Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Differential Evolution approach and parameter estimation of chaotic

Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.

Recovery of carboxylic acids from aqueous streams by extraction and back extraction

Separation of carboxylic acids from aqueous streams is an important part of their manufacturing process. The aqueous solutions are usually dilute containing less than 10 % acids. Separation by distillation is difficult as the boiling points of acids are only marginally higher than that of water. Because of this distillation is not only difficult but also expensive due to the evaporation of large amounts of water. Carboxylic acids have traditionally been precipitated as calcium salts. The yields of these processes are usually relatively low and the chemical costs high. Especially the decomposition of calcium salts with sulfuric acid produces large amounts of calcium sulfate sludge. Solvent extraction has been studied as an alternative method for recovery of carboxylic acids. Solvent extraction is based on mixing of two immiscible liquids and the transfer of the wanted components form one liquid to another due to equilibrium difference. In the case of carboxylic acids, the acids are transferred from aqueous phase to organic solvent due to physical and chemical interactions. The acids and the extractant form complexes which are soluble in the organic phase. The extraction efficiency is affected by many factors, for instance initial acid concentration, type and concentration of the extractant, pH, temperature and extraction time. In this paper, the effects of initial acid concentration, type of extractant and temperature on extraction efficiency were studied. As carboxylic acids are usually the products of the processes, they are wanted to be recovered. Hence the acids have to be removed from the organic phase after the extraction. The removal of acids from the organic phase also regenerates the extractant which can be then recycled in the process. The regeneration of the extractant was studied by back-extracting i.e. stripping the acids form the organic solution into diluent sodium hydroxide solution. In the solvent regeneration, the regenerability of different extractants and the effect of initial acid concentration and temperature were studied.

Extraction of polymeric galactoglucomannans from spruce wood by pressurized hot water

The major type of non-cellulosic polysaccharides (hemicelluloses) in softwoods, the partly acetylated galactoglucomannans (GGMs), which comprise about 15% of spruce wood, have attracted growing interest because of their potential to become high-value products with applications in many areas. The main objective of this work was to explore the possibilities to extract galactoglucomannans in native, polymeric form in high yield from spruce wood with pressurised hot-water, and to obtain a deeper understanding of the process chemistry involved. Spruce (Picea abies) chips and ground wood particles were extracted using an accelerated solvent extractor (ASE) in the temperature range 160 – 180°C. Detailed chemical analyses were done on both the water extracts and the wood residues. As much as 80 – 90% of the GGMs in spruce wood, i.e. about 13% based on the original wood, could be extracted from ground spruce wood with pure water at 170 – 180°C with an extraction time of 60 min. GGMs comprised about 75% of the extracted carbohydrates and about 60% of the total dissolved solids. Other substances in the water extracts were xylans, arabinogalactans, pectins, lignin and acetic acid. The yields from chips were only about 60% of that from ground wood. Both the GGMs and other non-cellulosic polysaccharides were extensively hydrolysed at severe extraction conditions when pH dropped to the level of 3.5. Addition of sodium bicarbonate increased the yields of polymeric GGMs at low additions, 2.5 – 5 mM, where the end pH remained around 3.9. However, at higher addition levels the yields decreased, mainly because the acetyl groups in GGMs were split off, leading to a low solubility of GGMs. Extraction with buffered water in the pH range 3.8 – 4.4 gave similar yields as with plain water, but gave a higher yield of polymeric GGMs. Moreover, at these pH levels the hydrolysis of acetyl groups in GGMs was significantly inhibited. It was concluded that hot-water extraction of polymeric GGMs in good yields (up to 8% of wood) demands appropriate control of pH, in a narrow range about 4. These results were supported by a study of hydrolysis of GGM at constant pH in the range of 3.8 – 4.2 where a kinetic model for degradation of GGM was developed. The influence of wood particle size on hot-water extraction was studied with particles in the range of 0.1 – 2 mm. The smallest particles (< 0.1 mm) gave 20 – 40% higher total yield than the coarsest particles (1.25 – 2 mm). The difference was greatest at short extraction times. The results indicated that extraction of GGMs and other polysaccharides is limited mainly by the mass transfer in the fibre wall, and for coarse wood particles also in the wood matrix. Spruce sapwood, heartwood and thermomechnical pulp were also compared, but only small differences in yields and composition of extracts were found. Two methods for isolation and purification of polymeric GGMs, i.e. membrane filtration and precipitation in ethanol-water, were compared. Filtration through a series of membranes with different pore sizes separated GGMs of different molar masses, from polymers to oligomers. Polysaccharides with molar mass higher than 4 kDa were precipitated in ethanol-water. GGMs comprised about 80% of the precipitated polysaccharides. Other polysaccharides were mainly arabinoglucuronoxylans and pectins. The ethanol-precipitated GGMs were by 13C NMR spectroscopy verified to be very similar to GGMs extracted from spruce wood in low yield at a much lower temperature, 90°C. The obtained large body of experimental data could be utilised for further kinetic and economic calculations to optimise technical hot-water extractionof softwoods.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Pressurized hot water flow-through extraction of birch wood

