Sample Volume Research Articles

Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds

Abstract. We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere (i.e. between layers or outside a cloud system). Despite the fact that the strength of lidar signals from the molecular atmosphere is much lower compared to the in-cloud intervals, studies of MS effects in such regions are of interest from scientific and practical points of view. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view (RFOV). Therefore, the photons scattered within the forward peak escape the sampling volume formed by the RFOV (i.e. the escape effect). We demonstrated that the escape effect is an inherent part of MS properties within the free atmosphere beyond the cloud far edge. In the cases of the ground-based lidar, the MS contribution is lower than 5 % within the regions of the cloud-free molecular atmosphere with a distance from the cloud far edge of about 1 km or higher. In the cases of the space-borne lidar, the rate of decrease of the MS contribution is so slow that the threshold of 5 % can hardly be reached. In addition, the effect of non-uniform beam filling is extremely strong. Therefore, practitioners should employ, with proper precautions, lidar data from regions below the cloud base when treating data of a space-borne lidar. In the case of two-layered cloud, the distance of 1 km is sufficiently large so that the scattered photons emerging from the first layer do not affect signals from the second layer when we are dealing with the ground-based lidar. In contrast, signals from the near edge of the second cloud layer are severely affected by the photons emerging from the first layer in the case of a space-borne lidar. We evaluated the Eloranta model (EM) in extreme conditions and showed its good performance in the cases of ground-based and space-borne lidars. At the same time, we revealed the shortcoming that can affect practical applications of the EM. Namely, values of the key parameters – i.e. the ratios of phase functions in the backscatter direction for the nth-order-scattered photon and a singly scattered photon – depend not only on the particle phase function but also on the distance from a lidar to the cloud and the receiver field of view. Those ratios vary within a quite large range, and the MS contribution to lidar signals can be largely overestimated or underestimated if erroneous values of the ratios are assigned to the EM.

Accurate and non-contact measurement of volume percentages of oil-water fluids using microstrip sensors independent of the volume of sample using artificial neural network

Due to their moderate sensitivity, extremely cheap cost, ease of fabrication method, and, more crucially, the fact that they are non-invasive, planar microwave sensors have attracted a lot of interest from both industries and academics over the past years. These intriguing properties drive this field's research toward opening up a wide range of applications that go beyond oil and gas to include biological, material sensing, pollution monitoring, and other industrial uses. The main focus of this research is on the simulation and fabrication of a high-sensitivity, very small, and repeatable microwave sensor to measure volume fractions of oil and water in real-time. This sensor is designed by Ansys HFSS software and is made on the RT/Duroid 5880 (with εr = 2.2, thickness = 0.787 mm, loss tangent of 0.0009). In a polylactic acid (PLA) box made using a 3D printer, oil and water with different volume percentages will be placed on the microwave sensor in non-contact conditions. To determine volume percentages independent of the volume of the samples, different samples were analyzed in volumes of 5 ml, 10 ml, and 15 ml. The developed sensor includes two passing bands, and when exposed to crude oil with varying amounts of water, the frequencies of these bands, their insertion loss, and their prominence in these frequencies change. Due to the non-linear variations in the insertion loss, frequency, and prominence value of the two passbands, the MLP neural network is used in this study over other approaches for identifying the objective parameter. The MLP neural network's output was the water volume percentage, and its inputs were variations in the frequency, insertion loss, and prominence of the two passbands in the transmission response. Thanks to microwave sensors and artificial neural networks, volume fractions could be detected with high accuracy, independent of the volume of samples. The suggested microwave sensor could be a highly effective way to measure volume percentages in the oil sector because of its high accuracy, compact size, simplicity of transportation, non-contact feature, etc.

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform

Label-free detection of multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. First, we characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles are required.

