Clarifying the complex chemistry of cobalt(II) thiocyanate-based tests for cocaine using single-crystal X-ray diffraction and spectroscopic techniques.

Cobalt(II) thiocyanate-based tests are routinely used to screen cocaine products, with the formation of a blue species interpreted as a positive response. An array of other organic bases has been identified as false positives - including well-documented cocaine product adulterant lidocaine and its salt. False positives prompt continued test development, though improvements are hindered by unresolved product structures and reaction pathways. Toward greater clarity, cobalt(II) thiocyanate reactions with cocaine hydrochloride, along with lidocaine and its salt, were investigated using multiple analytical techniques. Reactions involving cocaine hydrochloride yielded glassy, amorphous blue material while reactions of lidocaine hydrochloride monohydrate produced larger, needle-like crystals whose structure was determined via single-crystal X-ray diffraction to be an ion pair (Hlidocaine+ )2 ([Co(SCN)4 ]2- )·H2 O. While the blue precipitate isolated from reactions involving cocaine hydrochloride was unsuitable for crystallographic structure determination, comparative ultraviolet-visible, attenuated total reflectance infrared, and Raman spectroscopic analysis - along with elemental analysis - supports that this solid is comprised of a comparable ion pair (Hcocaine+ )2 [Co(SCN)4 ]2- . Pink crystals isolated from lidocaine reaction vessels were identified as coordination compounds cis-[CoL2 (SCN)2 ] and trans-[CoL2 (SCN)2 ] where L = lidocaine, while pink crystals from both cocaine hydrochloride and lidocaine hydrochloride monohydrate reaction vessels were the coordination polymer trans-[Co(H2 O)2 (SCN)2 ]·H2 O. The results presented herein enable reaction optimization to favor a desired product, whether ion pair or coordination species.

Digital imaging and vision analysis in science project improves the self-efficacy and skill of undergraduate students in computational work.

In many areas of science, the ability to use computers to process, analyze, and visualize large data sets has become essential. The mismatch between the ability to generate large data sets and the computing skill to analyze them is arguably the most striking within the life sciences. The Digital Image and Vision Applications in Science (DIVAS) project describes a scaffolded series of interventions implemented over the span of a year to build the coding and computing skill of undergraduate students majoring primarily in the natural sciences. The program is designed as a community of practice, providing support within a network of learners. The program focus, images as data, provides a compelling 'hook' for participating scholars. Scholars begin the program with a one-credit spring semester seminar where they are exposed to image analysis. The program continues in the summer with a one-week, intensive Python and image processing workshop. From there, scholars tackle image analysis problems using a pair programming approach and can finish the summer with independent research. Finally, scholars participate in a follow-up seminar the subsequent spring and help onramp the next cohort of incoming scholars. We observed promising growth in participant self-efficacy in computing that was maintained throughout the project as well as significant growth in key computational skills. DIVAS program funding was able to support seventeen DIVAS over three years, with 76% of DIVAS scholars identifying as women and 14% of scholars identifying as members of an underrepresented minority group. Most scholars (82%) entered the program as first year students, with 94% of DIVAS scholars retained for the duration of the program and 100% of scholars remaining a STEM major one year after completing the program. The outcomes of the DIVAS project support the efficacy of building computational skill through repeated exposure of scholars to relevant applications over an extended period within a community of practice.

Benzoic acid derivatives as luminescent sublimation dyes in cyanoacrylate fuming of latent fingerprints.

Development of latent prints employing cyanoacrylate ester (CA) can be a multistep process including CA fuming and subsequent fluorescent staining to produce fingerprints of sufficient contrast for comparison work. To enable a single-step CA fuming-staining process, a selection of fluorophores have been developed as sublimation dyes in CA fuming. A greater array of such luminescent sublimation dyes would allow users greater flexibility in selecting a particular dye-CA combination to best suit their processing needs. Toward this end, six benzoic acid derivatives were evaluated for use as luminescent sublimation dyes under elementary CA fuming conditions using a single non-porous surface type and an inexpensive handheld UV lamp for excitation. Two benzoic acid derivatives, 2-hydroxybenzoic acid (salicylic acid) and 2-aminobenzoic acid (anthranilic acid), were identified as new potential luminescent sublimation dyes with stained fingerprints excited at 254 nm. The fluorescence intensity and stability of prints produced via the sublimation of CA with 2-hydroxybenzoic acid and 2-aminobenzoic acid were evaluated over approximately six weeks using image and statistical analysis.

Printed Colorimetric Arrays for the Identification and Quantification of Acids and Bases.

Solid supported colorimetric sensing arrays have the advantage of portability and ease of use when deployed in the field, such as crime scenes, disaster zones, or in war zones, but many sensor arrays require complex fabrication methods. Here, we report a practical method for the fabrication of 4 × 4 colorimetric sensor arrays, which are printed on nylon membranes, using a commercially available inkjet printer. In order to test the efficacy of the printed arrays, they were exposed to 43 analytes at concentrations ranging from 0.001 to 3.0 M for a total of 559 samples of inorganic and organic acids or bases including hydrochloric, acetic, phthalic, malonic, picric, and trifluoroacetic acid, ammonium hydroxide, sodium hydroxide, lysine, and water as the control. Colorimetric data from the imaged arrays was analyzed with linear discriminant analysis and k-nearest neighbors to determine the analyte and concentration with ∼88-90% accuracy. Overall, the arrays have impressive analytical power to identify a variety of analytes at different concentrations while being simple to fabricate.

Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. Colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10 M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study.

An Improved Comparison of Chemometric Analyses for the Identification of Acids and Bases With Colorimetric Sensor Arrays.