Effective processes to fractionate the main compounds in biomass, such as wood, are a prerequisite for an effective biorefinery. Water is environmentally friendly and widely used in industry, which makes it a potential solvent also for forest biomass. At elevated temperatures over 100 °C, water can readily hydrolyse and dissolve hemicelluloses from biomass. In this work, birch sawdust was extracted using pressurized hot water (PHWE) flow-through systems. The hypothesis of the work was that it is possible to obtain polymeric, water-soluble hemicelluloses from birch sawdust using flow-through PHW extractions at both laboratory and large scale. Different extraction temperatures in the range 140–200 °C were evaluated to see the effect of temperature to the xylan yield. The yields and extracted hemicelluloses were analysed to obtain sugar ratios, the amount of acetyl groups, furfurals and the xylan yields. Higher extraction temperatures increased the xylan yield, but decreased the molar mass of the dissolved xylan. As the extraction temperature increased, more acetic acid was released from the hemicelluloses, thus further decreasing the pH of the extract. There were only trace amounts of furfurals present after the extractions, indicating that the treatment was mild enough not to degrade the sugars further. The sawdust extraction density was increased by packing more sawdust in the laboratory scale extraction vessel. The aim was to obtain extracts with higher concentration than in typical extraction densities. The extraction times and water flow rates were kept constant during these extractions. The higher sawdust packing degree decreased the water use in the extractions and the extracts had higher hemicellulose concentrations than extractions with lower sawdust degrees of packing. The molar masses of the hemicelluloses were similar in higher packing degrees and in the degrees of packing that were used in typical PHWE flow-through extractions. The structure of extracted sawdust was investigated using small angle-(SAXS) and wide angle (WAXS) x-ray scattering. The cell wall topography of birch sawdust and extracted sawdust was compared using x-ray tomography. The results showed that the structure of the cell walls of extracted birch sawdust was preserved but the cell walls were thinner after the extractions. Larger pores were opened inside the fibres and cellulose microfibrils were more tightly packed after the extraction. Acetate buffers were used to control the pH of the extracts during the extractions. The pH control prevented excessive xylan hydrolysis and increased the molar masses of the extracted xylans. The yields of buffered extractions were lower than for plain water extractions at 160–170 °C, but at 180 °C yields were similar to those from plain water and pH buffers. The pH can thus be controlled during extraction with acetate buffer to obtain xylan with higher molar mass than those obtainable using plain water. Birch sawdust was extracted both in the laboratory and pilot scale. The performance of the PHWE flow-through system was evaluated in the laboratory and the pilot scale using vessels with the same shape but different volumes, with the same relative water flow through the sawdust bed, and in the same extraction temperature. Pre-steaming improved the extraction efficiency and the water flow through the sawdust bed. The extracted birch sawdust and the extracted xylan were similar in both laboratory and pilot scale. The PHWE system was successfully scaled up by a factor of 6000 from the laboratory to pilot scale and extractions performed equally well in both scales. The results show that a flow-through system can be further scaled up and used to extract water-soluble xylans from birch sawdust. Extracted xylans can be concentrated, purified, and then used in e.g. films and barriers, or as building blocks for novel material applications.

