Subkritična voda kot zelen medij za ekstrakcijo in procesiranje naravnih materialov

In this doctoral dissertation, the application of subcritical water as a green medium for the extraction and processing of natural materials is presented. The work is divided into three main parts. In the first part, subcritical water is proposed as a solvent for the simultaneous extraction of oil- and water-soluble phase from oily seeds. The extraction parameters, such as temperature, time and material to solvent ratio that yield the highest amounts of both phases are examined. The quality of both obtained phases is examined. The characteristics of oils obtained using subcritical water is compared to that obtained using a conventional method. The second part of this work proposes subcritical water as an efficient solvent for the isolation of bioactive phenolic compounds from wood waste, that is produced by the forestry industry. Different wood fractions are firstly extracted in batch-mode and the fraction with the highest amounts of bioactive compounds is determined. Next, semi-continuous operation is applied, where the effects of different extraction parameters are studied on the extraction yield and quality of the extract. The effect of temperature and ethanol addition to the subcritical water on the content of single phenolic compounds identified in the extracts is observed. Lastly, the cost of manufacturing of such a product is estimated by evaluating the economics of different pilot- and industrial-scale processes operating at optimal conditions determined on the laboratory scale. The last part proposes the use of subcritical water as an efficient hydrolytic medium for glycoside bonded antioxidants, specifically those found in waste agro-industrial sources. Effect of temperature, treatment time, concentration and the atmosphere used for establishing the pressure in the reactor are first studied on a model glycoside compound - rutin and the optimal combination of reaction parameters are established for the batch-mode reactor. The degradation products of the model compound are identified and the concentration/time profiles of their degradation are observed. Furthermore, the reaction kinetics explaining the degradation of the rutin standard are evaluated. In the next step, the method is implemented on a real glycosides-containing extract. The extract is hydrolyzed at conditions obtained from the first step and the free aglycone is obtained at the highest yields possible. Lastly, the process is upgraded to continuous operation and the final hydrolyzed high-purity product is recovered.Glavni namen te doktorske disertacije je bilo raziskati uporabnost subkritične vode kot zelenega medija za izolacijo in procesiranje naravnih materialov. Delo sestoji iz treh delov. Prvi del se osredotoča na uporabnost subkritične vode kot topila za sočasno ekstrakcijo v olju in vodi topne faze iz oljnih semen. V ta namen smo študirali ekstrakcijske parametre, torej vpliv temperature, časa in razmerja material/topilo na izkoristek obeh faz. Kvaliteto obeh faz smo preverili. Kvaliteto olj pridobljenih s subkritično vodo smo primerjali z oljem pridobljenim s konvencionalno metodo. Drugi del te disertacije predlaga subkritično vodo kot efektivno topilo za izolacijo bioaktivnih fenolnih spojin iz odpadnega lesa. V prvem koraku smo ekstrahirali različne frakcije odpadnega lesa, ki nastanejo pri spravljenju lesa v gozdovih z uporabo šaržnega sistema, z namenom najti najprimernejšo frakcijo za izolacijo. V drugem koraku smo uporabili semi-kontinuirni ekstrakcijski postopek, kjer smo študirali vpliv ekstrakcijskih parametrov na ekstrakcijski izkoristek in kvaliteto ekstrakta. Določili smo vpliv temperature in dodatka etanola na hidrotemično degradacijo fenolnih spojin med samo ekstrakcijo. Na koncu smo ocenili še ekonomičnost pilotnih in industrijskih procesov z različnimi kapacitetami ekstraktorja, z namenom, približno ovrednotiti cene proizvodnje takšnega produkta. Zadnji del te doktorske disertacije predlaga subkritično vodo kot efektiven reakcijski medij za hidrolizo glikozidno vezanih antioksidantov najdenih v odpadkih živilskopridelovalne industrije. Preučili smo vpliv temperature, časa, koncentracije in atmosfere uporabljene za vzpostavitev tlaka v šaržnem reaktorju na potek hidrolize ter določili optimalno kombinacijo le-teh za modelni glikozid - rutin. Določili smo produkte hidroterminčnega razpada rutina ter degradacijske profile le-te v odvisnosti od časa. Poleg tega, smo razvili tudi kinetični model, ki matematično opisuje razgradnjo rutina v kvercetin. V naslednjem koraku smo metodo implementirali na realnem ekstraktu, ki vsebuje podobne glikozide kakor modelna komponenta in skušali dobiti proste aglikone v največjem možnem izkoristku. Na koncu smo izvedli hidrolizo tudi s kontinuirnim postopkom in skušali dobiti končni hidrolizirani produkt visoke čistosti