The Liquid Jet Endstation for Hard X-ray Scattering and Spectroscopy at the Linac Coherent Light Source

The ability to study chemical dynamics on ultrafast timescales has greatly advanced with the introduction of X-ray free electron lasers (XFELs) providing short pulses of intense X-rays tailored to probe atomic structure and electronic configuration. Fully exploiting the full potential of XFELs requires specialized experimental endstations along with the development of techniques and methods to successfully carry out experiments. The liquid jet endstation (LJE) at the Linac Coherent Light Source (LCLS) has been developed to study photochemistry and biochemistry in solution systems using a combination of X-ray solution scattering (XSS), X-ray absorption spectroscopy (XAS), and X-ray emission spectroscopy (XES). The pump–probe setup utilizes an optical laser to excite the sample, which is subsequently probed by a hard X-ray pulse to resolve structural and electronic dynamics at their intrinsic femtosecond timescales. The LJE ensures reliable sample delivery to the X-ray interaction point via various liquid jets, enabling rapid replenishment of thin samples with millimolar concentrations and low sample volumes at the 120 Hz repetition rate of the LCLS beam. This paper provides a detailed description of the LJE design and of the techniques it enables, with an emphasis on the diagnostics required for real-time monitoring of the liquid jet and on the spatiotemporal overlap methods used to optimize the signal. Additionally, various scientific examples are discussed, highlighting the versatility of the LJE.

Double-Sided Tape in Microfluidics: A Cost-Effective Method in Device Fabrication.

The demand for easy-to-use, affordable, accessible, and reliable technology is increasing in biological, chemical, and medical research. Microfluidic devices have the potential to meet these standards by offering cost-effective, highly sensitive, and highly specific diagnostic tests with rapid performance and minimal sample volumes. Traditional microfluidic device fabrication methods, such as photolithography and soft lithography, are time-consuming and require specialized equipment and expertise, making them costly and less accessible to researchers and clinicians and limiting the applicability and potential of microfluidic devices. To address this, researchers have turned to using new low-cost materials, such as double-sided tape for microfluidic device fabrication, which offers simple and low-cost processes. The innovation of low-cost and easy-to-make microfluidic devices improves the potential for more devices to be transitioned from laboratories to commercialized products found in stores, offices, and homes. This review serves as a comprehensive summary of the growing interest in and use of double-sided tape-based microfluidic devices in the last 20 years. It discusses the advantages of using double-sided tape, the fabrication techniques used to create and bond microfluidic devices, and the limitations of this approach in certain applications.

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters

Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters. Therefore, this study investigated the loss of seventy MPs on eight different syringe filters by employing Random Forest, a machine learning algorithm. The results indicate that the loss of MPs during filtration is filter specific, with glass microfiber and polytetrafluoroethylene filters being the most effective (<20%) compared with nylon (>90%) and others (regenerated-cellulose, polyethersulfone, polyvinylidene difluoride, cellulose acetate, and polypropylene). The Random Forest classifier showed outstanding performance (accuracy range 0.81–0.95) for determining whether the loss of MPs on filters exceeded 20%. Important factors in this classification were analyzed using the SHapley Additive exPlanation value and Kruskal–Wallis test. The results show that the physicochemical properties (LogKow/LogD, pKa, functional groups, and charges) of MPs are more important than the operational parameters (sample volume, filter pore size, diameter, and flow rate) in determining the loss of most MPs on syringe filters. However, other important factors such as the implications of the roles of pH for nylon and pre-rinsing for PTFE syringe filters should not be ignored. Overall, this study provides a systematic framework for understanding the behavior of various MP classes and their potential losses on syringe filters.

A simple and highly sensitive LC–MS workflow for characterization and quantification of ADC cleavable payloads

Antibody–drug conjugates (ADC) payloads are cleavable drugs that act as the warhead to exert an ADC’s cytotoxic effects on cancer cells intracellularly. A simple and highly sensitive workflow is developed and validated for the simultaneous quantification of six ADC payloads, namely SN-38, MTX, DXd, MMAE, MMAF and Calicheamicin (CM). The workflow consists of a short and simple sample extraction using a methanol-ethanol mixture, followed by a fast liquid chromatography tandem mass spectrometry (LC–MS/MS) analysis. The results showed that well-validated linear response ranges of 0.4–100 nM for SN38, MTX and DXd, 0.04–100 nM for MMAE and MMAF, 0.4–1000 nM for CM were achieved in mouse serum. Recoveries for all six payloads at three different concentrations (low, medium and high) were more than 85%. An ultra-low sample volume of only 5 µL of serum is required due to the high sensitivity of the method. This validated method was successfully applied to a pharmacokinetic study to quantify MMAE in mouse serum samples.