Intensification of hemicellulose hot-water extraction from spruce wood by parameter tuning

The growing population on earth along with diminishing fossil deposits and the climate change debate calls out for a better utilization of renewable, bio-based materials. In a biorefinery perspective, the renewable biomass is converted into many different products such as fuels, chemicals, and materials, quite similar to the petroleum refinery industry. Since forests cover about one third of the land surface on earth, ligno-cellulosic biomass is the most abundant renewable resource available. The natural first step in a biorefinery is separation and isolation of the different compounds the biomass is comprised of. The major components in wood are cellulose, hemicellulose, and lignin, all of which can be made into various end-products. Today, focus normally lies on utilizing only one component, e.g., the cellulose in the Kraft pulping process. It would be highly desirable to utilize all the different compounds, both from an economical and environmental point of view. The separation process should therefore be optimized. Hemicelluloses can partly be extracted with hot-water prior to pulping. Depending in the severity of the extraction, the hemicelluloses are degraded to various degrees. In order to be able to choose from a variety of different end-products, the hemicelluloses should be as intact as possible after the extraction. The main focus of this work has been on preserving the hemicellulose molar mass throughout the extraction at a high yield by actively controlling the extraction pH at the high temperatures used. Since it has not been possible to measure pH during an extraction due to the high temperatures, the extraction pH has remained a “black box”. Therefore, a high-temperature in-line pH measuring system was developed, validated, and tested for hot-water wood extractions. One crucial step in the measurements is calibration, therefore extensive efforts was put on developing a reliable calibration procedure. Initial extractions with wood showed that the actual extraction pH was ~0.35 pH units higher than previously believed. The measuring system was also equipped with a controller connected to a pump. With this addition it was possible to control the extraction to any desired pH set point. When the pH dropped below the set point, the controller started pumping in alkali and by that the desired set point was maintained very accurately. Analyses of the extracted hemicelluloses showed that less hemicelluloses were extracted at higher pH but with a higher molar-mass. Monomer formation could, at a certain pH level, be completely inhibited. Increasing the temperature, but maintaining a specific pH set point, would speed up the extraction without degrading the molar-mass of the hemicelluloses and thereby intensifying the extraction. The diffusion of the dissolved hemicelluloses from the wood particle is a major part of the extraction process. Therefore, a particle size study ranging from 0.5 mm wood particles to industrial size wood chips was conducted to investigate the internal mass transfer of the hemicelluloses. Unsurprisingly, it showed that hemicelluloses were extracted faster from smaller wood particles than larger although it did not seem to have a substantial effect on the average molar mass of the extracted hemicelluloses. However, smaller particle sizes require more energy to manufacture and thus increases the economic cost. Since bark comprises 10 – 15 % of a tree, it is important to also consider it in a biorefinery concept. Spruce inner and outer bark was hot-water extracted separately to investigate the possibility to isolate the bark hemicelluloses. It was showed that the bark hemicelluloses comprised mostly of pectic material and differed considerably from the wood hemicelluloses. The bark hemicelluloses, or pectins, could be extracted at lower temperatures than the wood hemicelluloses. A chemical characterization, done separately on inner and outer bark, showed that inner bark contained over 10 % stilbene glucosides that could be extracted already at 100 °C with aqueous acetone.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Continuous Counter-current Solvent Extraction of Magnesium and Calcium from Lithium-rich Brine

