Suha Elderderi

Suha Elderderi

*This is an algorithmically generated author record based on publicly available information.

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Suha Elderderi has a total of 24 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Comparison of Vibrational Spectroscopic Techniques for Quantification of Water in Natural Deep Eutectic Solvents

    by Suha Elderderi, Pierre-Yves Sacré, Laura Wils, Igor Chourpa, Abdalla A. Elbashir, Philippe Hubert, Hugh J. Byrne, Leslie Boudesocque-Delaye, Eric Ziemons, Franck Bonnier

    Vibrational spectroscopic techniques, i.e., attenuated total reflectance infrared (ATR-IR), near infrared spectroscopy (NIRS) and Raman spectroscopy (RS), coupled with Partial Least Squares Regression (PLSR), were evaluated as cost-effective label-free and reagent-free tools to monitor water content in Levulinic Acid/L-Proline (LALP) (2:1, mol/mol) Natural Deep Eutectic Solvent (NADES). ATR-IR delivered the best outcome of Root Mean Squared Error (RMSE) of Cross-Validation (CV) = 0.27% added water concentration, RMSE of Prediction (P) = 0.27% added water concentration and mean % relative error = 2.59%. Two NIRS instruments (benchtop and handheld) were also compared during the study, respectively yielding RMSECV = 0.35% added water concentration, RMSEP = 0.56% added water concentration and mean % relative error = 5.13% added water concentration, and RMECV = 0.36% added water concentration, RMSEP = 0.68% added water concentration and mean % relative error = 6.23%. RS analysis performed in quartz cuvettes enabled accurate water quantification with RMECV = 0.43% added water concentration, RMSEP = 0.67% added water concentration and mean % relative error = 6.75%. While the vibrational spectroscopic techniques studied have shown high performance in relation to reliable determination of water concentration, their accuracy is most likely related to their sensitivity to detect the LALP compounds in the NADES. For instance, whereas ATR-IR spectra display strong features from water, Levulinic Acid and L-Proline that contribute to the PLSR predictive models constructed, NIRS and RS spectra are respectively dominated by either water or LALP compounds, representing partial molecular information and moderate accuracy compared to ATR-IR. However, while ATR-IR instruments are common in chemistry and physics laboratories, making the technique readily transferable to water quantification in NADES, Raman spectroscopy offers promising potential for future development for in situ, sample withdrawal-free analysis for high throughput and online monitoring.


  • Monitoring the water content in NADES extracts from spirulina biomass by means of ATR-IR spectroscopy

    by Suha Elderderi, Soukaina Hilali, Laura Wils, Igor Chourpa, Martin Soucé, Barbara Clément-Larosière, Abdalla A. Elbashir, Hugh J. Byrne, Emilie Munnier, Leslie Boudesocque-Delaye, et al.

    Attenuated total reflectance-infrared spectroscopy (ATR-IR) coupled with partial least squares regression (PLSR) was evaluated as a rapid, label free and cost-effective tool to quantify water content in extracts obtained from spirulina wet biomass using a glucose glycerol natural deep eutectic solvent (NADES). NADESs are green, renewable and biodegradable solvents with unique properties outcompeting existing organic solvents, for instance, for plant or biomass extraction. The properties of NADESs depend critically on their water concentration, and therefore, it is essential to develop methods to monitor it, to ensure optimal extraction efficiency and experimental repeatability to achieve a better standardization of extraction protocols. First, Karl Fischer titration was performed on a set of 20 NADES extracts in order to obtain reference water concentrations. Secondly, ATR-IR spectra were collected and subjected to datamining to construct PLSR predictive models. An R2 value of 0.9996, a mean root mean square error of cross validation of 0.136% w/w and a root mean square error of prediction of 0.130% w/w highlight the feasibility and reliability to perform quantitative analysis using ATR-IR. Moreover, the mean relative error percentage achieved, ∼0.5%, confirms the high accuracy of water concentration determination in NADES extracts. This work demonstrates that powerful alternatives are available to provide more environmentally responsible analytical protocols. ATR-IR spectroscopy applied to NADES extracts does not require any sample preparation, reagents or solvents and has minimal requirements for single use consumables. The technique is consistent with current concerns to develop greener chemistry, especially in the field of extraction of natural compounds from plants which currently represents a major focus of interest in both research and industry.


  • Open Access

    In Situ Water Quantification in Natural Deep Eutectic Solvents Using Portable Raman Spectroscopy

    by Suha Elderderi, Laura Wils, Charlotte Leman-Loubière, Hugh J. Byrne, Igor Chourpa, Cécile Enguehard-Gueiffier, Emilie Munnier, Abdalla A. Elbashir, Leslie Boudesocque-Delaye, Franck Bonnier

    Raman spectroscopy is a label-free, non-destructive, non-invasive analytical tool that provides insight into the molecular composition of samples with minimum or no sample preparation. The increased availability of commercial portable Raman devices presents a potentially easy and convenient analytical solution for day-to-day analysis in laboratories and production lines. However, their performance for highly specific and sensitive analysis applications has not been extensively evaluated. This study performs a direct comparison of such a commercially available, portable Raman system, with a research grade Raman microscope system for the analysis of water content of Natural Deep Eutectic Solvents (NADES). NADES are renewable, biodegradable and easily tunable “green” solvents, outcompeting existing organic solvents for applications in extraction from biomass, biocatalysis, and nanoparticle synthesis. Water content in NADES is, however, a critical parameter, affecting their properties, optimal use and extraction efficiency. In the present study, portable Raman spectroscopy coupled with Partial Least Squares Regression (PLSR) is investigated for rapid determination of water content in NADES samples in situ, i.e., directly in glassware. Three NADES systems, namely Betaine Glycerol (BG), Choline Chloride Glycerol (CCG) and Glucose Glycerol (GG), containing a range of water concentrations between 0% (w/w) and 28.5% (w/w), were studied. The results are directly compared with previously published studies of the same systems, using a research grade Raman microscope. PLSR results demonstrate the reliability of the analysis, surrendering R2 values above 0.99. Root Mean Square Errors Prediction (RMSEP) of 0.6805%, 0.9859% and 1.2907% w/w were found for respectively unknown CCG, BG and GG samples using the portable device compared to 0.4715%, 0.3437% and 0.7409% w/w previously obtained by analysis in quartz cuvettes with a Raman confocal microscope. Despite the relatively higher values of RMSEP observed, the comparison of the percentage of relative errors in the predicted concentration highlights that, overall, the portable device delivers accuracy below 5%. Ultimately, it has been demonstrated that portable Raman spectroscopy enables accurate quantification of water in NADES directly through glass vials without the requirement for sample withdrawal. Such compact instruments provide solvent and consumable free analysis for rapid analysis directly in laboratories and for non-expert users. Portable Raman is a promising approach for high throughput monitoring of water content in NADES that can support the development of new analytical protocols in the field of green chemistry in research and development laboratories but also in the industry as a routine quality control tool.


  • In situ Analytical Quality Control of chemotherapeutic solutions in infusion bags by Raman spectroscopy

    by Alaa A. Makki, Suha Elderderi, Victor Massot, Renaud Respaud, Hugh.J. Byrne, Clovis Tauber, Dominique Bertrand, Elhadi Mohammed, Igor Chourpa, Franck Bonnier