MONOESTERIFICATION OF ETHYLENE GLYCOL: DETERMINATION OF MECHANISM AND RATE OF REACTION

Cilj diplomskega dela je bil razviti kinetični model in mehanizem monoesterifikacije, tipične reverzibilne reakcije. Kot primer smo uporabili monoesterifikacijo etilen glikola z benzojsko kislino. Reakcija je bila katalizirana v kislem mediju ob prisotnosti α-aluminijevega oksida. Vsi eksperimenti so bili izvedeni v avtomatiziranem reakcijskem kalorimetru, opremljenim z in-line IR spektrometrom. Na osnovi IR spektrov in metodologije umeritvene krivulje smo dobili koncentracijske profile produkta. Določili smo red reakcije, obe konstanti proizvodnosti in aktivacijsko energijo. Z uporabo kinetičnih in stehiometričnih podatkov smo ugotovili reakcijski mehanizem, ki pojasnjuje opažene značilnosti reakcije.The goal of this work was to develop the kinetic model and mechanism of monoesterification, a typical reversible reaction. As an example we used the ethylene glycol monoesterification with benzoic acid. The reaction was catalyzed in acidic medium supported with α-aluminum oxide. All experiments were carried out in an automated reaction calorimeter equipped with an in-line IR spectrometer. Based on the observed IR spectra and calibration curve methodology, product concentration profiles were obtained. Reaction order together with both reaction rate constants and activation energy have been determined. Using the obtained kinetic and stoichiometric data, the reaction mechanism was established which explains the observed reaction characteristics

Tuning Multi-Objective Evolutionary Algorithms on Different Sized Problem Sets

Multi-Objective Evolutionary Algorithms (MOEAs) have been applied successfully for solving real-world multi-objective problems. Their success can depend highly on the configuration of their control parameters. Different tuning methods have been proposed in order to solve this problem. Tuning can be performed on a set of problem instances in order to obtain robust control parameters. However, for real-world problems, the set of problem instances at our disposal usually are not very plentiful. This raises the question: What is a sufficient number of problems used in the tuning process to obtain robust enough parameters? To answer this question, a novel method called MOCRS-Tuning was applied on different sized problem sets for the real-world integration and test order problem. The configurations obtained by the tuning process were compared on all the used problem instances. The results show that tuning greatly improves the algorithms’ performance and that a bigger subset used for tuning does not guarantee better results. This indicates that it is possible to obtain robust control parameters with a small subset of problem instances, which also substantially reduces the time required for tuning

From Grammar Inference to Semantic Inference—An Evolutionary Approach

This paper describes a research work on Semantic Inference, which can be regarded as an extension of Grammar Inference. The main task of Grammar Inference is to induce a grammatical structure from a set of positive samples (programs), which can sometimes also be accompanied by a set of negative samples. Successfully applying Grammar Inference can result only in identifying the correct syntax of a language. With the Semantic Inference a further step is realised, namely, towards inducing language semantics. When syntax and semantics can be inferred, a complete compiler/interpreter can be generated solely from samples. In this work Evolutionary Computation was employed to explore and exploit the enormous search space that appears in Semantic Inference. For the purpose of this research work the tool LISA.SI has been developed on the top of the compiler/interpreter generator tool LISA. The first results are encouraging, since we were able to infer the semantics only from samples and their associated meanings for several simple languages, including the Robot language

