Applications In Analytical Chemistry Research Articles

Effect of fluid properties on intensification of heat transfer process in oil-water droplet flow in a T-shaped microchannel

Droplet-based microfluidics refers to the production and utilization of micrometer-sized droplets. This technology has found widespread applications in drug delivery, biotechnology, disease prevention, chemical analysis, cell research, and functional material synthesis. Cooling of high heat flux electronic systems and hot spots is another application of the droplet flow which is focused by the current work. In this paper, formation and hydrothermal performance of oil droplets in water flow in a T-junction microchannel is studied by a 3D numerical simulation. Effects of different parameters such as surface tension, wettability and heat flux on the droplet size, heat transfer rate and pressure drop are investigated. It is observed that the shear between the discrete and continuous phases results in recirculating zones in both phases which contribute to improved mixing and heat transfer rates. Liquid film thickness adjacent to the heated surface and the droplet velocity are two other factors that positively affect the heat transfer. Decreasing the surface tension is shown to enhance the heat transfer rate. Moreover, an optimum value is found for the contact angle as 135° at which a 23 % heat transfer enhancement is achieved. Results also indicate that droplet size decreases with increase of contact angle while it slightly increases with increase of the surface tension and negligibly varies with the applied heat flux.

Inductance coil high-frequency contactless chemical sensor: Systematic study of its cationic sensitivity

Contactless sensors for chemical analysis, based on inexpensive and widely available electronic components, are a promising alternative to existing routine laboratory methods. We have proposed a novel type of a contactless sensor, composed of three simple components: an alternate current generator, an inductance coil, and a receiver. The sample, placed into the coil as a core of the inductor, modifies the current passing through the coil. Previously, we have demonstrated that this contactless sensor may have numerous applications for chemical analysis. In this work, we have explored the performance of the coil-based measuring platform further and performed the first systematic study of the response of inductance coil sensor to metal cations in aqueous solutions. Sixteen metal cations with different charge and radii were studied. Linear response ranges, sensitivity values and the comparison between univariate and multivariate regression modeling are presented. The largest linear response range was observed for transition metal cations Ni2+, Cu2+, Pb2+ and Nd3+ (10-3 – 10-1 M), the narrowest – for Li+ and Gd3+ (10-2 – 3.2x10-1 M) with R2 values larger than 0.94. The dependence of the response on the radius and the charge of the cation are discussed. The analytical characteristics of the device show its potential in contactless and low-cost chemical analysis and set the ground for the future research.

Synthesis of long straight‐chain alkane substituted ferrocene with ultra‐robust oil solubility as multifunctional organometallic additive

Tailoring of organometallics structure toward desirable properties continues to be both fascinating and challenging in the field of materials science. Herein, a novel ferrocene derivative with long straight‐chain alkane mono‐substituent is synthesized and used as multifunctional organometallic additive in the base oil. This ferrocene‐based organometallic compound (MFc) is synthesized via the Friedel‐Crafts acylation of ferrocene with myristyl chloride, followed by reduction with sodium borohydride. The chemical structure, crystallizability, surface morphology, and the thermal properties of the as‐synthesized compound are systematically characterized. As the iron‐containing standard substance, the MFc was preferable dissolve in lubricating oil with the iron element content as high as 2*105 ppm. Resultantly, the MFc/oil solutions exhibited excellent stability even after high‐speed centrifugal treatment, long‐term storage up to 3 months, and ultra‐low temperature treatment at −40°C for 24 h. Moreover, the MFc as a functional lubricant additive could reduce the average wear scar diameter, wear volume, and coefficient of friction with 40%, 73%, and 18%, respectively, as compared to the corresponding pure base oil. This synthetic strategy provides a novel perspective for the design of functional organometallics, and the as‐synthesized novel ferrocene derivative may find a wide range of advanced potential applications in analytical chemistry, tribology, and interfacial science.

Nano-Engineered HfO2-Au photonic sensor for ultra-sensitive refractive index detection

In this study, we introduce a novel hafnium dioxide (HfO2) and thin gold layer based photonic crystal fiber (HfAu-PCF) sensor for refractive index measurement and optimize in the spectrum of 1.3 µm to 1.6 µm. The proposed sensor incorporates a D-shaped geometry for enhanced light-matter interaction, and the core of the fiber is surrounded by periodic air holes to facilitate efficient coupling of the guided mode with surface plasmons. The proposed HfAu-PCF sensor is geometrically optimized using finite element method (FEM) by fine-tuning air hole diameter, core size, layer thickness dimensions of the fiber to achieve performance stability. Leveraging the unique optical properties of HfO2 and Au, the sensor demonstrates superior performance metrics, achieving confinement loss (<10−6 dB/m), propagation constant (β) ∼ 6 × 106, V-Parameter < 2.3, a peak relative sensitivity of 99.05 % across the tested wavelength of 1.3 µm to 1.6 µm. Our findings reveal that choosing suitable parameters could lead to further enhancements in sensitivity, making the sensor for applications in bio-sensing, environmental monitoring, and chemical analysis, etc.

