Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

Functional models for iron(II)/α-keto acid dependent enzymes

Iron and iron enzymes are ubiquitous in nature. Besides heme-type enzymes, to which the well-known cytochrome P450 belongs, the superfamily of iron(II)/α-keto acid dependent enzymes is of utmost biological relevance. Enzymes of this class are involved in a number of important biochemical transformations including the synthesis of penicillin, the metabolism of taurine, DNA repair, or epigenetically relevant demethylation of DNA. The mechanism of action of these enzymes has been the focus of scientific investigations since 1982,[1] however, details of specific enzymatic transformations still remain elusive. In the years 2003-2005 a series of bioinorganic investigations, in part using synthetic model complexes, led to the discovery of an iron(IV)-oxido moiety as the active species in the enzymes’ catalytic cycle.[2–6] In 2009 ten-eleven translocation 5-methyl cytosine dioxygenase (TET) enzymes, members of the iron(II)/α-keto acid dependent enzyme superfamily, were discovered to play an integral part in the molecular processes of epigenetics by oxidizing the methyl group on the important epigenetic marker 5-methyl cytosine (5mC).[7] Whereas several biochemical investigations gave insight into the reactivity of TET enzymes, details are still unclear that warrant more thorough studies. For example, the reactivity of TET towards 5mC and its oxidized metabolites 5-hydroxymethyl cytosine (5hmC) and 5-formyl cytosine (5fC) unexpectedly does not correspond to the trend observed in the theoretically calculated bond dissociation energies (BDEs) of these substrates.[8] On another note, a defect in the gene coding for another iron(II)/α-keto acid dependent enzyme (4 hydroxyphenylpyruvate dioxygenase like, HPDL) was recently identified as the main cause for a neurodegenerative disorder.[9–11] Sequence, location, and some of the enzyme’s biochemical behavior including its substrate have been identified. However, there is reason to believe that not all intermediates have been identified unequivocally – not mentioning the final product nor the enzymes’ exact mechanism. Therefore, the goal of this work was to synthesize, study, and modify synthetic, iron-based model complexes for the study of the aforementioned enzymes. Once obtained, these functional models were then to be applied in detailed investigations with (model) substrates of both TET and HPDL. Expansion of the functional model complex platform in order to gain a more diverse portfolio of such iron-based model complexes represents an additional goal. The literature-known complex [FeIV(O)(Py5Me2H)]2+ (C-6; Py5Me2H = 2,6-bis(1,1-bis(2-pyridyl)ethyl)pyridine, L-1) is the basis of the functional model complex platform developed within the scope of this work.[12] Reaction with the nucleobase 5mC gave the expected TET metabolites 5hmC, 5fC, and 5-carboxy cytosine (5caC), as shown by GC-MS analysis. The mechanism of this reaction was elucidated by UV-vis kinetic investigations which allowed for the determination of the rate law as well as the identification of the rate-limiting step, hydrogen atom transfer (HAT) by the iron(IV)-oxido moiety from the methyl group of the substrate (chapter III.4).[13] Subsequently, the substrate’s complexity was increased to nucleosides (chapter III.5) and finally short oligonucleotides (10-mer). In a collaboration with the Carell research group at LMU Munich within the SFB1309 “Chemical Biology of Epigenetic Modifications” it was shown that C-6 is indeed capable of selectively oxidizing a 5mC residue within an oligonucleotide context. Side-product analysis was performed by MALDI-MS (matrix assissted laser desorption/ionization-mass spectrometry), which showed the formation of small amounts of end-of-strand decomposition, however, no interior strand breaks were observed (chapter III.7).[14] These findings lay the ground-work for ongoing investigations of the application of C-6 in epigenetic sequencing of DNA. The TET project was complemented by a joint SFB1309 investigation of the behavior of C-6 towards a series of natural and non-natural nucleobase substrates in collaboration with the Zipse research group at LMU Munich. Here, it was shown that BDEs are a good predictor for the reactivity of the functional model complex C-6 towards C-H bonds, particularly in a nucleobase context (chapter III.8).[15] Furthermore, the iron(III)-hydroxido complex [FeIII(OH)(L-1)]2+ (C-4) was successfully identified as the intermediate and product in the reaction of C-6 with organic substrates. Subsequent investigation of C 4 gave first insight into its reactivity in rebound reactions (chapter IV). In addition to these investigations on the application of C-6, the platform of iron-based functional model complexes was expanded: the ligand system Py5Me2H was modified at several locations, initial experiments towards the immobilization of C 6 on solid supports were successful, and a series of new iron(IV)-oxido, iron(III)-hydroxido, and iron(II) complexes were synthesized (chapter V). The findings presented in this work will give multiple opportunities to further continue on the bioinorganic analysis of iron(II)/α-keto acid dependent enzymes. Metabolomic studies on biological samples obtained from E. coli cultures overexpressing HPDL as well as mammalian cell cultures shed light on the substrate consumption, product formation, and the mechanism of HPDL. Model complex studies with C-6, its iron(III)-hydroxido derivative C-4, and several other iron compounds gave further insight into the complex interaction of HPDL with its substrates and intermediates (chapter VI)