Long Term Memory Assistance for Evolutionary Algorithms

Short term memory that records the current population has been an inherent component of Evolutionary Algorithms (EAs). As hardware technologies advance currently, inexpensive memory with massive capacities could become a performance boost to EAs. This paper introduces a Long Term Memory Assistance (LTMA) that records the entire search history of an evolutionary process. With LTMA, individuals already visited (i.e., duplicate solutions) do not need to be re-evaluated, and thus, resources originally designated to fitness evaluations could be reallocated to continue search space exploration or exploitation. Three sets of experiments were conducted to prove the superiority of LTMA. In the first experiment, it was shown that LTMA recorded at least 50 % more duplicate individuals than a short term memory. In the second experiment, ABC and jDElscop were applied to the CEC-2015 benchmark functions. By avoiding fitness re-evaluation, LTMA improved execution time of the most time consuming problems F 03 and F 05 between 7% and 28% and 7% and 16%, respectively. In the third experiment, a hard real-world problem for determining soil models’ parameters, LTMA improved execution time between 26% and 69%. Finally, LTMA was implemented under a generalized and extendable open source system, called EARS. Any EA researcher could apply LTMA to a variety of optimization problems and evolutionary algorithms, either existing or new ones, in a uniform way

A Graph Pointer Network-Based Multi-Objective Deep Reinforcement Learning Algorithm for Solving the Traveling Salesman Problem

Traveling Salesman Problems (TSPs) have been a long-lasting interesting challenge to researchers in different areas. The difficulty of such problems scales up further when multiple objectives are considered concurrently. Plenty of work in evolutionary algorithms has been introduced to solve multi-objective TSPs with promising results, and the work in deep learning and reinforcement learning has been surging. This paper introduces a multi-objective deep graph pointer network-based reinforcement learning (MODGRL) algorithm for multi-objective TSPs. The MODGRL improves an earlier multi-objective deep reinforcement learning algorithm, called DRL-MOA, by utilizing a graph pointer network to learn the graphical structures of TSPs. Such improvements allow MODGRL to be trained on a small-scale TSP, but can find optimal solutions for large scale TSPs. NSGA-II, MOEA/D and SPEA2 are selected to compare with MODGRL and DRL-MOA. Hypervolume, spread and coverage over Pareto front (CPF) quality indicators were selected to assess the algorithms’ performance. In terms of the hypervolume indicator that represents the convergence and diversity of Pareto-frontiers, MODGRL outperformed all the competitors on the three well-known benchmark problems. Such findings proved that MODGRL, with the improved graph pointer network, indeed performed better, measured by the hypervolume indicator, than DRL-MOA and the three other evolutionary algorithms. MODGRL and DRL-MOA were comparable in the leading group, measured by the spread indicator. Although MODGRL performed better than DRL-MOA, both of them were just average regarding the evenness and diversity measured by the CPF indicator. Such findings remind that different performance indicators measure Pareto-frontiers from different perspectives. Choosing a well-accepted and suitable performance indicator to one’s experimental design is very critical, and may affect the conclusions. Three evolutionary algorithms were also experimented on with extra iterations, to validate whether extra iterations affected the performance. The results show that NSGA-II and SPEA2 were greatly improved measured by the Spread and CPF indicators. Such findings raise fairness concerns on algorithm comparisons using different fixed stopping criteria for different algorithms, which appeared in the DRL-MOA work and many others. Through these lessons, we concluded that MODGRL indeed performed better than DRL-MOA in terms of hypervolumne, and we also urge researchers on fair experimental designs and comparisons, in order to derive scientifically sound conclusions

Hydrothermal Degradation of Rutin: Identification of Degradation Products and Kinetics Study

The model glycoside compound quercetin-3-<i>O</i>-rutinoside (rutin) was subjected to subcritical water within the temperature range of 120–220 °C, and the hydrothermal degradation products were analyzed. Two kinetic models describing the degradation of this compound in two different atmospheres (N₂ and CO₂), used for pressure establishment in the reactor, have been developed and compared. Reaction was considered a successive one with three irreversible steps. We confirmed that rutin degradation to quercetin follows first-order kinetics. At higher temperatures quercetin is further degraded in two degradation steps. Formations of 3,4-dihydroxybenzoic acid and catechol were described with the zero-order kinetic models. Reaction rate constants for hydrolysis of glycoside to aglycone in a CO₂ atmosphere are higher compared to those in a N₂ atmosphere, whereas at higher temperatures reaction rate constants for further two successive reactions of aglycone degradation are slightly lower in the presence of CO₂. The difference in reaction activation energies is practically negligible for both gases. Furthermore, degradation products of sugar moieties, that is, 5-hydroxymethylfurfural and 5-methylfurfural, were also detected and analyzed