Synthesis of nano magnetic chitosan modified with acrylamide schiff’s base for simultaneous removal of Cu(II) and Co(II) from waste water samples

ABSTRACT A magnetic nano sorbent based on the functionalization of magnetic chitosan with acrylamide was synthesized for Cu(II) and Co(II) removal from wastewater samples. To characterize the magnetic nano sorbent, they have been applied from Fourier transform infrared spectroscopic analysis (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The effective parameters of Cu(II) and Co(II) adsorption on magnetic nano sorbent such as pH of the solution, adsorbent dose, contact time and sample volume, were optimized. Also, the effective parameters on Cu(II) and Co(II) desorption conditions (type and volume of elution solvent) were optimized. The isotherms and kinetics models for the adsorption of Cu(II) and Co(II) on the magnetic nano sorbent were studied. The data were well-fitted with the Langmuir isotherm and pseudo-second-order model. The maximum adsorption capacities for Cu(II) and Co(II) were 165.4 and 159.9 mg g-1, respectively. Also, the thermodynamic parameters were studied. Application of magnetic nano sorbent for 4 times of use was acceptable. For the real samples, the percentage of recovery was higher than 97% and RSD (%) was between 1.4% and 2.7%. Finally, the magnetic nano sorbent exhibited high performance in removing the Cu(II) and Co(II) from wastewater samples.

Label-free and label-based electrochemical detection of disease biomarker proteins

Introduction: Biosensors, analytical devices integrating biological sensing elements with physicochemical transducers, have gained prominence as rapid and convenient tools for monitoring human health status using biochemical analytes. Due to its cost-effectiveness, simplicity, portability, and user-friendliness, electrochemical detection has emerged as a widely adopted method in biosensor applications. Crucially, biosensors enable early disease diagnosis by detecting protein biomarkers associated with various conditions. These biomarkers offer an objective indication of medical conditions that can be accurately observed from outside the patient. Method: This review comprehensively documents both label-free and labelled detection methods in electrochemical biosensor techniques. Label-free detection mechanisms elicit response signals upon analyte molecule binding to the sensor surface, while labelled detection employs molecular labels such as enzymes, nanoparticles, and fluorescent tags. Conclusion: The selection between label-free and labelled detection methods depends on various factors, including the biomolecular compound used, analyte type and biological binding site, biosensor design, sample volume, operational costs, analysis time, and desired detection limit. Focusing on the past six years, this review highlights the application of label-free and labelled electrochemical biosensors for detecting protein biomarkers of diseases.

Preconcentrating extractive polymeric network in paper-based sensing of copper

The concept of using an extractive polymeric sensing network on a paper-based substrate for the pretreatment of samples in the colorimetric analysis of heavy metals is demonstrated with the determination of Cu2+ in aqueous samples. The newly developed paper-based device combines the advantages of both liquid–liquid extraction-based separation and the analytical capabilities of microfluidic paper-based analytical devices (μPADs). The preconcentrating extractive polymeric network composed of 53.5 wt% poly(vinyl chloride) (PVC), 45 wt% extractant (di-(2-ethylhexyl)phosphoric acid (D2EHPA)) and 1.5 wt% dye (1-(2′-pyridylazo)-2-naphthol (PAN)), coated on filter paper, shows good water-wicking properties, allowing the transmission of high sample volumes. This results in significant analyte preconcentration. The extractant (D2EHPA) selectively binds Fe3+ and Zn2+ which otherwise will compete with Cu2+ in its colour reaction with PAN at the chosen pH of 3.0. The device’s capacity to process higher sample volumes resulting in higher sensitivity is increased by the integration of several filter paper absorption layers. The optimized device is characterized by a limit of detection (LOD) for tap and environmental waters of 3.4 and 9.6 µg/L, respectively; stability of 51 days if stored in a refrigerator; and total analysis time (from sample insertion to colour detection) of less than 5 min.