Colorimetric sensor arrays incorporating red, green, and blue (RGB) image analysis use value changes from multiple sensors for the identification and quantification of various analytes. RGB data can be easily obtained using image analysis software such as ImageJ. Subsequent chemometric analysis is becoming a key component of colorimetric array RGB data analysis, though literature contains mainly principal component analysis (PCA) and hierarchical cluster analysis (HCA). Seeking to expand the chemometric methods toolkit for array analysis, we explored the performance of nine chemometric methods were compared for the task of classifying 631 solutions (0.1 to 3 M) of acetic acid, malonic acid, lysine, and ammonia using an eight sensor colorimetric array. PCA and LDA (linear discriminant analysis) were effective for visualizing the dataset. For classification, linear discriminant analysis (LDA), (k nearest neighbors) KNN, (soft independent modelling by class analogy) SIMCA, recursive partitioning and regression trees (RPART), and hit quality index (HQI) were very effective with each method classifying compounds with over 90% correct assignments. Support vector machines (SVM) and partial least squares - discriminant analysis (PLS-DA) struggled with ~85 and 39% correct assignments, respectively. Additional mathematical treatments of the data set, such as incrementally increasing the exponents, did not improve the performance of LDA and KNN. The literature precedence indicates that the most common methods for analyzing colorimetric arrays are PCA, LDA, HCA, and KNN. To our knowledge, this is the first report of comparing and contrasting several more diverse chemometric methods to analyze the same colorimetric array data.

Colorimetric Sensor Arrays for the Detection and Identification of Chemical Weapons and Explosives.

There is a significant demand for devices that can rapidly detect chemical-biological-explosive (CBE) threats on-site and allow for immediate responders to mitigate spread, risk, and loss. The key to an effective reconnaissance mission is a unified detection technology that analyzes potential threats in real time. In addition to reviewing the current state of the art in the field, this review illustrates the practicality of colorimetric arrays composed of sensors that change colors in the presence of analytes. This review also describes an outlook toward future technologies, and describes how they could possibly be used in areas such as war zones to detect and identify hazardous substances.

Applied circular dichroism: a facile spectroscopic tool for configurational assignment and determination of enantiopurity.

In order to determine if electronic circular dichroism (ECD) is a good tool for the qualitative evaluation of absolute configuration and enantiopurity in the absence of chiral high performance liquid chromatography (HPLC), ECD studies were performed on several prescriptions and over-the-counter drugs. Cotton effects (CE) were observed for both S and R isomers between 200 and 300 nm. For the drugs examined in this study, the S isomers showed a negative CE, while the R isomers displayed a positive CE. The ECD spectra of both enantiomers were nearly mirror images, with the amplitude proportional to the enantiopurity. Plotting the differential extinction coefficient (Δε) versus enantiopurity at the wavelength of maximum amplitude yielded linear standard curves with coefficients of determination (R (2)) greater than 97% for both isomers in all cases. As expected, Equate, Advil, and Motrin, each containing a racemic mixture of ibuprofen, yielded no chiroptical signal. ECD spectra of Suphedrine and Sudafed revealed that each of them is rich in 1S,2S-pseudoephedrine, while the analysis of Equate vapor inhaler is rich in R-methamphetamine.

Synthesis of a Fluorophore with Improved Optical Brightness.

The synthesis and characterization of a novel fluorophore(1), with potential application as an optical brightener are reported. This compound was prepared by reacting 4,4-diaminostilbene-2,2-disulfonic acid with cyanuric chloride in the presence of Na2CO3 followed by the addition of trityl aniline. Solution and solid state fluorescence demonstrated a strong blue/purple emission centered at 450 nm. 1H-NMR spectroscopy, mass spectrometry analysis, elemental analysis, and DOSY-NMR were used for the characterization of the fluorophore.

DETECHIP: a sensor for drugs of abuse.

The design and preliminary characterization of a novel sensor for drugs of abuse, DETECHIP, is described in this proof-of-concept note. Combining both colorimetric and fluorimetric assays, DETECHIP is suitable for lab and field use. More than a conventional spot test which provides a single "yes or no" answer, DETECHIP provides twenty responses for a more complete characterization of suspect material. This is accomplished by visually noting colorimetric and fluorescent changes of carefully selected dyes upon the addition of test analytes, including drugs of abuse, with respect to controls. Color and fluorescence changes are recorded numerically so that a 20 digit identification code can be constructed for comparison of test analytes and known compounds. DETECHIP is applicable to a variety of drugs, both plant-derived and synthetic, addressing the need to use several different spot tests simultaneously for a single sample.

Current trends in the detection of peroxide-based explosives.

The increased use of peroxide-based explosives (PBEs) in criminal and terrorist activity has created a demand for continued innovation in the detection of these agents. This review provides an update to a previous 2006 review on the detection of PBEs, with a focus in this report on luminescence and fluorescence methods, infrared and Raman spectroscopy, mass spectrometry, and electrochemical techniques. Newer developments in gas chromatography and high performance liquid chromatography methods are also discussed. One recent trend that is discussed is an emphasis on field measurements through the use of portable instruments or portable assay formats. An increase in the use of infrared spectroscopy and mass spectrometry for PBE analysis is also noted. The analysis of triacetone triperoxide has been the focus in the development of many of these methods, although hexamethylene triperoxide diamine has received increased attention in PBE detection during the last few years.

18-crown-6 as a class I organic modifier in MEKC.

The use of 18-crown-6 as a class I organic modifier for SDS MEKC is described. Two positional isomer series, one neutral (nitrotoluenes) and one anionic (nitrophenols), are used to demonstrate different effects of 18-crown-6 on analyte retention in SDS MEKC.