Experimental methods in chemical engineering: X‐ray photoelectron spectroscopy‐XPS

X‐ray photoelectron spectroscopy (XPS) is a quantitative surface analysis technique used to identify the elemental composition, empirical formula, chemical state, and electronic state of an element. The kinetic energy of the electrons escaping from the material surface irradiated by an x‐ray beam produces a spectrum. XPS identifies chemical species and quantifies their content and the interactions between surface species. It is minimally destructive and is sensitive to a depth between 1–10nm. The elemental sensitivity is in the order of 0.1 atomic %. It requires ultra high vacuum ( Pa) in the analysis chamber and measurement time varies from minutes to hours per sample depending on the analyte. XPS dates back 50 years ago. New spectrometers, detectors, and variable size photon beams, reduce analysis time and increase spatial resolution. An XPS bibliometric map of the 10 000 articles indexed by Web of Science^[1] identifies five research clusters: (i) nanoparticles, thin films, and surfaces; (ii) catalysis, oxidation, reduction, stability, and oxides; (iii) nanocomposites, graphene, graphite, and electro‐chemistry; (iv) photocatalysis, water, visible light, and ; and (v) adsorption, aqueous solutions, and waste water.     

Mechanical behavior of cold-water fish gelatin gels crosslinked with 1,4-butanediol diglycidyl ether

In this work, chemical crosslinking with 1,4-butanediol diglycidyl ether (BDDGE) is used as strategy to enhance mechanical performance of fish gelatin (FG) gels in order to meet the properties' range of mammalian gelatin physical gels. Joint analysis of free amino groups, swelling ratio, and total soluble material indicates that crosslinking degree increases with increasing FG concentration and it is favored by a 0.2 BDDGE/FG ratio. Increasing crosslinking degree enhances gel indentation strength and shear modulus (μ) while decreases fracture toughness (G_IC). Measured μ and G_IC values lies within the range exhibited by mammalian gelatin physical gels, but the relationship between these parameters is opposite. This is due to the different fracture mechanisms occurring in chemically crosslinked and physical gels.     

Molecular size evaluation of linear and branched paraffins from the gasoline pool by DFT quantum chemical calculations

A good approach of the critical molecular dimensions of 35 linear and branched C5-C8 paraffins by DFT quantum chemical calculations at B3LYP/6-31G** level of theory in gas phase is described. In this context, we found that either the determined molecular width or width-height average values can be used as critical measures in the analysis for selection of molecular sieves materials, depending on their pore size and shape. The molecular width values for linear and monosubstituted paraffins are 4.2 and 5.5 Å, respectively. In the case of disubstituted paraffins, the values are 5.5 Å for 2,3-, 2,4-, 2,5- and 3,4-disubstituted and for 2,2- and 3,3-disubstituted are 6.7-7.1 Å. The values for ethyl-substituted are 6.1-6.7 Å and for trisubstituted isoparaffins are 6.7. In order to select a porous material for selective separation of isoparaffins and paraffins, the zeolite diffusivity can be correlated with the critical diameter of the paraffins according to the geometry-limited diffusion concept and the effective minimum dimensions of the molecules. The calculated values of CPK molecular volume of the titled paraffins showed a good discrimination between the number of carbons and molecular size.     

Electrical properties of Pb0.98Eu0.02(ZryTi1−y)0.995O3 prepared by sol–gel processing

A Pb_0.98Eu_0.02(Zr_yTi_1−y )_0.995O₃ compound series, with y = 0.60, 0.53 and 0.45 was prepared. PZT samples were synthesized by sol–gel technique. The crystallization and quality of the compounds were analyzed by powder X-ray diffraction and electron microscopy. The shape of the ε′(ω) vs T curves can be considered typical of a ferro-paraelectric transition. The ferro-paraelectric transition temperature for each composition was 348, 328 and 307°C, for the y = 0.45, 0.53 and 0.60, respectively. σ′(ω) is strongly influenced by short range processes. For the logσ′(ω) curves as function of temperature, there is evidence of a non dispersive dc-conductivity component for the high temperature region. The associated dc-activation energies are larger than those calculated for the ac region (at lower temperatures).     