On Ve-Degree and Ev-Degree Based Topological Invariants of Chemical Structures

In the realm of graph theory, recent developments have introduced novel concepts, notably the ν ε -degree and ε ν -degree, offering expedited computations compared to traditional degree-based topological indices (TIs). These TIs serve as indispensable molecular descriptors for assessing chemical compound characteristics. This manuscript aims to meticulously compute a spectrum of TIs for silicon carbide S i C 4 - I [ r , s ] , with a specific focus on the ε ν -degree Zagreb index, the ν ε -degree Geometric-Arithmetic index, the ε ν -degree Randić index, the ν ε -degree Atom-bond connectivity index, the ν ε -degree Harmonic index, and the ν ε -degree Sum connectivity index. This study contributes to the ongoing advancement of graph theory applications in chemical compound analysis, elucidating the nuanced structural properties inherent in silicon carbide molecules.

Monosaccharide composition of lignocellulosic matrix—Optimization of microwave-assisted acid hydrolysis condition

Compositional analysis of polysaccharides is crucial in many applications of analytical chemistry, and typically involves hydrolysis as initial step, to break glycosidic bonds and release individual monosaccharide units. We developed a new method for the microwave-assisted acid hydrolysis of polysaccharides, here applied for determining the composition of the polysaccharide fraction within the lignocellulosic matrix of Pinus sylvestris. The optimisation of reaction conditions was carried out using a GC–MS method after a double-step sugar derivatization process.Under the optimized conditions, specifically, employing 2 M TFA, 40 min, and 120 °C, a high depolymerisation yield was achieved with minimal degradation. Furthermore, the amount of polysaccharides detected in pine wood aligns with the results in existing literature, substantiating the determined chemical composition.The synergy of microwave-assisted acid hydrolysis and full factorial design not only facilitated the determination of the optimal hydrolysis conditions but also enabled the assessment of the parameters influencing the polysaccharide hydrolysis process and their relationships. This approach made it feasible to achieve maximum hydrolysis efficiency while minimizing analyte degradation, employing a method that reduces environmental impact through the use of microwave energy. This strategy effectively reduced the required reaction temperature, time, and reagent quantities.

Introducing UV–visible spectroscopy at high school level following the historical evolution of spectroscopic instruments: a proposal for chemistry teachers

Spectroscopy is a scientific topic at the interface between Chemistry and Physics, which is taught at high school level in relation with its fundamental applications in Analytical Chemistry. In the first part of the paper, the topic of spectroscopy is analyzed having in mind the well-known Johnstone’s triangle of chemistry education, putting in evidence the way spectroscopy is usually taught at the three levels of chemical knowledge: macroscopic/phenomenological, sub-microscopic/molecular and symbolic ones. Among these three levels, following Johnstone’s recommendations the macroscopic one is the most useful for high school students who learn spectroscopy for the first time. Starting from these premises, in the second part of the paper, we propose a didactic sequence which is inspired by the historical evolution of spectroscopic instruments from the first spectroscopes invented by Gustav Kirchhoff and Robert Bunsen in 1860 to the UV–vis spectrophotometers which became common since the 1960s. The idea behind our research is to analyze the conceptual advancements through the history of spectroscopy and to identify the key episodes/experiments and spectroscopic instruments. For each of them, a didactic activity, typically an experiment, is then proposed underlining the relevant aspects from the chemistry education point of view. The present paper is the occasion to reflect on the potentialities of an historical approach combined with a laboratorial one, and to discuss the role of historical instruments and related technological improvements to teach spectroscopy.

Numerical Simulations of Combined Dielectrophoresis and Alternating Current Electrothermal Flow for High-Efficient Separation of (Bio)Microparticles.

