exhibited lower allelic diversity. No statistically significant deviation from Hardy–Weinberg equilibrium was detected after correction for multiple testing. The combined power of discrimination exceeded 0.99, and the combined power of exclusion reached 0.99999965, demonstrating the high forensic efficiency of the STR panel. Population structure analyses positioned the Casablanca-Settat population within an intermediate genetic cluster, closely related to central Moroccan populations, consistent with historical gene flow and admixture. Conclusions: This study provides robust autosomal STR reference data for the Casablanca-Settat population, confirming the suitability of these markers for forensic identification in Morocco and offering valuable insights into regional population structure and genetic diversity.

Marwa I. Helmy, Reem H. Obaydo, Dania Nashed et al.

To detect memantine hydrochloride (MEM) and pramipexole dihydrochloride monohydrate (PDM) in pure form, pharmaceutical dosage forms, and spiked human plasma with improved speed and sensitivity, this study presents a novel potentiometric strategy using functionalized magnetic nano-sized iron oxide particles (5 nm) with 2-hydroxypropyl-β-cyclodextrin (2HP-β-CD). These particles were incorporated into the internal solution of the sensor electrode. Performance surpassed previous sensors due to the unique properties of magnetic iron oxide, which enhanced sensitivity and selectivity. Electrochemical evaluation followed IUPAC standards. Linearity was observed for MEM and PDM within 1 × 10−7–1 × 10-² M & 1 × 10−8–1 × 10-² M, respectively. Six weeks of replicate calibration graphs confirmed long-term potential stability and repeatability. Accuracy was validated using the standard addition technique. Experimental variables such as plasticizer type, pH influence, temperature fluctuations, foreign substance interference, and nanoparticle concentration were optimized. This method reflects principles of sustainability by combining excellent analytical performance with environmental and economic benefits. The high whiteness score, assessed via the RGB12 tool, confirms its alignment with white chemistry. This work demonstrates that true sustainability requires not only green practices but also comprehensive attention to analytical efficiency, eco-friendliness, and affordability.

Tian Xue, Jacob P. Covey, Matthew Otten

Quantum chemistry is a promising application of future quantum computers, but the requirements on qubit count and other resources suggest that modular computing architectures will be required. We introduce an implementation of a quantum chemistry algorithm that is distributed across several computational modules: the distributed unitary selective coupled cluster (dUSCC). We design a packing scheme using the pseudo-commutativity of Trotterization to maximize the parallelism while optimizing the scheduling of all inter-module gates around the buffering of inter-module Bell pairs. We demonstrate dUSCC on a 3-cluster (H$_4$)$_3$ chain and show that it naturally utilizes the molecule's structure to reduce inter-module latency. We show that the run time of dUSCC is unchanged with inter-module latency up to $\sim$20$\times$ slower than intra-module gates in the (H$_4$)$_3$ while maintaining chemical accuracy. dUSCC should be "free" in the weakly entangled systems, and the existence of "free" dUSCC can be found efficiently using classical algorithms. This new compilation scheme both leverages pseudo-commutativity and considers inter-module gate scheduling, and potentially provides an efficient distributed compilation of other Trotterized algorithms.

Zehua Zhao, Zhixian Huang, Junren Li et al.

Current benchmarks for evaluating the chemical reasoning capabilities of Large Language Models (LLMs) are limited by oversimplified tasks, lack of process-level evaluation, and misalignment with expert-level chemistry skills. To address these issues, we introduce SUPERChem, a benchmark of 500 expert-curated reasoning-intensive chemistry problems, covering diverse subfields and provided in both multimodal and text-only formats. Original content and an iterative curation pipeline eliminate flawed items and mitigate data contamination. Each problem is paired with an expert-authored solution path, enabling Reasoning Path Fidelity (RPF) scoring to evaluate reasoning quality beyond final-answer accuracy. Evaluations against a human baseline of 40.3% accuracy show that even the best-performing model, GPT-5 (High), reaches only 38.5%, followed closely by Gemini 2.5 Pro (37.9%) and DeepSeek-V3.1-Think (37.3%). SUPERChem elicits multi-step, multimodal reasoning, reveals model-dependent effects of visual information, and distinguishes high-fidelity reasoners from heuristic ones. By providing a challenging benchmark and a reliable evaluation framework, SUPERChem aims to facilitate the advancement of LLMs toward expert-level chemical intelligence. The dataset of the benchmark is available at https://huggingface.co/datasets/ZehuaZhao/SUPERChem.