Solvent extraction of calcium and magnesium impurities from a lithium-rich brine (Ca ~ 2,000 ppm, Mg ~ 50 ppm, Li ~ 30,000 ppm) was investigated using a continuous counter-current solvent extraction mixer-settler set-up. The literature review includes a general review about resources, demands and production methods of Li followed by basics of solvent extraction. Experimental section includes batch experiments for investigation of pH isotherms of three extractants; D2EHPA, Versatic 10 and LIX 984 with concentrations of 0.52, 0.53 and 0.50 M in kerosene respectively. Based on pH isotherms LIX 984 showed no affinity for solvent extraction of Mg and Ca at pH ≤ 8 while D2EHPA and Versatic 10 were effective in extraction of Ca and Mg. Based on constructed pH isotherms, loading isotherms of D2EHPA (at pH 3.5 and 3.9) and Versatic 10 (at pH 7 and 8) were further investigated. Furthermore based on McCabe-Thiele method, two extraction stages and one stripping stage (using HCl acid with concentration of 2 M for Versatic 10 and 3 M for D2EHPA) was practiced in continuous runs. Merits of Versatic 10 in comparison to D2EHPA are higher selectivity for Ca and Mg, faster phase disengagement, no detrimental change in viscosity due to shear amount of metal extraction and lower acidity in stripping. On the other hand D2EHPA has less aqueous solubility and is capable of removing Mg and Ca simultaneously even at higher Ca loading (A/O in continuous runs > 1). In general, shorter residence time (~ 2 min), lower temperature (~23 °C), lower pH values (6.5-7.0 for Versatic 10 and 3.5-3.7 for D2EHPA) and a moderately low A/O value (< 1:1) would cause removal of 100% of Ca and nearly 100% of Mg while keeping Li loss less than 4%, much lower than the conventional precipitation in which 20% of Li is lost.

Excavation-drier method of energy-peat extraction reduces long-term climatic impact

Climatic impacts of energy-peat extraction are of increasing concern due to EU emissions trading requirements. A new excavation-drier peat extraction method has been developed to reduce the climatic impact and increase the efficiency of peat extraction. To quantify and compare the soil GHG fluxes of the excavation drier and the traditional milling methods, as well as the areas from which the energy peat is planned to be extracted in the future (extraction reserve area types), soil CO2, CH4 and N2O fluxes were measured during 2006–2007 at three sites in Finland. Within each site, fluxes were measured from drained extraction reserve areas, extraction fields and stockpiles of both methods and additionally from the biomass driers of the excavation-drier method. The Life Cycle Assessment (LCA), described at a principal level in ISO Standards 14040:2006 and 14044:2006, was used to assess the long-term (100 years) climatic impact from peatland utilisation with respect to land use and energy production chains where utilisation of coal was replaced with peat. Coal was used as a reference since in many cases peat and coal can replace each other in same power plants. According to this study, the peat extraction method used was of lesser significance than the extraction reserve area type in regards to the climatic impact. However, the excavation-drier method seems to cause a slightly reduced climatic impact as compared with the prevailing milling method.

Recovery and purification of anthocyanins from purple-blue potato

The aim of this work was to study techniques to extract and purify of anthocyanins from purple-blue potato. This topic was determined as a master’s thesis and it was done in collaboration with the Food Chemistry and Food Development Department of University of Turku and Department of Chemical and Process Engineering at Lappeenranta University of Technology. At first, purple-blue potatoes were pretreated in four types of boiled, raw, freeze-dried and dried boiled potato for extraction. They were mixed with aqueous acidified ethanol (ethanol:water:acetic acid 40%:53%:7% v/v) for conventional extraction. Boiled potato was selected as a best pretreated potato. Different ethanol concentration and extraction time were examined and the mixture of 80% in 24 h resulted in maximum anthocyanin content (132.23 mg/L). As conventional extraction method of anthocyanins was non-selective, some of impurities such as free sugars might accelerate anthocyanin degradation. Therefore, to obtain anthocyanins in purified form, adsorption as a promising selective method was used to recovery and isolate anthocyanins. It was carried out with six adsorbents. Among those, Amberlite XAD-7HP, a nonionic acrylic ester adsorbent, was found to have the best performance. In an adsorption column, flow rate of 3 mL/min was selected as the loading flow rate among four tested flow rates. Eluent volume and flow rate were 3 BV of aqueous acidified ethanol (75%, v/v) and 1 mL/min for desorption. The quantification of the total anthocyanin contents was performed by pH-differential method using UV-vis spectrophotometer. The resulting anthocyanin solution after purification was almost free from free sugars which were the major cause for degradation of anthocyanins. The average anthocyanin concentration in the purified and concentrated sample was obtained 1752.89 mg/L.