High-efficient separation of (bio)microparticles has important applications in chemical analysis, environmental monitoring, drug screening, and disease diagnosis and treatment. As a label-free and high-precision separation scheme, dielectrophoresis (DEP) has become a research hotspot in microparticle separation, especially for biological cells. When processing cells with DEP, relatively high electric conductivities of suspending media are sometimes required to maintain the biological activities of the biosample, which results in high temperature rises within the system caused by Joule heating. The induced temperature gradient generates a localized alternating current electrothermal (ACET) flow disturbance, which seriously impacts the DEP manipulation of cells. Based on this, we propose a novel design of the (bio)microparticle separator by combining DEP with ACET flow to intensify the separation process. A coupling model that incorporates electric, fluid flow, and temperature fields as well as particle tracking is established to predict (bio)microparticle trajectories within the separator. Numerical simulations reveal that both ACET flow and DEP motion act in the same plane but in different directions to achieve high-precision separation between particles. This work provides new design ideas for solving the very tricky Joule heating interference in the DEP separation process, which paves the way for further improving the throughput of the DEP-based (bio)microparticle separation system.

Direct observation and elemental analysis of material nanoparticles in solution using scanning electron-assisted dielectric microscopy and EDS

High-resolution observation and elemental analysis of various particles in solution are important in the fields of materials, analytical chemistry, and industrial applications. Analysis of slurries of raw materials is essential for the development of highly functional materials. Recently, we have developed an SEM-based scanning electron assisted dielectric microscope (SE-ADM), which can directly observe biological samples and organic materials in aqueous solutions. Here, we have developed an SE-ADM system with the addition of energy-dispersive x-ray spectrometry that enables direct observation and elemental analysis of nanoparticles in solution. Using this system, we were able to directly observe and conduct elemental analysis of ceramic slurries and to clarify the dispersion state of alumina particles in solution, the distribution of binder, and the bonding state of silica and magnesium particles. Furthermore, our system can be applied to diverse liquid samples across a broad range of scientific and industrial fields, for example, nanotubes, organic specimens, batteries, and catalytic materials.

Near-IR Photoinduced Electrochemiluminescence Imaging with Structured Silicon Photoanodes.

Infrared (IR) imaging devices that convert IR irradiation (invisible to the human eye) to a visible signal are based on solid-state components. Here, we introduce an alternative concept based on light-addressable electrochemistry (i.e., electrochemistry spatially confined under the action of a light stimulus) that involves the use of a liquid electrolyte. In this method, the projection of a near-IR image (λexc = 850 or 840 nm) onto a photoactive Si-based photoanode, immersed into a liquid phase, triggers locally the photoinduced electrochemiluminescence (PECL) of the efficient [Ru(bpy)3]2+-TPrA system. This leads to the local conversion of near-IR light to visible (λPECL = 632 nm) light. We demonstrate that compared to planar Si photoanodes, the use of a micropillar Si array leads to a large enhancement of local light generation and considerably improves the resolution of the PECL image by preventing photogenerated minority carriers from diffusing laterally. These results are important for the design of original light conversion devices and can lead to important applications in photothermal imaging and analytical chemistry.

An all-inorganic lead-free metal halide double perovskite for the highly selective detection of norfloxacin in aqueous solution.

Lead-based perovskites are highly susceptible to environmental influences, and their application in analytical chemistry, especially in aqueous solution, has been reported rarely. All-inorganic lead-free metal halide perovskites have been considered as a substitute for lead-based perovskites. Herein, a Cs2RbTbCl6 perovskite microcrystal (PMCs), which emits strong yellow-green fluorescence with a maximum emission wavelength at 547nm, was for the first time synthesized and characterized. The Cs2RbTbCl6 PMCs could be well dispersed in N,N-dimethylacetamide (DMF), and its fluorescence could be significantly enhanced by the addition of norfloxacin (NOR) in the aqueous solution. We found that the Cs2RbTbCl6 PMCs can be used as fluorescent probes (excitation, 365nm; emission, 547nm) to selectively detect NOR in a concentration range from 10.0 to 200.0μM with the limit of detection (LOD) being 0.04μM. The Cs2RbTbCl6 PMCs could also be adsorbed on filter paper to fabricate as a fluorescent test paper for visual detection of NOR under 365-nm ultraviolet (UV) lamp irradiation. The proposed method has the potential to establish a new analytical method to visualize the detection of NOR in aqueous environments and also promotes the application of all-inorganic lead-free perovskites for analytical detection in aqueous environments.

