Ante Jukić

Correlation of electronic structure and catalytic activity of Zr–Ni amorphous alloys for the hydrogen evolution reaction

Abstract The electrocatalytic activity of amorphous Zr–Ni alloys with respect to the hydrogen evolution reaction (h.e.r.) was studied in relation to both composition and active surface area. Kinetic parameters of the h.e.r. were evaluated by electrochemical and impedance spectroscopy techniques in 1-M NaOH solution at room temperature. Intrinsic activity of the investigated metallic glasses was related to the real exchange current density, j 0 and the reciprocal value of charge transfer resistance, R ct −1 . The surface roughness factor was deduced from impedance measurements. Electrocatalytic activity of two investigated Zr 100− y Ni y alloys, with y =33; and y =60 was directly related to the split-band electronic structure of Zr–Ni alloys. An enhanced electrocatalytic activity observed for the h.e.r. with increasing y in the Zr–Ni alloy was associated with a rapid increase of electronic density of states at Fermi energy level, D ( E F ) of the 3d Ni band with increasing Ni concentration. The formation of Ni-hydrides during hydrogen evolution was prevented and the high activity of the 3d Ni band for the h.e.r. was preserved. It was shown that alloying of Zr–Ni metallic glasses with varying individual component contents could be explored to optimize the electrocatalytic properties of Zr–Ni glasses and their use in water electrolysis, as electrode materials of long term stability. The highest catalytic activity could be expected for y =65, when a maximum hybridization of 3d–4d orbitals and a rapid decrease i.e. minimum density of 4d Zr states at the Fermi level were observed.

The hydrogen evolution reaction on pure and polypyrrole-coated GdNi4Al electrodes

Abstract Stability and electrocatalytic properties for the hydrogen evolution reaction (h.e.r.) were investigated on pure and polypyrrole (PPy)-coated GdNi 4 Al intermetallic alloy in 1 M NaOH electrolyte solution. In both cases, a surface film played an essential role in controlling this behavior. GdNi 4 Al was produced by arc melting of its pure components. Electronically conducting PPy film of 0.86 μm thickness was electrosynthesized on the alloy surface. A segregation phenomenon driven by preferential Gd oxidation, because of high reactivity of rare earths in contact with aqueous media, resulted in enrichment of the surface film with metallic Ni. The intermetallics high catalytic activity for h.e.r. was ascribed to formation of a continuous, electronically conducting net-like structure of nickel nanoparticles in the matrix of a barrier Gd 2 O 3 surface film, facilitated by the formation of interfacial Raney-type structure by leaching of Al in a basic solution, pH 14. In the narrow overpotential region, the PPy coating on the surface of the GdNi 4 Al electrode prevented the formation and growth of surface oxides and the loss of metallic conductivity, which, as a consequence, resulted in a smaller Tafel slope (Δ b c =−74 mV) and greater catalytic activity for h.e.r. At overpotentials higher than −0.12 V, the PPy layer did not protect the surface of the GdNi 4 Al electrode from mechanical decomposition, due to extensive hydrogen penetration in the bulk of the alloy. Structural characteristics of surface films formed on the GdNi 4 Al alloy as well as at the solid–liquid interface were investigated in situ using structural sensitive values of capacitance and resistance obtained by the complex nonlinear least-square (CNLS) method used in the fitting procedure of impedance spectra recorded in the frequency range 100 kHz–10 mHz.

Prediction of diesel fuel properties by vibrational spectroscopy using multivariate analysis

Partial least squares regression (PLS) calibration models based on Fourier transform infrared (FTIR-ATR) and Raman spectra (FT-Raman) were applied to the rapid and accurate simultaneous determination of the main properties of diesel fuels. Training sets were composed of over ninety commercial diesel fuel samples. The methods use baseline-uncorrected, raw FTIR-ATR and FT-Raman spectra. Two spectral regions were studied: full spectral region and “fingerprint” region. The models were validated using the cross-validation process. Based on the correlation coefficient and root mean square error of cross validation (RMSECV) values the both developed calibration models, PLS/FTIR-ATR and PLS/FT-Raman, were very accurate and comparable with standard testing methods. The following diesel fuel properties may be confidently estimated: cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, as well as the contents of total aromatics and polycyclic aromatic hydrocarbons. As compared to the “fingerprint” spectral region, the PLS/FTIR-ATR model using full spectral region displayed slightly better performances with the most of the correlation coefficient values above 0.98.