CV3: Visual Exploration,Assessment, and Comparison of CVs

The Curriculum Vitae (CV, also referred to as “résumé”) is an established representation of a person's academic and professional history. A typical CV is comprised of multiple sections associated with spatio‐temporal, nominal, hierarchical, and ordinal data. The main task of a recruiter is, given a job application with specific requirements, to compare and assess CVs in order to build a short list of promising candidates to interview. Commonly, this is done by viewing CVs in a side‐by‐side fashion. This becomes challenging when comparing more than two CVs, because the reader is required to switch attention between them. Furthermore, there is no guarantee that the CVs are structured similarly, thus making the overview cluttered and significantly slowing down the comparison process. In order to address these challenges, in this paper we propose “CV3”, an interactive exploration environment offering users a new way to explore, assess, and compare multiple CVs, to suggest suitable candidates for specific job requirements. We validate our system by means of domain expert feedback whose results highlight both the efficacy of our approach and its limitations. We learned that CV3 eases the overall burden of recruiters thereby assisting them in the selection process.     

Optimal sampling for the estimation of dispersion parameters in soil columns using an Iterative Genetic Algorithm

In groundwater modelling, an appropriate soil characterization is strongly recommended to evaluate both the fate and transport of solutes and the performance of groundwater remediation criterion, though parameter estimation techniques are often blocked by several inherent difficulties (i.e. ill-posedness and insufficient quantity and quality of observation data). In this paper, an iterative decision model is built and tested in order to locate the position of a fixed number of sample points in a soil column experiment to obtain optimal parameter estimation (OPE), minimizing the parametric uncertainty and the overall cost of the experimental campaign. Starting from an initial guess of chosen points (given by a fraction of the total disposable ones), an Iterative Genetic Algorithm (IGA) is capable of finding the best points able to minimize a first-order approximation of the parameter covariance matrix. The parameter estimates are updated under a Bayesian scheme, using exclusively the observations collected after the earlier run of minimization, and the iterative process stops when the imposed convergence criterion based on the parameter values is reached. An important contribution of this work is the development of an effective direct search algorithm (IGA) for solving the sampling network optimization problem at a laboratory scale.     

Hyper-arc consistency of polynomial constraints over finite domains using the modified Bernstein form

This paper describes an algorithm to enforce hyper-arc consistency of polynomial constraints defined over finite domains. First, the paper describes the language of so called polynomial constraints over finite domains, and it introduces a canonical form for such constraints. Then, the canonical form is used to transform the problem of testing the satisfiability of a constraint in a box into the problem of studying the sign of a related polynomial function in the same box, a problem which is effectively solved by using the modified Bernstein form of polynomials. The modified Bernstein form of polynomials is briefly discussed, and the proposed hyper-arc consistency algorithm is finally detailed. The proposed algorithm is a subdivision procedure which, starting from an initial approximation of the domains of variables, removes values from domains to enforce hyper-arc consistency.     

Multi-stage modeling using fuzzy multi-criteria feature selection to improve survival prediction of ICU septic shock patients

In many binary medical classification problems, the cost of misclassifying one category is higher than the other, and in these applications it is desirable to employ a classifier with selective sensitivity or specificity. This work explores the utility of a fuzzy multi–criteria function for performance evaluation during knowledge–based medical classification and prediction. The method presented here uses fuzzy optimization to combine the sensitivity, specificity, and accuracy of classification as goals in a single objective function. This approach is used to assign flexible goals, which can be used to maximize the outcome in terms of each one of the goals. The proposed approach significantly increases the sensitivity and the specificity while maintaining or increasing accuracy. The versatility of the method is further exploited in a multi-model approach, using individual structures of multi-objective optimization of sensitivity and specificity separately, and then combining their outcomes through a decision-making module. Among various medical benefits derived from applying this technique, the divergent feature sets selected by high sensitivity and specificity models lend insight into factors more integrally connected to what causes risk of death for patients.