Wenhui Zhang, Min Zhao, Leqiang Wang et al.

Summary: Metal-organic frameworks (MOFs) based on nanomaterials have attracted attention for tumor microenvironment (TME)-responsive therapy. However, they lack intrinsic imaging capabilities to monitor drug release and predict therapeutic outcomes. Herein, metal-phenolic nanosheets (Cu/EA-MOF) with photoacoustic (PA) imaging property in the second near-infrared window were constructed to achieve diagnosis and treatment for H2S-enriched tumors. Endogenous H2S triggers the decomposition of Cu/EA-MOF into the ellagic acid (EA) and copper sulfide (Cu2-xS), which can be used for chemotherapy and chemodynamic therapy, respectively. Moreover, EA can enhance the efficiency of chemodynamic therapy by boosting superoxide dismutase activity. Importantly, the degradation of Cu/EA-MOF can be indicated via the change of ratiometric PA signal intensity. Furthermore, the NIR-II fluorescent molecule benzobisthiadiazole (BBT) was further introduced into Cu/EA-MOF to investigate the degradation process and drug release. As a promising theranostic nanomaterial, Cu/EA/BBT-MOF is successfully used to achieve effective synergistic therapy and predict therapeutic outcomes.

Kourosh Darvish, Marta Skreta, Yuchi Zhao et al.

Chemistry experiments can be resource- and labor-intensive, often requiring manual tasks like polishing electrodes in electrochemistry. Traditional lab automation infrastructure faces challenges adapting to new experiments. To address this, we introduce ORGANA, an assistive robotic system that automates diverse chemistry experiments using decision-making and perception tools. It makes decisions with chemists in the loop to control robots and lab devices. ORGANA interacts with chemists using Large Language Models (LLMs) to derive experiment goals, handle disambiguation, and provide experiment logs. ORGANA plans and executes complex tasks with visual feedback, while supporting scheduling and parallel task execution. We demonstrate ORGANA's capabilities in solubility, pH measurement, recrystallization, and electrochemistry experiments. In electrochemistry, it executes a 19-step plan in parallel to characterize quinone derivatives for flow batteries. Our user study shows ORGANA reduces frustration and physical demand by over 50%, with users saving an average of 80.3% of their time when using it.

Daniele Locci, Giambattista Aresu, Antonino Petralia et al.

High-energy radiation from stars impacts planetary atmospheres deeply affecting their chemistry, providing departures from chemical equilibrium. While the upper atmospheric layers are dominated by ionizations induced by extreme ultraviolet radiation, deeper into the atmosphere molecular abundances are controlled by a characteristic X-ray dominated chemistry, mainly driven by an energetic secondary electron cascade. In this work, we aim at identifying molecular photochemically induced fingerprints in the transmission spectra of a giant planet atmosphere. We have developed a numerical code capable of synthesizing transmission spectra with arbitrary spectral resolution, exploiting updated infrared photoabsorption cross sections. Chemical mixing ratios are computed using a photochemical model, tailored to investigate high energy ionization processes. We find that in case of high levels of stellar activity, synthetic spectra in both low and high resolutions show significant, potentially observable out-of-equilibrium signatures arising mainly from CO, CH$_4$, C$_2$H$_2$, and HCN.

Jana F. Karthäuser, Dierk Gruhn, Dierk Gruhn et al.