Thermal Stability of Lubricating Oil Additives Based on Styrene and n-Alkyl Methacrylate Terpolymers

In this work the thermal stability of polymeric additives for the improvement of rheological behavior of mineral lubricating oils was investigated. The systems studied comprised methyl methacrylate (MMA)/dodecyl methacrylate (DDMA)/octadecyl methacrylate (ODMA) and styrene (Sty)/DDMA/ODMA terpolymers. The composition of the terpolymers was determined by the 1H nuclear magnetic resonance spectroscopy and molar mass distribution by the size exclusion chromatography. The thermal degradation of terpolymers was studied by the thermogravimetric analysis. Sty/DDMA/ODMA terpolymers exhibited an improved thermal stability in comparison with MMA/DDMA/ODMA terpolymers of the corresponding compositions. Thus, the temperatures of 50% weight loss were found to be 313°C and 363°C for MMA terpolymer and Sty terpolymer, respectively, where x (MMA) = x (Sty) = 30 mol%.

Prediction of diesel fuel cold properties using artificial neural networks

In this paper, two neural networks, multilayer perceptron and networks with radial-basis function, were used to predict important cold properties of commercial diesel fuels, namely cloud point and cold filter plugging point. The developed models predict the named properties using cetane number, density, viscosity, contents of total aromatics, and distillation temperatures at 10, 50, and 90 vol. % recovery as input data. The training algorithms, number of hidden layer neurons, and number of training data points were optimized in order to obtain a model with optimal predictive ability. The results indicated better prediction of cloud and cold filter plugging points in the case of multilayer perceptron networks. The obtained absolute error mean for the optimal neural network models (0.58°C for the cloud point and 1.46°C for the cold filter plugging point) are within the range of repeatability of standard cold properties determination methods.

A Chromatographic Study of Shear Stability of Poly(styrene-co-alkyl methacrylate) Viscosity Modifier for Lubricating Oils

Shear stability of styrene, dodecyl methacrylate, and octadecyl methacrylate terpolymer of various molecular weights, as the rheology modifier of improved solubility, thermal and oxidation stability in mineral base oil, was investigated. Viscosity loss of the 5 wt% solutions caused by scission of macromolecules subjected to the high shear forces ranges between 15% and 27% for weight average molecular weights from 156000 to 252000. After the shear tests the number average molecular weights of polymer increases while weight and Z-average molecular weights decrease. As macromolecules of molecular weights above 700000 fully break the molar-mass dispersity decreases significantly, from starting at 2.34–2.79 down to below 1.8. A linear dependence between viscosity loss of terpolymer solutions and molecular weights was observed. The advantage of using the size exclusion chromatography to determine the stability of the polymer against mechanical shear directly and the viscosity loss indirectly was established.

Modeling of dibenzothiophene oxidative desulfurization using response surface methodology

ABSTRACT The effect of reaction temperature, mixing speed and oxidant to catalyst volume ratio, including their interactions on the oxidative desulfurization of dibenzothiophene by using response surface methodology was studied. Hydrogen peroxide was used as oxidant and acetic acid as catalyst. The obtained model accurately predicts conversion of dibenzothiophene and the best conversion of 98.7% was observed at temperature 70°C, mixing speed of 1250 rpm and oxidant to catalyst volume ratio of 1:1. At high temperatures, a major limitation of the desulfurization process is the mass transfer and the high mixing speed is needed to achieve an efficient process.