On the limit behavior of lattice-type metamaterials with bi-stable mechanisms

This paper explores 2D lattice-type metamaterials featuring bi-stable unit cells and predefined symmetry configurations. Our investigation delves into the emergence of phase-transition patterns and probes the limit behavior of these lattice arrangements. We develop a macroscale generalized standard material model based on a quasi-convexified free energy framework and validate it through a specific lattice configuration – a 1D chain of bi-stable elements – where the relaxed free energy is analytically derived.To assess the limit behavior of the analyzed lattices, we elucidate the connection between energy release and topology at the microscale. This insight aids in identifying lattice configurations yielding high extrinsic energy dissipation density. We introduce the concept of dissipation efficiency and quantify it across all examined lattices under different loading conditions. Transverse loads prevail in the studied configurations and exhibit a detrimental effect by diminishing extrinsic energy dissipation during metamaterial phase transitions. To facilitate a comprehensive numerical assessment of diverse lattice configurations, we employ a surrogate model of the bistable element. This approach enables an efficient evaluation of sampling volumes constituted by numerous unit cells.

Wheat gluten structure and (non–)covalent network formation during deep-fat frying

The aim of this work was to investigate wheat gluten protein network structure throughout the deep-frying process and evaluate its contribution to frying-induced micro- and macrostructure development. Gluten polymerization, gluten-water interactions, and molecular mobility were assessed as a function of the deep-frying time (0 – 180 s) for gluten-water model systems of differing hydration levels (40 – 60 % moisture content). Results showed that gluten protein extractability decreased considerably upon deep frying (5 s) mainly due to glutenin polymerization by disulfide covalent cross-linking. Stronger gliadin and glutenin protein–protein interactions were attributed to the formation of covalent linkages and evaporation of water interacting with protein chains. Longer deep-frying (> 60 s) resulted in progressively lower protein extractabilities, mainly due to the loss in gliadin protein extractability, which was associated with gliadin co-polymerization with glutenin by thiol-disulfide exchange reactions. The mobility of gluten polymers was substantially reduced during deep-frying (based on the lower T2 relaxation time of the proton fraction representing the non-exchanging protons of gluten) and gluten proteins gradually transitioned from the rubbery to the glassy state (based on the increased area of said protons). The sample volume during deep-frying was strongly correlated to the reduced protein extractability (r = –0.792, p < 0.001) and T2 relaxation time of non-exchanging protons of gluten proteins (r = –0.866, p < 0.001) thus demonstrating that the extent of gluten structural expansion as a result of deep-frying is dictated both by the polymerization of proteins and the reduction in their molecular mobility.

Melamine sponges incorporated azo-linked porous organic polymer as adsorbent for extraction and determination of six B vitamins using pipette tip micro solid-phase extraction

A novel azo-linked porous organic polymer (AL-POP) was synthesized from caffeic acid and benzidine via an azo-coupling reaction and characterized by FTIR, SEM-EDS, BET, TGA, XRD and zeta potential analysis. AL-POPs were incorporated into melamine sponges and used for pipette tip micro solid-phase extraction (PT-MSPE) of six types of B vitamins (including thiamine, riboflavin, nicotinamide, pyridoxine, folic acid, and cyanocobalamin). After extraction, the samples were analyzed using high performance liquid chromatography-diode array detection (HPLC-DAD) system. The effect of AL-POP composition on the extraction efficiency (EE) of vitamins was investigated and benzidine to caffeic acid mol ratio of 1.5, 3.35 mmol of NaNO2, and reaction time of 8 h were selected as optimum conditions. The efficiency of the extraction process was improved by optimizing various parameters such as the amount of sorbent, pH and ionic strength of the sample, sample volume, number of sorption and desorption cycles, type of wash solvent, and type and volume of eluent solvent. Linearity (R2≥0.9987), Limit of detection (LOD) (11.88–18.97 ng/mL), limit of quantification (LOQ) (39.62–63.23 ng/mL), and enrichment factor (EF) (1.27–4.31) were obtained using calibration curves plotted under optimum conditions. Recovery values of these six B vitamins in the spiked multivitamin syrup samples varied from 80.01% to 108.35%, with a relative standard deviation (RSD) below 5.44%. Eventually, the optimized method was successfully used to extract and quantify the B vitamins in multivitamin syrup and non-alcoholic beer.

Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry.

Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.

Persistence and risk factors of occult hepatitis B virus infections among antiretroviral therapy-naïve people living with HIV in Botswana.