The fouling resistance of zwitterionic coatings is conventionally explained by the strong hydrophilicity of such polymers. Here, the in vitro biocompatibility of a set of systematically varied amphiphilic, zwitterionic copolymers is investigated. Photocrosslinkable, amphiphilic copolymers containing hydrophilic sulfobetaine methacrylate (SPe) and butyl methacrylate (BMA) were systematically synthesized in different ratios (50:50, 70:30, and 90:10) with a fixed content of photo-crosslinker by free radical copolymerization. The copolymers were spin-coated onto substrates and subsequently photocured by UV irradiation. Pure pBMA and pSPe as well as the prepared amphiphilic copolymers showed BMA content-dependent wettability in the dry state, but overall hydrophilic properties a fortiori in aqueous conditions. All polysulfobetaine-containing copolymers showed high resistance against non-specific adsorption (NSA) of proteins, platelet adhesion, thrombocyte activation, and bacterial accumulation. In some cases, the amphiphilic coatings even outperformed the purely hydrophilic pSPe coatings.

P. Krebs, M. Nägele, P. Fomina et al.

Objective: A prototype infrared attenuated total reflection (IR-ATR) laser spectroscopic system designed for in vivo classification of human cartilage tissue according to its histological health status during arthroscopic surgery is presented. Prior to real-world in vivo applications, this so-called osteoarthritis (OA) scanner has been tested at in vitro conditions revealing the challenges associated with complex sample matrices and the accordingly obtained sparse spectral datasets. Methods: In vitro studies on human knee cartilage samples at different contact pressures (i.e., 0.2–0.5 ​MPa) allowed recording cartilage degeneration characteristic IR signatures comparable to in vivo conditions with high temporal resolution. Afterwards, the cartilage samples were assessed based on the clinically acknowledged osteoarthritis cartilage histopathology assessment (OARSI) system and correlated with the obtained sparse IR data. Results: Amide and carbohydrate signal behavior was observed to be almost identical between the obtained sparse IR data and previously measured FTIR data used for sparse partial least squares discriminant analysis (SPLSDA) to identify the spectral regions relevant to cartilage condition. Contact pressures between 0.3 and 0.4 ​MPa seem to provide the best sparse IR spectra for cylindrical (d ​= ​3 ​mm) probe tips. Conclusion: Laser-irradiating IR-ATR spectroscopy is a promising analytical technique for future arthroscopic applications to differentiate healthy and osteoarthritic cartilage tissue. However, this study also revealed that the flexible connection between the laser-based analyzer and the arthroscopic ATR-probe via IR-transparent fiberoptic cables may affect the robustness of the obtained IR data and requires further improvements.

Adineh Aminianfar, Mohammad Hossein Fatemi, Fatemeh Azimi

Black tea, a widely popular non-alcoholic beverage, is renowned for its unique aroma and has attracted significant attention due to its complex composition. However, the chemical profile of Iranian tea remains largely unexplored. In this research, black tea samples from key tea cultivation regions in four geographical areas in northern Iran were firstly analyzed using headspace solid-phase microextraction followed by gas chromatography–mass spectrometry (HS-SPME-GC–MS) to separate, identify, and quantify their volatile organic compounds. Subsequently, employing a robust investigative strategy, we utilized for the first time the well-known multivariate curve resolution-alternating least square (MCR-ALS) method as a deconvolution technique to analyze the complex GC–MS peak clusters of tea samples. This approach effectively addressed challenges such as severe baseline drifts, overlapping peaks, and background noise, enabling the identification of minor components responsible for the distinct flavors and tastes across various samples. The MCR-ALS technique significantly improved the resolution of spectral and elution profiles, enabling both qualitative and semi-quantitative analysis of tea constituents. Qualitative analysis involved comparing resolved peak profiles to theoretical spectra, along with retention indices, while semi-quantification was conducted using the overall volume integration (OVI) approach for volatile compounds, providing a more accurate correlation between peak areas and concentrations. The application of chemometric tools in GC–MS analysis increased the number of recognized components in four tea samples, expanding from 54 to 256 components, all with concentrations exceeding 0.1 %. Among them, 32 volatile compounds were present in every tea sample. Hydrocarbons (including alkenes, alkanes, cycloalkanes, monoterpenes and sesquiterpenes), esters and alcohols were the three major chemical classes, comprising 78 % of the total relative content of volatile compounds. Analyzing black teas from four distinct regions revealed variations not only in their volatile components but also in their relative proportions. This integrated approach provides a comprehensive understanding of the volatile chemical profiles in Iranian black teas, enhances knowledge about their unique characteristics across diverse geographical origin, and lays the groundwork for quality improvement.

