Quantitative Analytical Chemistry Research Articles

What is a mathematician doing…in a chemistry class?

AbstractThe way of thinking of mathematicians and chemists in their respective disciplines seems to have very different levels of abstractions. While the firsts are involved in the most abstract of all sciences, the seconds are engaged in a practical, mainly experimental discipline. Therefore, it is surprising that many luminaries of the mathematics universe have studied chemistry as their main subject. Others have started studying chemistry before swapping to mathematics or have declared some admiration and even love for this discipline. Here I reveal some of these mathematicians who were involved in chemistry from a biographical perspective. Then, I analyze what these remarkable mathematicians and statisticians could have learned while studying chemical subjects. I found analogies between code-breaking and molecular structure elucidation, inspiration for statistics in quantitative analytical chemistry, and on the role of topology in the study of some organic molecules. I also analyze some parallelisms between the way of thinking of organic chemists and mathematicians in terms of the use of backward analysis, search for patterns, and use of pictures in their respective researches.

Effectiveness of Formative Assessment As Learning Tool in Quantitative Analytical Chemistry Remote Learning

The effectiveness of learning tools in remote learning mode during the COVID-19 pandemic was investigated in The Quantitative Analytical Chemistry Course in University of the Philippines-Diliman. The effectiveness of formative assessments with feedback was determined by comparing students’ performance in the pretest and posttest assessments. Dependent sample t-test analysis of over-all performance of student showed that as a cohort, there was a statistically significant improvement in the posttest ( M = 8.44, SD = 1.63) performance compared to pretest (M = 5.46, SD = 2.19), t(49) = 9.926, p < 0.001). The dependent t-test analysis indicate that there was a statistically significant improvement in nine topics while there was no statistically significant improvement in two topics. Results of the study indicate that in three of the topics with Problem Solving/Analyze/Evaluate type of questions, less than 55% of the students were able to fully answer the problem in the posttest. The findings indicate that for multistep problem solving and evaluate type of questions, additional learning strategies are needed for majority of students to be fully competent on the topics. This study also aimed to assess effectiveness of commercially available online learning platforms as learning tool. The data indicate that only 50% (28 out of 54 students) of the students accessed at least once the online learning platform during the duration of the course.

Exploration and Practice of Teaching Reforms in “Quantitative Analytical Chemistry” under the Perspective of New Agricultural Science

Exploration and Practice of Teaching Reforms in “Quantitative Analytical Chemistry” under the Perspective of New Agricultural Science

Single-particle detection of cholesterol based on the host-guest recognition induced plasmon resonance energy transfer

Plasmon resonance energy transfer (PRET) occurs between the plasmonic nanoparticles (NPs) and organic dyes forming donor-acceptor pairs, which has great potential in quantitative analytical chemistry because of its excellent sensitivity under dark-field microscopy (DFM). Herein, we introduce supramolecular β-cyclodextrin (β-CD) to design a host-guest recognition plasmonic nano-structure modified gold nanoparticles (GNPs), while GNPs and rhodamine molecule (RB) act as the donor and acceptor, respectively. In the presence of the target cholesterol, due to the stronger binding of cholesterol with β-CD, RB molecules are released, inducing the inhibition of PRET, as well as the increase of the scattering intensity of GNPs. The proposed strategy achieves a linear range from 0.02 µmol/L to 2.0 µmol/L for cholesterol detection, and reaches a limit of detection (LOD) of 6.7 nmol/L. This host-guest recognition strategy can easily integrate receptor-donor pair into one nanoparticle, which simplifies the construction of the PRET platform, and further provides an effective approach for PRET-based analytical applications. Afterwards, the proposed PRET strategy was successfully applied for the detection of cholesterol in serum samples with high sensitivity and specificity. The proposed method provides an effective clinically potential means for the detection of cholesterol and other disease-related biomarkers.

Stochastic Dynamic Electrospray Ionization Mass Spectrometric Quantitative Analysis of Metronidazole in Human Urine