Utilizing hemicelluloses – the first step : controlled extraction with hot water

Människor utnyttjar ofta kemi mångsidigt i sitt vardagliga liv utan att närmare tänka på detaljerna. Nuförtiden kan man framställa en ökande mängd av produkter ur förnybara råmaterial och en av de mest mångsidiga nybara råmaterialet i Norden är barrträd. Den lyriska lägerelden eller spiselden och möbler av ved samt papper är en väsentlig del av vardagen. Också livsmedel och läkemedel kan innehålla föreningar ur ved. Ved som råmaterial består av tre huvudkomponenten: cellulosa, som är uppbyggd av druvsockermolekyler är en långkedjad, oförgrenad polymer; lignin, som sammanhåller fibrerna i vedmaterialet som lim samt hemicellulosor, som ofta är uppbyggda av olika sockerarter och är en förgrenad polymer. Följaktligen består vedmaterialet av 70 % socker. I detta arbete har vi koncentrerat på i hemicellulosa och dess extraktion ur gran, samt bestämning av hemicellulosans egenskaper. Den slutliga målsättningen i forskningen var att skapa nya produkter ur gran. Forskning i extraktionens hemligheter eller hur hemicellulosa kan effektivt extraheras i den önskade formen kräver nya typers experimentellasanläggningar och experiment samt matematisk modellering. Den långkedjade hemicellulosan är lämplig för att användas t.ex. i skyddshinnor eller i livsmedel. Medel- och småmolekylär hemicellulosa kan användas som utgångsämne för framställning av bränslen, smörjmedel, sockersyror och alkoholer, av vilka xylitol är mest känd för alla pga hälsobefrämjande effekter. Det är utomordentligt viktigt ur miljöns och energiekonomins synvinkel att sträva efter effektivering av utnyttjandet av den värdefullaste och största naturtillgången, skogen i vårt land, med alla möjliga sätt. Resultaten av denna forskning utnyttjar avsevärt den växande, nya, på skogen baserande biobaseradeindustrin, som framställer nya spetsprodukter samt skapar nya arbetsplatser. ----------------------------------------------------- Ihmiset hyödyntävät usein huomaamattaan kemiaa monipuolisesti jokapäiväisessä elämässä. Nykyään kasvava määrä tuotteista kyetään valmistamaan uusiutuvista raaka-aineista ja yksi monipuolisimmista uusiutuvista luonnonvaroistamme pohjolassa ovat havupuut. Tunnelmallinen nuotio tai takkatuli ja puiset huonekalut sekä paperi ovat olennainen osa arkea. Myös elintarvikkeet ja lääkkeet voivat sisältää puusta peräisin olevia yhdisteitä. Puu materiaalina koostuu rakenteeltaan pääosin kolmesta osasta; selluloosasta, joka on rypälesokerista koostuva pitkäketjuinen haaroittumaton polymeeri, ligniinistä, joka toimii puun koossa pitävänä liima-aineena ja hemiselluloosasta, joka on useista eri sokereista rakentunut haaroittunut polymeeri. Näin ollen puusta 70 % on sokeria. Tässä työssä olemme keskittyneet hemiselluloosaan ja sen uuttamiseen kuusesta, sekä ominaisuuksien kartoittamiseen. Tutkimusaiheen lopullinen tavoite on luoda uusia tuotteita kuusesta. Uuton salojen tutkiminen eli miten hemiselluloosa saadaan tehokkaasti uutettua halutunlaisena vaatii uudenlaisia koelaitteistoja ja kokeita, sekä matemaattista mallintamista. Suurikokoinen hemiselluloosa on sopivaa käytettäväksi esimerkiksi suojakalvoissa tai elintarvikkeissa. Keskikokoista ja pienimolekyylistä hemiselluloosaa voidaan käyttää lähtöaineena valmistettaessa polttoaineita, voiteluaineita, sokerihappoja ja sokerialkoholeja, joista xylitoli on terveysvaikutustensa vuoksi kaikille tuttu. Niin ympäristömme kuin myös energiataloutemme kannalta on ensiarvoisen tärkeää pyrkiä kaikin keinoin tehostamaan maallemme arvokkaan, sekä luonnonvaroistamme yhden suurimman, metsän, vastuullista hyödyntämistä. Tämän tutkimuksen tulokset hyödyntävät merkittävästi maahamme nousevaa uutta metsään pohjautuvaa biojalostusteollisuutta, joka valmistaa uusia huipputuotteita sekä luo työpaikkoja.