Gursimrat Kaur Brar, Vanita Keshav, Surender Pal Singh Sodhi et al.

The removal of tuberosity post extraction of the maxillary third molar is a very rare complication and there has not been ample discussion in the literature. Forceful extraction of a maxillary third molar can lead to soft and hard tissue loss. Various techniques have been used for the management of such defects such as local flaps, free soft tissue flaps, free bone flaps, and even tissue engineering. We present a case report of a large post-traumatic defect of maxillary tuberosity caused by forceful extraction of the maxillary third molar, which was managed conservatively by secondary healing, and the patient is on regular follow-up.

Weitang Li, Jonathan Allcock, Lixue Cheng et al.

TenCirChem is an open-source Python library for simulating variational quantum algorithms for quantum computational chemistry. TenCirChem shows high performance on the simulation of unitary coupled-cluster circuits, using compact representations of quantum states and excitation operators. Additionally, TenCirChem supports noisy circuit simulation and provides algorithms for variational quantum dynamics. TenCirChem's capabilities are demonstrated through various examples, such as the calculation of the potential energy curve of $\textrm{H}_2\textrm{O}$ with a 6-31G(d) basis set using a 34-qubit quantum circuit, the examination of the impact of quantum gate errors on the variational energy of the $\textrm{H}_2$ molecule, and the exploration of the Marcus inverted region for charge transfer rate based on variational quantum dynamics. Furthermore, TenCirChem is capable of running real quantum hardware experiments, making it a versatile tool for both simulation and experimentation in the field of quantum computational chemistry.

Anastasiia Shuba, Ekaterina Anokhina, Ruslan Umarkhanov et al.

Deep eutectic solvents (DESs) have unique physical and chemical properties, such as low vapor pressure, ease of synthesis, stability, and non-toxicity. Although they have found application in areas of research such as organic synthesis, electrochemistry, biocatalysis, and the development of biosensors, their use as sensitive coatings for chemical sensors has not been previously considered. This study examines the fundamental principles of generating sensitive coatings for piezoelectric quartz sensors utilizing hydrophilic deep eutectic solvents (choline + polyalcohols). Thin films from DESs with a melting point above 50 °C, including those in the composite coatings with amorphous silicon oxide, have been studied. The sorption characteristics of the coatings were thoroughly examined via piezoelectric quartz microbalance. It has been demonstrated that the limits of detection and determination of volatile organic compounds in aqueous solutions by films based on DESs exhibit lower limits than other polymer coatings. A novel approach is proposed for processing the kinetic curve of the sorption of volatile substances by films based on DES to improve the reliability and detection of volatile compounds in the gas phase above aqueous solutions. The use of DES-based piezoelectric quarts sensors has been demonstrated for assessing microbiological indicators of milk.

Kayla M Billiard, Amanda R Dershem, Emanuela Gionfriddo

Implementing green analytical methodologies has been one of the main objectives of the analytical chemistry community for the past two decades. Sample preparation and extraction procedures are two parts of analytical method development that can be best adapted to meet the principles of green analytical chemistry. The goal of transitioning to green analytical chemistry is to establish new methods that perform comparably—or superiorly—to traditional methods. The use of assessment tools to provide an objective and concise evaluation of the analytical methods’ adherence to the principles of green analytical chemistry is critical to achieving this goal. In this review, we describe various sample preparation and extraction methods that can be used to increase the greenness of a given analytical method. We gave special emphasis to modern microextraction technologies and their important contributions to the development of new green analytical methods. Several manuscripts in which the greenness of a solid-phase microextraction (SPME) technique was compared to other sample preparation strategies using the Green Analytical Procedure Index (GAPI), a green assessment tool, were reviewed.