The study reports quantification of metronidazole (MTZ) in clinical human urine employing our innovative stochastic dynamic equation D”SD =2.6388.10-17.(<I2>–<I2>). There are direct analysis without presence of internal standard, using ultra-high accuracy nano-electrospray ionization (ESI) mass spectrometry (MS), quantum chemistry and chemometrics, respectively. The linear calibration D”SD =f(conc.) equations are obtained for concentration range 2.5 to 25000 ng.(mL)-1 of spiked urine samples, examining analyte MS ions at m/z 171.0998, 172.0718, 172.04081, 213.1463, 181.0722 and 151.1114, respectively. There is achieved exact coefficient of linear correlation (|r|=1) between theory and experiment of ion at m/z 172.04081. The major challenge to quantify MTZ in urine sample is that it stabilizes cations [M+H]+ of two tautomers, which equilibrium varies drastically within the standard linear calibration dynamic range. The fragmentation patterns depend on analyte tautomers and it unambiguous assignment in multicomponent samples with complex sample matrix effect (SME) is unable to be made without mediation to an independent physico-chemical law. To solve the problem, herein, is used, again, above equation, which is designed a bridge between quantitative and multidimensional structural analytical chemistry, when is used complementary with Arrhenius’s quantum chemical diffusion parameter (DQC.) There is achieved |r|=0.98 of D”SD=f(DQC’) examining tautomeric molecular and fragment ions of MTZ.

Logarithmic Data Processing Can Be Used Justifiably in the Plotting of a Calibration Curve.

The article is a response to a recent opinion piece that log concentration values should not be applied in analytical chemistry. An essential aim in the development of analytical chemistry methods is to obtain more sensitive and accurate detection values. For the application of chemical analysis methods, the obtained experiment data need to fit with the mathematical functions in the first place. As influenced by different detection principles and analytical methods, data can be displayed in a coordinate system with two linear axes for linear function fitting, or the data can first be taken through a logarithmic transformation and then for function fitting. Using raw data or data after logarithmic transformation primarily depends on analytical principles, without special rules of data formats. For example, ultraviolet-visible spectrophotometric data are more suitable for direct linear fitting. However, enzyme-catalyzed reaction or electrochemical data in logarithmic form are more appropriate for function fitting. This transformation of data form will not affect the soundness of fit statistics; rather, it simplifies the complexity of function analysis and calculation, which are the essence of analytical chemistry. In this brief article, we provide justification and legitimacy of the application of logarithmic processing in various fields of quantitative analytical chemistry.

Capillary Electrophoresis as a Monitoring Tool for Flow Composition Determination

Flow analysis is the science of performing quantitative analytical chemistry in flowing streams. Because of its efficiency and speed of analysis, capillary electrophoresis (CE) is a prospective method for the monitoring of a flow composition withdrawn from various processes (e.g., occurring in bioreactors, fermentations, enzymatic assays, and microdialysis samples). However, interfacing CE to a various flow of interest requires further study. In this paper, several ingenious approaches on interfacing flow from various chemical or bioprocesses to a capillary electrophoresis instrument are reviewed. Most of these interfaces can be described as computer-controlled autosamplers. Even though most of the described interfaces waste too many samples, many interesting and important applications of the devices are reported. However, the lack of commercially available devices prevents the wide application of CE for flow analysis. On the contrary, this fact opens up a potential avenue for future research in the field of flow sampling by CE.

Teaching and Learning of Quantitative Analytical Chemistry Laboratory from the Perspective of Teaching Assistant

Teaching and Learning of Quantitative Analytical Chemistry Laboratory from the Perspective of Teaching Assistant

Why we should be interested in P values and hypothesis tests

The origins of chemometrics in quantitative analytical chemistry is contrasted to the emerging growth points of statistically based hypothesis testing and generation such as in applications to metabolomics and heritage science.

Biosorption of Cr (III) from Aqueous Solution Using Banana Peel Powder

O uso de cascas de banana moídas foi avaliado como biossorvente para a remoçãode resíduos de Cr (III) em eflentes aquosos. O eflente aquoso utilizado foi geradoem aulas experimentais de química analítica quantitativa no Instituto Federal do RioGrande do Sul (IFRS). Técnicas alternativas foram empregadas no presente trabalho,os ensaios combinaram duas metodologias para o tratamento deste resíduo. Oprimeiro explora a capacidade de cascas de banana como biossorvente na remoção deCr (III), enquanto o segundo emprega a complexação de Cr (III) usando EDTA, sobirradiação de microondas, para fis de quantifiação. A remoção máxima de 60% doconteúdo de Cr (III) foi alcançada em 40 minutos de tratamento, em escala de batelada.

