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  • Open access
  • 52 Reads
Synthesis and Chiral Molecular Recognition of Phenylene-Bridged Bispyrrole Derivatives Having N-Substituted Imino Groups

Spectroscopic sensing of chiral substances with chemosensors has attracted much attentions in the field of supramolecular chemistry. We previously reported that p-phenylene-bridged bispyrrole bearing N-alkylimino groups becomes an acid-responsive single trichromatic BOG (blue, orange, and green) luminescent dye capable of emitting pure WL in solution.[1]The observed variable emission originates from its trichromatic luminescent behavior upon protonation of the imino groups. As an extension of the study, we newly designed the m-phenylene-bridged bispyrrole bearing N-substituted imino groups as an acyclic chemosensor for carboxylic acids. We expected that the imino (Schiff base) groups specifically bind the carboxylic acid via acid-base hydrogen bonding interactions. This guest-binding might bring about the specific conformational changes of the host molecule to give the characteristic spectral changes in UV-Vis absorption, fluorescence, and CD spectroscopies.

In this poster presentation, we report synthesis and chemoseising behaviors of the three-types of m-phenylene-bridged bispyrrole bearing N-pyridyl, benzyl, or alkyl substituted imino groups. These bispyrrole derivatives showed spectral changes in the absorption and CD spectroscopy upon mixing with chiral dibenzoyl tartaric acid and mandelic acid. Especially, the pyridyl-substituted bispyrrole showed characteristic and relatively stronger Cotton effect in CD spectroscopy, which may originate from the multi-points and multi-step host-guest interactions.

[1] K. Imamura, Y. Ueno, S. Akimoto, K. Eda, Y. Du, C. Eerdun, M. Wang, K. Nishinaka, A. Tsuda, ChemPhotoChem 2017, 1, 427-431.

  • Open access
  • 114 Reads
Hydroxychalcone Color Indicators for pH and Fluoride Ion
, , , ,

Chalcone, an α,β-unsaturated carbonyl group bridged aromatic compound, exhibits a variety of biological activities. With an objective to develop a novel chalcone-based functional dye, we have synthesized a chalcone diol, bearing two hydroxyl groups (-OH) at the 2-positions on both phenyl rings. This new chalcone derivative was then employed as a color indicator for pH and fluoride ion[1]. The chalcone diol showed a vivid color change from colorless to yellow (halochromism) in water at pH ≥ 10. In CH3CN, this chalcone diol showed a specific color change from colorless to red upon sensing of fluoride ion.

The absorption spectral study together with TD-DFT calculations and X-ray crystallographic analysis revealed that the characteristic Π-resonant structures of the chalcone diol caused by OH–F- interactions and the planar conformation owing to its intramolecular hydrogen bonding may provide a strong charge transfer (CT) absorption in the visible region.

The observed results and the mechanisms revealed in this study provide important ideas and strategies for the future molecular design of chalcone-based chemosensors and bioactive substances.

[1] Y. Du, F. Liang, M. Hu, R. Bu, M. Wang, A. Tsuda, C. Eerdun, RSC Advances 2020, 10, 37463–37472.

  • Open access
  • 78 Reads
Developing potentiometric PVC-plasticized sensors for Sc3+

Nowadays scandium is widely used in high-tech fields such as electronics, aerospace, optics, catalysis, and metallurgical industries due to its unique physical, chemical, electric and magnetic characteristics. With the growth of miscellaneous commercial applications of this element and its compounds, monitoring of scandium in technological processes is in demand and thereby making it interesting in the analytical chemistry area. Different conventional analytical methods have been employed to measure scandium, and the most often applied are ICP-MS and ICP-AES. Despite the high precision and sensitivity of these tools, serious drawbacks including sophisticated and time-consuming analysis limit their wide use. On the other hand, potentiometric sensors possess merits over these conventional analytical methods due to their cost-effectiveness and reagent-free procedures as well as their reasonable precision and rapid response time. Potentiometric sensors based on polymeric membranes are routinely used to measure different cations and anions, but no study has yet been carried out for scandium sensors. This research is devoted to the development of Sc3+ potentiometric sensors. A series of potentiometric electrodes with polymer plasticized membranes was prepared using different neutral ligands adopted from liquid extraction of rare earth metals as sensing components. These ligands include phosphine oxides and diamides of various organic acids. The membranes also contained poly(vinylchloride) as polymeric matrix, o-nitrophenyloctyl ether as a solvent-plasticizer, and chlorinated cobalt dicarbollide or fluorinated tetraphenyl borate derivatives as cation-exchangers. Most sensors exhibited Nernstian or super-Nernstian response towards Sc3+ across the concentration range (10-5 – 10-3 M) with a low detection limit of about 0.4 mg/l in acidic media (pH=2). Interferences from other rare earth metals were measured by the separate solution method, and most of the proposed sensors were found to be more selective towards Sc3+. Reproducible, stable, and precise results for sensing properties of the developed sensors imply the relevance of using these instruments for scandium quantification in real technological solutions.