Visualization-enhanced under-oil open microfluidic system for in situ characterization of multi-phase chemical reactions

Under-oil open microfluidic system, utilizing liquid-liquid boundaries for confinements, offers inherent advantages including clogging-free flow channels, flexible access to samples, and adjustable gas permeation, making it well-suited for studying multi-phase chemical reactions that are challenging for closed microfluidics. However, reports on the novel system have primarily focused on device fabrication and functionality demonstrations within biology, leaving their application in broader chemical analysis underexplored. Here, we present a visualization-enhanced under-oil open microfluidic system for in situ characterization of multi-phase chemical reactions with Raman spectroscopy. The enhanced system utilizes a semi-transparent silicon (Si) nanolayer over the substrate to enhance visualization in both inverted and upright microscope setups while reducing Raman noise from the substrate. We validated the system’s chemical stability and capability to monitor gas evolution and gas-liquid reactions in situ. The enhanced under-oil open microfluidic system, integrating Raman spectroscopy, offers a robust open-microfluidic platform for label-free molecular sensing and real-time chemical/biochemical process monitoring in multi-phase systems.

Reduced reverse degree-based topological indices of graphyne and graphdiyne nanoribbons with applications in chemical analysis

Graphyne and Graphdiyne Nanoribbons reveal significant prospective with diverse applications. In electronics, they propose unique electronic properties for high-performance nanoscale devices, while in catalysis, their excellent surface area and reactivity sort them valuable catalyst supports for numerous chemical reactions, contributing to progresses in sustainable energy and environmental remediation. The topological indices (TIs) are numerical invariants that provide important information about the molecular topology of a given molecular graph. These indices are essential in QSAR/QSPR analysis and play a significant role in predicting various physico-chemical characteristics. In this article, we present a formula for computing reduced reverse (RR) degree-based topological indices for graphyne and graphdiyne nanoribbons, including the RR Zagreb indices, RR hyper-Zagreb indices, RR forgotten index, RR atom bond connectivity index, and RR Geometric-arithmetic index. We also execute a graph-theoretical analysis and comparison to demonstrate the critical significance and validate the acquired results. Our findings provide insights into the structural and chemical properties of these nanoribbons and contribute to the development of new materials for various applications.

Unravelling the Potential of Magnetic Nanoparticles: A Comprehensive Review of Design and Applications in Analytical Chemistry

Unravelling the Potential of Magnetic Nanoparticles: A Comprehensive Review of Design and Applications in Analytical Chemistry

Unveiling the ion sensing capabailities of 'click' derived chalcone-tailored 1,2,3-triazolic isomers for Pb(ii) and Cu(ii) ions: DFT analysis.

In this study, two novel chalcone-derived 1,2,3-triazole-appended positional isomers (probe 6 and probe 9) were synthesized via the 'CuAAC' (Cu(i) - catalysed alkyne azide cycloaddition) methodology for the purpose of metal ion detection. The synthesized probes underwent characterization utilizing standard spectroscopic methodologies including FTIR, NMR (1H and 13C), and mass spectrometry. Subsequently, the sensing capabilities of these probes were explored using UV-Vis and fluorescence spectroscopy, wherein their selective recognition potential was established for Pb(ii) and Cu(ii), both of which can pose serious health hazards when prevalent in the environment above permissible limits. Both the probes exhibited fairly low limits of detection (LoD), determined as 5.69 μM and 6.55 μM in the case of probe 6 for Pb(ii) and Cu(ii) respectively; whereas the probe 9 exhibited an LoD of 5.06 μM and 7.52 μM for Pb(ii) and Cu(ii), respectively. The job's plot for the probe demonstrates the formation of a 1 : 1 complex between the metal and ligand. Furthermore, the interaction of the free probes with the metal ions in the metal-ligand complex was elucidated through 1H NMR analysis and validated theoretically using Density Functional Theory (DFT) simulations with the B3LYP/6-311G++(d,p) and B3LYP/LANL2DZ basis sets for geometry optimization of the probes and their corresponding metal complexes. These findings offer a reliable approach to Cu(ii) and Pb(ii) ion detection and can be further used for the potential applications in environmental monitoring and analytical chemistry.

Investigating the Spectral Response of Fiber Bragg Grating for Strain Sensor Applications

Abstract: The optical fibre sensor (OFS) has become quite well-known and prominent in the sensor technology industry. It is often used to react to outputs from other systems, like those in industrial, monitoring, and chemical analysis applications, and to detect changes in the environment. A Bragg reflector starts to grow and transmit all other wavelengths while a short section of optical fibre with a specific wavelength is reflected with light in a device called a Fibre Bragg Grating. The current study focuses on the evolving characteristics and behaviours of strain and temperature sensors operating on Fibre Bragg Gratings (FBG) through software modelling. This work's primary goal is to investigate the characteristics and behaviour of strain sensor that are used with fibre bragg gratings. A strain sensor can be used to determine the strain in an object whose resistance changes when force is applied.