This study aimed to determine the kinetics of occult hepatitis B virus infections (OBI) among people with HIV (PWH). The study used archived plasma samples from longitudinal HIV natural history studies. We identified new OBI cases and assessed risk factors for OBI using Cox proportional hazards regression analysis. At baseline, 8 of 382 [(2.1%) (95% CI: 1.06-4.1)] samples tested positive for hepatitis B surface antigen (HBsAg+). Of the 374 HBsAg-negative samples, 76 had sufficient sample volume for HBV DNA screening. OBI positivity (OBI+) at baseline was reported in 11 of 76 [14.7 95% CI (8.3-24.1)] HBsAg-negative (HBsAg-) participants. Baseline HBsAg-negative samples with sufficient follow-up samples (n = 90) were used for analysis of newly identified OBI cases. Participants contributed 129.74 person-years to the study and were followed for a median of 1.02 years (IQR: 1.00-2.00). Cumulatively, there were 34 newly identified OBI cases from the 90 participants, at the rate of 26.2/100 person-years (95% CI: 18.7-36.7). Newly identified OBI cases were more common among men than women (61.1% vs. 31.9%) and among participants with CD4+ T-cell counts ≤450 cells/mL (p-value = 0.02). Most of the newly identified OBI cases [55.9% (19/34)] were possible reactivations as they were previously HBV core antibody positive. There was a high rate of newly identified OBI among young PWH in Botswana, especially in men and in participants with lower CD4+ T-cell counts. OBI screening in PWH should be considered because of the risk of transmission, possible reactivation, and risk factors for the development of chronic liver disease, including hepatocellular carcinoma.

The Effects of Irradiation on Structure and Leaching of Pure and Doped Thin-Film Ceria SIMFUEL Models Prepared via Polymer-Templated Deposition

When studying hazardous materials such as spent nuclear fuel (SNF), the minimisation of sample volumes is essential, together with the use of chemically-similar surrogates where possible. For example, the bulk behaviour of urania (UO2) can be mimicked by appropriately-engineered thin films of sufficient thickness, and inactive materials such as ceria (CeO2) can be used to study the effects within radioactive systems used to fuel nuclear fission. However, thin film properties are sensitive to the preparative method, many of which require the use of highly toxic precursors and specialised apparatus (e.g., chemical vapour deposition). To address this, we present the development of a flexible, tuneable, scalable method for the preparation of thin-film CeO2 SIMFUEL models with a thickness of ≈5 μm. The effects of γ irradiation (up to 100 kGy) and dopants including trivalent lanthanides (Ln3+) and simulant ε-particles on the structure and long-term leaching of these systems under SNF storage conditions were explored, alongside the context of this within further work. It was found that the sensitivity of CeO2 films to reduction upon irradiation, particularly in the presence of simulant ε-particles, resulted in increased leaching of Ce (as CeIII), while trivalent lanthanides (Nd3+ and Eu3+) had a minimal effect on Ce leaching.

Bioinspired integrated triboelectric electronic tongue

An electronic tongue (E-tongue) comprises a series of sensors that simulate human perception of taste and embedded artificial intelligence (AI) for data analysis and recognition. Traditional E-tongues based on electrochemical methods suffer from a bulky size and require larger sample volumes and extra power sources, limiting their applications in in vivo medical diagnosis and analytical chemistry. Inspired by the mechanics of the human tongue, triboelectric components have been incorporated into E-tongue platforms to overcome these limitations. In this study, an integrated multichannel triboelectric bioinspired E-tongue (TBIET) device was developed on a single glass slide chip to improve the device’s taste classification accuracy by utilizing numerous sensory signals. The detection capability of the TBIET was further validated using various test samples, including representative human body, environmental, and beverage samples. The TBIET achieved a remarkably high classification accuracy. For instance, chemical solutions showed 100% identification accuracy, environmental samples reached 98.3% accuracy, and four typical teas demonstrated 97.0% accuracy. Additionally, the classification accuracy of NaCl solutions with five different concentrations reached 96.9%. The innovative TBIET exhibits a remarkable capacity to detect and analyze droplets with ultrahigh sensitivity to their electrical properties. Moreover, it offers a high degree of reliability in accurately detecting and analyzing various liquid samples within a short timeframe. The development of a self-powered portable triboelectric E-tongue prototype is a notable advancement in the field and is one that can greatly enhance the feasibility of rapid on-site detection of liquid samples in various settings.