  • Open access
  • 109 Reads
Development of a pattern recognition tool for the classification of electronic tongue signals using machine learning.

Electronic tongue type sensor arrays are made of different materials with the property of capturing signals independently by each sensor. The signals captured when conducting electrochemical tests often have high dimensionality, which increases when performing the data unfolding process. This unfolding process consits on arranged the data coming from different experiments, sensors and sample times, thus the obtained infomation is arranged in a two dimensional matrix. In this work, a description of a tool for the analysis of electronic tongue signals is developed. These tool is developed in Matlab® App Designer, to process and classify the data from different substances analyzed by an electronic tongue type sensor array. The data processing is carried out through the execution of the following stages: (1) data unfolding, (2) normalization, (3) dimensionality reduction, (4) classification through a supervised machine learning model and finally (5) a cross validation procedure to calculate a set of classification performance measures. Some important characteristics of this tool are the possibility to tune the parameters of the dimensionality reduction and classifier algorithms, and also plot the two and three dimensional scatter plot of the features after reduced the dimensionality. This to see the data separability between classes and compatibility in each class. This interface is successfully tested with two electronic tongue sensor array datasets with multifrequency large amplitude pulse voltammetry (MLAPV) signals. The developed graphical user interface allows comparing different methods in each of the mentioned stages to find the best combination of methods and thus obtain the highest values of classification performance measures.

  • Open access
  • 202 Reads
Hydroponics Monitoring Through UV-Vis Spectroscopy and Artificial Intelligence: Quantification of Nitrogen, Phosphorous and Potassium

In hydroponic cultivation, monitoring and quantification of nutrients is of paramount importance. Accurate, robust sensors for detection of Nitrogen, Phosphorus and Potassium (NPK) would be desired in horticultural production. Spectroscopy can be used for this, but other nutrients interfere and hinder accurate and reliable quantification.

In order to better understand and solve nutrients’ interferences, an orthogonal experimental design has been used, based on Hoagland fertilizer solutions, a widely used complete and complex nutrient mixture. The experimental factorial design consisted of eight orthogonal levels of N, P and K rendered on 83 of different samples of Hoagland solution, each one with its own specific concentration of NPK. Concentration ranges were varied in a target analyte independent style: [N]= [103.17-554.85] ppm; [P]= [15.06-515.35] ppm; [K]= [113.78-516.45] ppm, by dilution from individual stock solutions. This strategy allowed the variation of each parameter individually, maintaining the remaining constant, enabling the individual variations as well as their correlations to be obtained. A UV-Vis-based Artificial Intelligence-enhanced (AI) system was used for quantification of NPK on the analysed samples. It featured an advanced processing algorithm named Self-Learning Artificial Intelligence (SL-AI).

From the analysis of the acquired and processed data, it was possible to understand that N spectral features are dominant, whereas P and K will behave as interferents, with information on P properties not being very evident on spectra. The obtained results allowed very good quantifications for N and K, with errors of 6.7% (0.997) and 3.8% (0.987), respectively, to be achieved. Regarding P, as expected, only satisfactory results were obtained, corresponding to a qualitative grade. The developed system can be of great potential for monitoring and quantification of NPK in hydroponic platforms.


The authors would like to thank the financial support under the ERA-NET Cofund WaterWorks2015 Call, within the frame of the collaborative international consortium AGRINUPES. This ERA-NET is an integral part of the 2016 Joint Activities developed by the Water Challenges for a Changing World Joint Programme Initiative (Water JPI/002/2015).

RM acknowledges Fundação para a Ciência e Tecnologia (FCT) research contract grant (CEEIND/017801/2018).

AFS gratefully acknowledges the financial support provided by FCT (Portugal’s Foundation for Science and Technology) within grant (DFA/BD/9136/2020).

  • Open access
  • 132 Reads
Metal-peptide complexes - a novel class of molecular receptors for electrochemical phosphate sensing

Determination of phosphate anions concentration in body fluids provides information about various disorders such as hyperparathyroidism or vitamin D deficiency. Therefore, the monitoring of phosphates level is of interest for human health. Chemical sensors are a good alternative to classic analytical methods, but their construction requires the synthesis of appropriate receptors selectively binding the analyte.