Analyzing types of interaction in nuclear magnetic spectroscopy online discussion forums that affects student learning outcomes

Many research shows that interaction can increase concept understanding. Course interaction can be categorized in student-student interaction and student-lecturer interaction. Strong interaction can increasing students high order thinking skill. Learning design begins to pay attention to that interaction effect. Interaction can be done online and lead to cognitive understanding. This qualitative descriptive research aims to describe the cognitive process in an online discussion, specifically in analytical chemistry course. They learn about nuclear magnetic spectroscopy that most used in both qualitative and quantitative analytical chemistry. The subjects are seven groups consists of three chemistry students in their third year. They have three worksheets to discuss in three weeks about basic principal, instrument, spectrum, and experimental design in Nuclear Magnetic Resonance spectroscopy. Data sources are their online discussion transcript obtained from their elearning discussion forum. They also have pretest and posttest to analyze N-gain score. Their discussions are analyzed using coding categories to count the number of meaningful interaction. The trend of n-gain score and number of meaningful interaction are analyzed. Type of interaction that showed is ARA, ARC, ARI, DRA, DRI, and DRC. Results show that gain score correlates with number of meaningful interactions.

Automatic sequential fluid handling with multilayer microfluidic sample isolated pumping.

To sequentially handle fluids is of great significance in quantitative biology, analytical chemistry, and bioassays. However, the technological options are limited when building such microfluidic sequential processing systems, and one of the encountered challenges is the need for reliable, efficient, and mass-production available microfluidic pumping methods. Herein, we present a bubble-free and pumping-control unified liquid handling method that is compatible with large-scale manufacture, termed multilayer microfluidic sample isolated pumping (mμSIP). The core part of the mμSIP is the selective permeable membrane that isolates the fluidic layer from the pneumatic layer. The air diffusion from the fluidic channel network into the degassing pneumatic channel network leads to fluidic channel pressure variation, which further results in consistent bubble-free liquid pumping into the channels and the dead-end chambers. We characterize the mμSIP by comparing the fluidic actuation processes with different parameters and a flow rate range of 0.013 μl/s to 0.097 μl/s is observed in the experiments. As the proof of concept, we demonstrate an automatic sequential fluid handling system aiming at digital assays and immunoassays, which further proves the unified pumping-control and suggests that the mμSIP is suitable for functional microfluidic assays with minimal operations. We believe that the mμSIP technology and demonstrated automatic sequential fluid handling system would enrich the microfluidic toolbox and benefit further inventions.

Genetic Algorithm for Variable and Samples Selection in Multivariate Calibration Problems

One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful combinations of statistical methods to chemical data, both in analytical chemistry and in theoretical chemistry. Among used methods can cite Artificial Neural Networks (ANN), the Nonlinear Partial Least Squares (N-PLS), Principal Components Regression (PCR) and Multiple Linear Regression (MLR). In addition of multivariate calibration methods algorithms of samples selection are used. These algorithms choose a subset of samples to be used in training set covering adequately the space of the samples. In other hand, a large spectrum of a sample is typically measured by modern scanning instruments generating hundreds of variables. Search algorithms have been used to identify variables which contribute useful information about the dependent variable in the model. This paper proposes a Genetic Algorithm based on Double Chromosome (GADC) to do these tasks simultaneously, the sample and variable selection. The obtained results were compared with the well-known algorithms for samples and variable selection Kennard-Stone, Partial Least Square and Successive Projection Algorithm. We showed that the proposed algorithm can obtain better calibrations models in a case study involving the determination of content protein in wheat samples.

Solid-state determination of hop bitter acids in beer by UV–MALDI–Orbitrap mass spectrometry

Despite of the fact that the manufacturing of beer dated from many centuries, and nevertheless, of enormous analytical instrumental elaborations, developments and implementations for highly precise and accurate protocols for determination of foodstuffs, the quantitation of beer ingredients still represent significant challenge. It is caused by: (A) high complexity of the beer as foodstuffs matrix with significant proteins and maltooligosaccharide content as well as diversity of more than 57 low-molecular weight hop bitter acidic analytes and their oxidation products; (B) higher instability and variety of chemical oxidation processes typical for these ingredients; (C) easy isometrization and rearrangements, tautomerism and large number of different conformations of hop bitter acids; (D) structural similarity of the analytes; (E) photo-instability of the ingredients; and (F) still unavailable commercial standards for all hop acids, which difficult the analysis of major and minor components in crude hop extracts, during brewing process and storage of final food product. The diverse number of chemical and photochemical processes may be conducted at each these stages of beer manufacturing, which caused need of methodological elaborations and implementations of accurate analytical protocols for on-line analysis of beer components. For this reason the paper content encompasses quantitative solid-state analysis of hop bitter acids in different brands beer beverages employing UV–MALDI–Orbitrap MS method. Despite of its powerful instrumental capability, this mass spectrometric method has been scarce utilized in analysing of beer foodstuffs, limiting the scientific efforts and reports to mainly qualitative analysis and fingerprinting of proteins and maltooligosaccharides. In this respect the study provided novelty in the field of the quantitative analytical chemistry of low molecular weight analytes in beer demonstrating its capability for accurate determination of closely structural ingredients such as the large number of naturally occurring hop bitter acids.