Green Surfactant Assisted-Solidified Floating Organic Drop Micro-Extraction (SA-SFODME) for the Preconcentration of Trace Lead with Determination by Flame Atomic Absorption Spectrometry (FAAS)

Determination of trace lead from environmental samples was carried out by solidified floating organic drop microextraction for preconcentration before analysis by flame atomic absorption spectrometry. The determination of lead from environmental samples, even at trace levels, was possible with an ordinary flame atomic absorption spectrometer (FAAS). The lead formed a hydrophobic complex with the anionic surfactant sodium dodecyl benzene sulfonate (SDBS), and this hydrophobic complex was extracted into the 1-dodecanol drop. Parameters affecting analytical performance have been studied. The optimum pH value was 3.5. The optimum sample volume, SDBS concentration, and extraction solvent volume were 75 mL, 50 mM in dodecanol, and 75 µL, respectively. The optimum extraction time was determined as 30 min, the optimum extraction temperature was 45 °C, the optimum mixing speed was 650 rpm and the ideal extraction phase volume was 0.50 mL. Methanol has been shown to be effective when used as a diluent. Using the optimum conditions, the enhancement factor was 106, and the limit of detection (3s) and precision were 3.3 ng/mL and 2.3% (n = 9,15 ng/mL), respectively. The limit of quantification (LOQ) (10s) was 10 ng/mL and the linear working range was 15-100 ng/mL. The accuracy was evaluated by certified reference material analysis. The optimized method was applied to the determination of Pb(II) from environmental water samples. This method follows the principles of green analytical chemistry.

Innovative sensor design for reliable detection of formaldehyde adulteration in milk

This research presents a straightforward and cost-effective sensor design for the detection of harmful chemical adulterants in raw milk, with a focus on formaldehyde, a common preservative. The proposed sensor design involves a minimal sample volume of 4 ml and utilizes a low-cost assembly with two nickel electrodes within a plastic cuvette. Electrochemical Impedance Spectroscopy (EIS) was conducted with an LCR meter to record three key electrical parameters: impedance (Z), phase angle (θ), and parallel plate capacitance (Cp). Testing was conducted in a controlled laboratory environment at temperatures between 25 to 27 °C for both unadulterated and adulterated milk samples. The results reveal that Z is the most sensitive parameter, capable of detecting formaldehyde adulteration as low as 0.5%. Conversely, θ and Cp effectively detected adulteration levels exceeding 3%. A noteworthy finding is a consistent and proportional increase in Z ranging from 2.2% to 26.4% as the formaldehyde concentration increases from 0.5% to 10% across a wide frequency range from 10 kHz to 200 kHz. This method offers a dependable and efficient approach to quality control, ensuring the safety and integrity of milk products.

The use of deep eutectic solvent-liquid phase microextraction as green analytical sample treatment for the analysis of drugs in urine

In this paper, a natural deep eutectic solvent (NADES)-based liquid phase microextraction (LPME) of 20 pharmaceuticals from urine, employing liquid chromatography tandem mass spectrometry (LC-MS/MS) for precise quantification, has been developed. The chromatographic gradient was accurately evaluated to ensure the effective separation of tramadol, an opioid receptor agonist, and o-desmethylvenlafaxine, one active metabolite of the antidepressant venlafaxine, both compounds sharing identical molecular mass for the precursor ion (Q1: 264.2 m/z) and fragmentation patterns (Quantifier ion: 58.2 m/z; qualifier ion: 246.0 m/z). NADES consisted of menthol-octanoic acid in a molar ratio of 1:2. Using the appropriate extraction conditions, the developed methodology provided appropriate LOQ values, ranging from 15 to 208 ng L–1, with reasonable RSD values (below 11 %), recoveries ranging from 64 to 120 % and preconcentration factors up to 66.6 folds. Application of the developed method to the analysis of urine samples served to highlight its usefulness. An AGREEprep score of 0.64 was obtained despite the demand for substantial sample volumes and the use of LC-MS/MS for analyte determination.