Crystallization and Pour Point of Solutions of the Dispersant Poly(Styrene-Co-Methacrylate) Viscosity Modifiers in Lubricating Base Oil

ABSTRACT Dispersant viscosity index improvers were synthesized by free radical copolymerization of N,N-dimethylaminoethyl methacrylate (DMAEMA), dodecyl methacrylate, octadecyl methacrylate, and styrene in solution of mineral base oil. Studies included the dependence of the pour point and low-temperature crystallization behavior (characteristic temperatures and enthalpies) of the solutions of these polymer viscosity modifiers (VMs) on the amount of dispersant comonomer, DMAEMA, in the copolymer, weight average molecular weight of the copolymer, and concentration of the polymer in oil. Incorporation of dispersant comonomer in poly(styrene-alkyl methacrylate) structure additionally decreases the pour point of its solutions even for a very small concentration: the pour point of the base oil reduces from −9 to −25°C and −33°C for the 0.1 and 0.5 wt% concentrations of polymer, respectively. For concentrated 50 wt% solutions the enthalpy of crystallization decreases linearly with a decrease in the long-chain alkyl methacrylate share in copolymer. There is no unambiguous correlation between the pour point and crystallization parameters of semidiluted and diluted polymer solutions obtained by differential scanning calorimetry.

Dynamic Simulation of Batch Polymerization Reactor and Sensitivity Analysis of Styrene Homopolymerization

Od sedamdesetih godina 20. stoljeća, kada se polimerno reakcijsko inženjerstvo počelo razvijati kao znanstvena disciplina, i matematičko modeliranje polimerizacijskih reaktora postalo je vrlo detaljno i opsežno.1,2 Za razvoj prikladnog matematičkog modela nužno je poznavanje kinetike i reakcijskog mehanizma kojim se odvija proces polimerizacije, zatim konfiguracije polimernog reaktora i radnih uvjeta kako bi se predvidio njihov utjecaj na građu sintetiziranih makromolekula (na primjer, raspodjelu molekulskih masa, stupanj cijepljenja i drugo) kao i morfologiju polimernog proizvoda (na primjer, raspodjelu veličine čestica, poroznost i drugo). Kod polimerizacijskih procesa kvaliteta proizvoda vrlo je kompleksno pitanje jer o strukturnim i morfološkim karakteristikama polimera ovise njihova fizikalna, kemijska, toplinska, reološka i mehanička svojstva, pa tako i krajnja primjena. U današnje vrijeme računalni programi za simulaciju (engl. Computer-Aided Design, CAD) rada polimerizacijskih reaktora smatraju se jednim od vrlo uspješnih alata koji znatno pridonose razvoju procesnih tehnologija kao i proizvodnji polimera.2,3 To uključuje projektiranje procesa, optimizaciju, procjenu parametara stanja i vođenje procesa. Stabilnost i vođenje rada polimerizacijskih reaktora mogu se preliminarno ispitati i provjeriti prije izgradnje postrojenja upotrebom dinamičkih reaktorskih modela. Takvi modeli mogu identificirati potencijalne izvore koji uzrokuju varijacije u kvaliteti proizvoda te ih svesti na najmanju mjeru, a bitni su i za razvoj odgovarajuće računalne podrške pri vođenju takvih procesa.4–7 Najznačajniju ulogu u razvoju polimerizacijskih procesa i proizvoda imaju procesni inženjeri jer njihovo dugogodišnje iskustvo i znanje o procesu kao i o modeliranju i programiranju znatno pridonosi stvaranju visokokvalitetnih proizvoda. Do danas je razvijeno nekoliko komercijalnih programskih paketa za simuliranje raznih polimerizacijskih procesa, a prvi takav bio je POLYRED, razvijen na sveučilištu Wisconsin.3

Novi petrokemijski procesi na temelju izravne pretvorbe metana

Petrokemija je grana kemije i kemijskog inženjerstva koja proucava reakcije i procese dobivanja i svojstva proizvoda iz naftnih prerađevina i prirodnoga plina, a koji ne služe kao goriva ili maziva. U svojim pocetcima petrokemija, odnosno organska kemijska industrija, temeljila se na etinu i Reppeovim sintezama. Danas su osnovne petrokemikalije olefini i aromatski ugljikovodici, s težnjom razvoja novih procesa i sve vece uporabe sinteznog plina, metana i drugih alkana kao ishodnih sirovinskih komponenti. U ovom radu dan je pregled reakcija i novih procesa izravne pretvorbe metana u vrjednije petrokemijske proizvode. Kroz pojedina poglavlja u radu su detaljnije opisane reakcije parcijalne oksidacije metana, dehidroaromatizacije metana te oksidacijskog i neoksidacijskog spajanja metana u vise ugljikovodike.