Quantitative Mass Spectrometry Independence from Matrix Effects and Detector Saturation Achieved by Flow Injection Analysis with Real-Time Infinite Dilution

A high-throughput quantitative analysis method is presented to determine analyte concentrations at the infinite dilution limit, where the presence and effects of matrix become null, achieving mathematical independence from the detrimental phenomenon of matrix effects. Dilution is achieved online, reproducibly and in seconds by diffusion/mixing that occurs in flow injection analysis, while analyte concentration measurements are made by electrospray ionization tandem mass spectrometry. Because of matrix effects, the measured analyte concentration (Am) was inaccurate at high matrix concentrations, but accuracy consistently improved as matrix concentration was reduced by dilution. The method provides a practical solution around the decades-long matrix effects problem in quantitative analytical chemistry without separation of analytes from the matrix (e.g., chromatography) or use of corrective procedures, such as matrix-matched standards or isotopically labeled internal standards. Broad applications were demonstrated for part-per-billion quantitation of bioactive molecules (pesticides) in extracts of food, plant tissues, and body fluids by coupling the method to a high-throughput sample extraction/cleanup based on salting out with ammonium formate. The technique provides an assessment of matrix effects with remarkable comprehensiveness, simplicity, and speed. A limit of quantitation of 10 ng/g, a level appropriate for pesticide residue analysis and bioanalytical applications, was demonstrated. The method is also independent of detector saturation; this feature increased the applicable concentration range 20-100-fold above that of conventional techniques. In the abstract graphic, the measured analyte concentration (Am) approaches the accurate value (A0) when matrix effects disappear as measurements are conducted while lowering the normalized sample concentration (Snorm) by real-time dilution.

Origin and early history of Die Methode des Eichzusatzes or The Method of Standard Addition with primary emphasis on its origin, early design, dissemination, and usage of terms

The Method of Standard Additions or The Standard Addition Method, often referred to by its acronym as just SAM, is a proverbial workhorse in both inorganic and organic quantitative analytical chemistry and in related disciplines such as geochemistry. Its advantage in mitigating the effects of matrix interferences compared with the calibration curve approach is well known and is one of its major benefits. It is presented in virtually all standard textbooks on analytical chemistry in varying degrees of complexity. Yet the story of how it originated, and by whom, is not well known. It is generally believed that it originated in the early 1950s, introduced by spectroscopists. We have determined that the priority of its use and discovery apparently belongs exclusively to Hans Hohn (1906– 1978), a mining chemist, dating from the exposition of the method in his 1937 book on polarography, Chemische Analysen mit dem Polarographen. How the method became established in other disciplines quite different from polarography is not completely clear. It is likely that it was rediscovered independently in at least two separate disciplines, X-ray fluorescence (XRF) and atomic spectroscopy, almost simultaneously in 1953, 16 years after Hohn’s original description.

Theme-based modular approach for delivering the undergraduate analytical chemistry curriculum

Since the later part of the twentieth century, educational focus has shifted from acquisition of literacy skills only (simple reading, writing, and calculating skills) to inclusion of critical reading and thinking, clear and persuasive communication, and problem-solving skills [1]. In 1996, the Advisory Committee to the National Science Foundation Directorate for Education and Human Resources released a report of the review of undergraduate education in science, mathematics, and engineering titled Shaping the future: new expectations for undergraduate education in science, mathematics, engineering, and technology [2]. The overarching recommendation of this report is that “All students have access to supportive, excellent undergraduate education in science, mathematics engineering and technology, and all students learn these subjects by direct experience with the methods and process of inquiry” [2]. As such, an area of undergraduate science education that has received much attention lately is the type of instructional approach employed. In most academic settings, the typical instructional approach (a.k.a. the traditional approach) comprises lectures where faculty presents facts to students. These lectures are generally accompanied by a number of pretested laboratory experiments with predetermined outcomes. Also, the laboratory experiments are selected to survey a particular set of topics in 3–4-h time periods. A more modern approach, commonly referred to as inquiry-based, includes many variants such as cooperative learning, problem-based learning, discovery-based learning, and others. The commonalities of these approaches lie in their philosophy of active student participation in the entire educational process of teaching and learning [3]. There has been much debate on the strengths and the flaws of these two pedagogical approaches. For example, a strength of the traditional approach is its focus on content coverage and grounding in the fundamentals. However, in the process it inadvertently overlooks the development of the thought process (critical thinking) and professional skills, which are both important for the student’s future endeavors in the chemical industry or academia [3, 4]. On the other hand, the inquiry-based model emphasizes critical thinking and professional skills development. It also offers the opportunity for depth of coverage. However, being faced with the limitations of time and resources, one sacrifice breadth of coverage [5–11]. Finding a balance between this traditional pedagogy and more modern teaching pedagogies is necessary to ensure the complete development of an analytical chemist who is equipped to face the challenges of a twenty-first century global economy [12–14]. At Butler University, we are exploring a pedagogical model that purports to exploit the strengths and serves as a bridge between the traditional and inquiry-based models. In this new approach, we utilize the strengths of the lecture to deliver content while still involving students in active participation in their learning through in-class collaborative group problem-solving. Critical thinking and professional skills development are then strongly addressed within the framework of theme-based modular laboratory courses. In this article we present (1) how quantitative analytical chemistry fits into the new approach, (2) detail of the central framework, (3) two examples of its pilot implementation to demonstrate its flexibility, and (4) our thoughts for future directions. Anal Bioanal Chem (2008) 392:1–8 DOI 10.1007/s00216-008-2240-4