Scott Pratt, Dmytro Oliinychenko, Chris Plumberg

Baryon annihilations during the hadronic stage of heavy-ion collisions affects final-state baryon and antibaryon yields and final-state correlations of baryons and antibaryons. Understanding annihilation is important for addressing questions about the chemistry at the beginning of the hadronic stage, and for interpreting charge-balance correlations involving baryons. Here, charge balance functions, using protons and antiprotons binned by relative momentum, rapidity and azimuthal angle, are shown to clarify the amount of annihilation in the hadronic stage. This enables a more accurate extraction of the baryo-chemistry at the beginning of the hadronic stage. Understanding annihilation is also crucial if charge balance correlations are to be used to infer the chemistry of the earliest stages of a heavy-ion collision. Calculations are presented based on microscopic simulations of the hadronic stage coupled to a hydrodynamic description of the earlier stage, along with a detailed modeling of correlations of protons and antiprotons, known as charge-balance functions.

Ross O'Donoghue, Serena Viti, Marco Padovani et al.

Cosmic rays are crucial for the chemistry of molecular clouds and their evolution. They provide essential ionizations, dissociations, heating and energy to the cold, dense cores. As cosmic rays pierce through the clouds they are attenuated and lose energy, which leads to a dependency on the column density of a system. The detailed effects these particles have on the central regions still needs to be fully understood. Here, we revisit how cosmic rays are treated in the UCLCHEM chemical modeling code by including both ionization rate and H2 dissociation rate dependencies alongside the production of cosmic ray induced excited species and we study in detail the effects of these treatments on the chemistry of pre-stellar cores. We find that these treatments can have significant effects on chemical abundances, up to several orders of magnitude, depending on physical conditions. The ionization dependency is the most significant treatment, influencing chemical abundances through increased presence of ionized species, grain desorptions and enhanced chemical reactions. Comparisons to chemical abundances derived from observations show the new treatments reproduce these observations better than the standard handling. It is clear that more advanced treatments of cosmic rays are essential to chemical models and that including this type of dependency provides more accurate chemical representations.

Felix Bänsch, Christoph Steinbeck, Achim Zielesny

Different charge treatment approaches are examined for cyclotide-induced plasma membrane disruption by lipid extraction studied with dissipative particle dynamics. A pure Coulomb approach with truncated forces tuned to avoid individual strong ion pairing still reveals hidden statistical pairing effects that may lead to artificial membrane stabilization or distortion of cyclotide activity depending on the cyclotide’s charge state. While qualitative behavior is not affected in an apparent manner, more sensitive quantitative evaluations can be systematically biased. The findings suggest a charge smearing of point charges by an adequate charge distribution. For large mesoscopic simulation boxes, approximations for the Ewald sum to account for mirror charges due to periodic boundary conditions are of negligible influence.

Aleksandra Garmidolova, Ivelina Desseva, Dasha Mihaylova et al.

Nowadays, the search for food-suitable plant proteins is a great challenge. In addition to their sustainability and nutritional value, the focus is more and more on possible positive interactions with human health. To date, the presence of bioactive peptides encrypted in the structure of protein opens new perspectives, addressing the food industry’s request for new ingredients with technological properties and also the nutraceutical and pharmaceutical sectors based on multifunctional health applications. <i>Lupinus</i> is a sustainable genus of the legume family <i>Fabaceae</i>, and the lupin seed-derived bioactive peptides have demonstrated different effects including anti-inflammatory, antidiabetic, antioxidant, antibacterial, hypocholesterolemic, and antihypertensive activities. This review aims to discuss the current knowledge on lupin protein and their bioactive peptides, highlighting the documented health claims, but also the possibility of allergenicity and the work to be done for the development of new functional products.

Aysu Yarman, Sevinc Kurbanoglu

Since the first reported case of COVID-19 in 2019 in China and the official declaration from the World Health Organization in March 2021 as a pandemic, fast and accurate diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has played a major role worldwide. For this reason, various methods have been developed, comprising reverse transcriptase-polymerase chain reaction (RT-PCR), immunoassays, clustered regularly interspaced short palindromic repeats (CRISPR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and bio(mimetic)sensors. Among the developed methods, RT-PCR is so far the gold standard. Herein, we give an overview of the MIP-based sensors utilized since the beginning of the pandemic.