Investigating The Spectral Response of Fiber Bragg Grating (FBG) for Temperature Sensor Applications

Abstract: In the field of sensor technology, the optical fibre sensor (OFS) has gained a lot of notoriety and prominence. It is frequently utilised to detect changes in the environment and react to outputs from other systems, such as those used in chemical analysis, industrial, and monitoring applications. A Fibre Bragg Grating (FBG) is a type of device in which a brief segment of optical fibre with a particular wavelength is reflected with light, while the Bragg reflector begins to grow and transmit all other wavelengths. The developing features and behaviours of temperature and strain sensors working on Fibre Bragg Grating using computer modelling are the focus of the current project. The main objective of this work is to examine the behaviour and properties of temperature sensors operating on Fibre Bragg Grating. The temperature sensor is utilised to measure and identify any temperature anomalies operating on the Fibre Bragg Grating that may cause mishaps or fires. This will reveal how temperature sensors may be demonstrated using Fibre Bragg Grating.

The role played by sensors consisting of smartphone and black box in analytical chemistry: Increase the achievability

In recent years, smartphone-based rapid detection methods have emerged and gained popularity among a wide range of researchers. Smartphone are favoured due to their integration of diverse functions such as photography, positioning, internet connectivity, and high-performance operating systems. The presence of a black box ensures the stable and improved conversion and transmission of optical and electrical signals, which is crucial for detection tasks carried out in environments where the ideal laboratory environment may not be feasible or guaranteed. The objective of this review is to elaborate on the application of chemical analysis based on the combined effect of smartphone and black box. Initially, we analyzed the design factors and fundamental functions of the black box. Subsequently, we provided a detailed description of the process involving the black box's integration with cuvettes, paper bases, and microtiter plates (MTPs) for presenting and transmitting light signals, which are then processed and calculated by the smartphone. We also presented the conversion and application of light signals generated by special reaction vessels and the generation of electrical signals at electrodes through the black box. Finally, we discussed the challenges and prospects associated with the combination of smartphone and black box assay models.

Two all-biomass cellulose/amino acid spherical nanoadsorbents based on a tri-aldehyde spherical nanocellulose II amino acid premodification platform for the efficient removal of Cr(VI) and Cu(II)

Adsorbents consisting of spherical nanoparticles exhibit superior adsorption performance and hence, have immense potential for various applications. In this study, a tri-aldehyde spherical nanoadsorbent premodification platform (CTNAP), which can be grafted with various amino acids, was synthesized from corn stalk. Subsequently, two all-biomass spherical nanoadsorbents, namely, cellulose/l-lysine (CTNAP-Lys) and cellulose/L-cysteine (CTNAP-Cys), were prepared. The morphologies as well as chemical and crystal structures of the two adsorbents were studied in detail. Notably, the synthesized adsorbents exhibited two important characteristics, namely, a spherical nanoparticle morphology and cellulose II crystal structure, which significantly enhanced their adsorption performance. The mechanism of the adsorption of Cr(VI) onto CTNAP-Lys and that of Cu(II) onto CTNAP-Cys were studied in detail, and the adsorption capacities were determined to be as high as 361.69 (Cr(VI)) and 252.38 mg/g (Cu(II)). Using the proposed strategy, it should be possible to prepare other all-biomass cellulose/amino acid spherical nanomaterials with high functional group density for adsorption, medical, catalytic, analytical chemistry, corrosion, and photochromic applications.

PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction

Accurate vapor pressure prediction is crucial for various applications, but obtaining precise measurements for certain compounds is resource- and labor-intensive. This challenge is amplified when a temperature-dependent relationship is required. To address this, we introduce PUFFIN (Path-Unifying Feed-Forward Interfaced Network), a machine learning approach that combines transfer learning with a specialized inductive bias node (inspired by the Antoine equation) to enhance vapor pressure prediction. PUFFIN outperforms alternative strategies that lack inductive bias or use generic compound descriptors by leveraging inductive bias and transfer learning using graph embeddings. The framework's incorporation of domain-specific knowledge overcomes data limitations and shows promise for broader chemical compound analysis applications, including the prediction of other physicochemical properties. An important aspect of our proposed approach is its partial interpretability, as the inductive Antoine node yields network-derived Antoine equation coefficients.