Major Advances in Testing of Dairy Products: Milk Component and Dairy Product Attribute Testing

Milk component analysis is relatively unusual in the field of quantitative analytical chemistry because an analytical test result determines the allocation of very large amounts of money between buyers and sellers of milk. Therefore, there is high incentive to develop and refine these methods to achieve a level of analytical performance rarely demanded of most methods or laboratory staff working in analytical chemistry. In the last 25 yr, well-defined statistical methods to characterize and validate analytical method performance combined with significant improvements in both the chemical and instrumental methods have allowed achievement of improved analytical performance for payment testing. A shift from marketing commodity dairy products to the development, manufacture, and marketing of value added dairy foods for specific market segments has created a need for instrumental and sensory approaches and quantitative data to support product development and marketing. Bringing together sensory data from quantitative descriptive analysis and analytical data from gas chromatography olfactometry for identification of odor-active compounds in complex natural dairy foods has enabled the sensory scientist and analytical chemist to work together to improve the consistency and quality of dairy food flavors.

Quantitative Assay for Starch by Colorimetry Using a Desktop Scanner

Solution color change by mixture of iodine with starch is well-known. Here we describe a procedure to produce a standard curve for quantification of starch concentration using colorimetry. The colorimetry is performed by image analysis of a picture of solutions obtained using a desktop scanner. The analysis is performed using a Visual Basic computer program (COLORS.EXE) that measures red, green, and blue pixel intensities from the image. The computer program is provided in Supplemental Material in JCE Online. The lower limit of detection of the described assay is of the order of 10 mg/dL. The measurement of the starch content in potatoes is given as an example. The experiment can serve as an introduction to quantitative analytical chemistry at the high school level and has the desirable feature of using only common and inexpensive reagents. The procedure is likely amenable to further development for other food science experiments.

The influence of variations in atmospheric pressure on the uncertainty budget of weighing results

The various assays in quantitative analytical chemistry always include mass determinations, along with other operations, and the same is true for the uncertainty budget of such a procedure. In order to obtain an accurate weighing result it is necessary to consider air buoyancy, which depends on, besides other parameters, atmospheric pressure. In contrast to air temperature and humidity, it is not possible to control the atmospheric pressure in a conventional laboratory. Therefore, it can be necessary to consider the uncertainty of pressure in uncertainty calculations of weighing operations, depending on the mass and density of the weighed object. The theoretical relationship between pressure variations and obtained weight value are derived. Experimental confirmation was obtained on the one hand by the mass determination of five Pyrex glass bottles over a period of 6 months; these are objects with a lower density than the reference weights of the balance, thus showing a negative dependence of weight value on atmospheric pressure. On the other hand, a tungsten cylinder was weighed over several weeks; this high-density object has a positive dependence. In both cases the experimental slopes agreed with the theoretical values. The consequences on the uncertainty budget of a weighing operation are remarkable: the total uncertainty of the mass determination of a 90 g glass bottle is 0.3 mg whereas it is 4 μg for a 4.6 g tungsten cylinder. The contributions originating from the pressure variation alone are 0.3 mg and 3.5 μg, respectively, i.e., the pressure uncertainty dominates and is much more important than the uncertainty contributions of balance repeatability and linearity.