Amyloid β peptides (Aβ) related to Alzheimer’s Disease are well known for their neurotoxic properties. However, their N-terminally truncated analogs own unique coordination properties that could be employed in the design of potential receptors for biorelevant anionic species. The Aβ5-9 peptide possesses a His-2 binding motif and thus forms stable complexes with transition metal ions, where metal ion such as Cu(II) or Ni(II) is bound by three nitrogen (3N) from the His residue, the N-terminal amine, and the peptide backbone amide. The resulting chelates exhibit high stability and a labile coordination site enabling ternary interactions. Furthermore, metal-peptide complexes offer the possibility of fine-tuning their sensitivity and selectivity for desired applications by altering the amino acid sequence and metal ion center.

The present work explores and compares the coordination and redox properties of Aβ5-9 complexes with Cu(II) and Ni(II) ions using electrochemical and spectroscopic techniques. The ability of binding biologically relevant phosphate anions and nucleotides by metal-peptide complexes was also studied. Obtained results provided a new insight into the design of a promising class of peptide-based molecular receptors with potential application as recognition elements in electrochemical biosensors and in vitro clinical diagnostics.

Acknowledgments: This work has been financially supported by the Warsaw University of Technology under the program Excellence Initiative, Research University (ID-UB), BIOTECHMED-1 project no. PSP 504/04496/1020/45.010407 and implemented as a part of the Operational Program Knowledge Education Development 2014-2020 (Project No POWR.03.02.00-00-I007/16-00) co-financed by the European Social Fund.

  • Open access
  • 132 Reads
Simultaneous Quantification of five principal NSAIDs through voltammetry and artificial neural networks using a modified carbon paste electrode in pharmaceutical Samples

This work describes the development of a novel and low-cost methodology for the simultaneous quantification of five main nonsteroidal anti-inflammatory drugs (NSAIDs) in pharmaceutical samples using differential pulse voltammetry coupled with an artificial neural network model (ANN). The working electrode used as a detector was a carbon paste electrode (CPE) modified with multi-wall carbon nanotubes (MWCNT-CPE). The specific voltammetric determination of the drugs was performed by cyclic voltammetry (CV). Some characteristic anodic peaks were found at potentials of 0.337, 0.588, 0.888 V related to paracetamol diclofenac, and aspirin. For naproxen, two anodic peaks were found at 0.959 and 1.14 V and for ibuprofen an anodic peak was not observed but it did modify the baseline of the buffer at an optimum pH of 10 in 0.1 mol L-1 Britton-Robinson buffer. Since these drugs oxidation process turned out to be irreversible and diffusion-controlled, drug quantification was carried out by differential pulse voltammetry (DPV). The Box Behnken design technique's optimal parameters were: step potential of 5.85 mV, the amplitude of 50 mV, period of 750 ms, and a pulse width of 50 ms. From the voltammetric records obtained, an ANN was built to interpret the voltammograms generated at different drug concentrations to obtain a calibration of the system. The ANN model's architecture is based on a Multilayer Perceptron Network (MLP) and a Bayesian training algorithm. The trained MLP achieves R2 values greater than 0.9 for the test data to simultaneous quantification of the five drugs.

  • Open access
  • 128 Reads
Statistical analysis for selective identifications of VOCs by using surface functionalized MoS2 based sensor array

Disease diagnosis through breath analysis have attracted a significant attention in recent years due to its non-invasive nature, rapid testing ability and applicability for the patients of all ages. More than 1000 volatile organic component (VOC) exists in human breath, but only a selected VOCs are associated with specific diseases. Selective identifications of those disease marker VOCs by using array of multiple sensors is highly desirable in the current scenario. Not only the use of efficient sensors but also the use of suitable classification algorithms is essential for the selective and reliable detection of those disease markers in the complex breath. In the current study, we fabricated noble metals (Au Pd and Pt) nanoparticles functionalized MoS2 based sensor array for the selective identifications of different VOCs. Four sensors i.e. pure MoS2, Au/MoS2, Pd/MoS2 and Pt/MoS2 were tested in the exposure different VOCs like acetone, benzene, ethanol, xylene, 2-propenol, methanol and toluene at 50°C. Initially, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to discriminate those seven VOCs. As compared to the PCA, LDA was able to discriminate well among the seven VOCs. Four different machine learning algorithms like k-nearest neighbors (KNN), decision tree, random forest and multinomial logistic regression was used to identify those VOCs further. The classification accuracy of those seven VOCs by using KNN, decision tree, random forest and multinomial logistic regression were 97.14%, 92.43%, 84.1% and 98.97% respectively. These results authenticated that multinomial logistic regression performed best among all the four machine learning algorithms to discriminate and differentiate multiple VOCs popularly present in human breath.

  • Open access
  • 74 Reads
Validation of Spent Coffee Grounds as Precursors for the Development of Sustainable Carbon Dot-based for Fe3+ Optical Sensing

Carbon dots (CDs) are fluorescence carbon-based nanomaterials that possess several properties such as (photo)chemical stability, biocompatibility and good water solubility.[1, 2] They can be fabricated from a large variety of precursors, however, most available organic molecules are still expensive and their use or synthesis can lead to significant challenges to the environment and human health. It has become desirable to use biomass waste as alternative precursors in the synthesis of CDs, given that biomass waste material is ubiquitous, nontoxic, cheap, and renewable.

The significant increasement of coffee consumption has consequently led to an increase in waste products, including spent coffee grounds (SCGs), which are the residues of coffee brewing.

In this work, we fabricated SCG-based CDs via one-pot and solvent-free carbonization of solid samples generating particles with sizes between 2.1 and 3.9 nm. These carbon nanoparticles exhibited blue fluorescence and excitation-dependent emission of CDs with moderate quantum yields (2.9-5.8%).[3]

More importantly, SCG-based CDs showed potential for being used as optical Fe3+ optical sensors, with Life Cycle Assessment (LCA) studies validating the SCGs as more sustainable precursors than classical precursors, both considering a weight- or function-based functional unit.

Acknowledgments: Fundação para a Ciência e Tecnologia (FCT) is acknowledged for funding projects PTDC/QUI-QFI/2870/2020 and UIDB/00081/2020, the Ph.D. Grant SFRH/BD/144423/2019 (D.M.A.C.), and scientific employment stimulus CEECIND/01425/2017 (L.P.d.S.).


    1. Crista, D.M.A., J.C.G. Esteves da Silva, and L. Pinto da Silva, Evaluation of Different Bottom-up Routes for the Fabrication of Carbon Dots. Nanomaterials (Basel), 2020. 10(7).
    2. Vale, N., et al., Normal breast epithelial MCF-10A cells to evaluate the safety of carbon dots. RSC Medicinal Chemistry, 2021. 12(2): p. 245-253.
    3. Crista, D.M.A., et al., Turning Spent Coffee Grounds into Sustainable Precursors for the Fabrication of Carbon Dots. Nanomaterials, 2020. 10(6): p. 1209.

      • Open access
      • 146 Reads
      Comparison of The Performances of Two RNA-Based Geno-Sensing Principles for The Detection of lncPCA3 Biomarker

      The most common prostate cancer (PCa) diagnostics which is based on detection of prostate-specific antigen (PSA) in blood has specificity limitations often resulting in both false-positive and false-negative results ; therefore, improvement in PCa diagnostics using more specific PCa biomarkers is of high importance. Studies have shown that the long noncoding RNA Prostate Cancer Antigen 3 (lncPCA3) over-expressed in the urine of prostate cancer patients is an ideal biomarker for non-invasive early diagnostics of PCa. Geno-sensors based on aptamer bio-receptors (Apta-sensors) offer cost- and time-effective, and precise diagnostic tools for detection PCa biomarker . In this study, we report on further development of RNA-based Apta-sensors exploiting two different detection strategies, i.e. electrochemical (CV and IS) and optical (spectroscopic ellipsometry) measurements. These sensors were made by immobilization of thiolated CG-3 RNA aptamers on the surface of gold. Aptamer labelled with redox group (ferrocene) was used in electrochemical measurements, while non-labelled aptamer was used in total internal reflection ellipsometry (TIRE) measurements. The results obtained by these two methods were compared, the sensitivity in FM level of concentration was achieved and the required selectivity is provided by high affinity of PCA3-to-aptamer binding with KA in 107 L/mol range. The conditions for the aptamer immobilisation procedure (aptamer concentration, incubation time) were optimised. The detection of PCA3 in urine was attempted. The proposed detection approaches allow the reliable detection of PCA3 at low concentrations, thus providing a background for future development of novel, highly sensitive and cost-effective diagnostic methodologies for prostate cancer detection.


      1. Salman, J.W. et al., Prostate specific antigen as a tumor marker in prostate cancer: Biochemical and clinical aspects. In Advances in Cancer Biomarkers; Springer: 2015, 867, 93–114.
      2. Schmid, M. et al. Urinary prostate cancer antigen 3 as a tumour marker: Biochemical and clinical aspects. In Advances in Experimental Medicine and Biology; Springer, 2015; p. 291.
      3. Nabok A., Abu-Ali, H., Takita, S., Smith, D.P., Electrochemical detection of prostate cancer biomarker PCA3 using specific RNA-based aptamer labelled with ferrocene, Chemosensors, 2021, 9, 59.