Knowledge-based Modelling of Additive Manufacturing for Sustainability Performance Analysis and Decision Making

Additiivista valmistusta on pidetty käyttökelpoisena monimutkaisissa geometrioissa, topologisesti optimoiduissa kappaleissa ja kappaleissa joita on muuten vaikea valmistaa perinteisillä valmistusprosesseilla. Eduista huolimatta, yksi additiivisen valmistuksen vallitsevista haasteista on ollut heikko kyky tuottaa toimivia osia kilpailukykyisillä tuotantomäärillä perinteisen valmistuksen kanssa. Mallintaminen ja simulointi ovat tehokkaita työkaluja, jotka voivat auttaa lyhentämään suunnittelun, rakentamisen ja testauksen sykliä mahdollistamalla erilaisten tuotesuunnitelmien ja prosessiskenaarioiden nopean analyysin. Perinteisten ja edistyneiden valmistusteknologioiden mahdollisuudet ja rajoitukset määrittelevät kuitenkin rajat uusille tuotekehityksille. Siksi on tärkeää, että suunnittelijoilla on käytettävissään menetelmät ja työkalut, joiden avulla he voivat mallintaa ja simuloida tuotteen suorituskykyä ja siihen liittyvän valmistusprosessin suorituskykyä, toimivien korkea arvoisten tuotteiden toteuttamiseksi. Motivaation tämän väitöstutkimuksen tekemiselle on, meneillään oleva kehitystyö uudenlaisen korkean lämpötilan suprajohtavan (high temperature superconducting (HTS)) magneettikokoonpanon kehittämisessä, joka toimii kryogeenisissä lämpötiloissa. Sen monimutkaisuus edellyttää monitieteisen asiantuntemuksen lähentymistä suunnittelun ja prototyyppien valmistuksen aikana. Tutkimus hyödyntää tietopohjaista mallinnusta valmistusprosessin analysoinnin ja päätöksenteon apuna HTS-magneettien mekaanisten komponenttien suunnittelussa. Tämän lisäksi, tutkimus etsii mahdollisuuksia additiivisen valmistuksen toteutettavuuteen HTS-magneettikokoonpanon tuotannossa. Kehitetty lähestymistapa käyttää fysikaalisiin kokeisiin perustuvaa tuote-prosessi-integroitua mallinnusta tuottamaan kvantitatiivista ja laadullista tietoa, joka määrittelee prosessi-rakenne-ominaisuus-suorituskyky-vuorovaikutuksia tietyille materiaali-prosessi-yhdistelmille. Tuloksina saadut vuorovaikutukset integroidaan kaaviopohjaiseen malliin, joka voi auttaa suunnittelutilan tutkimisessa ja täten auttaa varhaisessa suunnittelu- ja valmistuspäätöksenteossa. Tätä varten testikomponentit valmistetaan käyttämällä kahta metallin additiivista valmistus prosessia: lankakaarihitsaus additiivista valmistusta (wire arc additive manufacturing) ja selektiivistä lasersulatusta (selective laser melting). Rakenteellisissa sovelluksissa yleisesti käytetyistä metalliseoksista (ruostumaton teräs, pehmeä teräs, luja niukkaseosteinen teräs, alumiini ja kupariseokset) testataan niiden mekaaniset, lämpö- ja sähköiset ominaisuudet. Lisäksi tehdään metalliseosten mikrorakenteen karakterisointi, jotta voidaan ymmärtää paremmin valmistusprosessin parametrien vaikutusta materiaalin ominaisuuksiin. Integroitu mallinnustapa yhdistää kerätyn kokeellisen tiedon, olemassa olevat analyyttiset ja empiiriset vuorovaikutus suhteet, sekä muut tietopohjaiset mallit (esim. elementtimallit, koneoppimismallit) päätöksenteon tukijärjestelmän muodossa, joka mahdollistaa optimaalisen materiaalin, valmistustekniikan, prosessiparametrien ja muitten ohjausmuuttujien valinnan, lopullisen 3d-tulosteun komponentin halutun rakenteen, ominaisuuksien ja suorituskyvyn saavuttamiseksi. Valmistuspäätöksenteko tapahtuu todennäköisyysmallin, eli Bayesin verkkomallin toteuttamisen kautta, joka on vankka, modulaarinen ja sovellettavissa muihin valmistusjärjestelmiin ja tuotesuunnitelmiin. Väitöstyössä esitetyn mallin kyky parantaa additiivisien valmistusprosessien suorituskykyä ja laatua, täten edistää kestävän tuotannon tavoitteita.Additive manufacturing (AM) has been considered viable for complex geometries, topology optimized parts, and parts that are otherwise difficult to produce using conventional manufacturing processes. Despite the advantages, one of the prevalent challenges in AM has been the poor capability of producing functional parts at production volumes that are competitive with traditional manufacturing. Modelling and simulation are powerful tools that can help shorten the design-build-test cycle by enabling rapid analysis of various product designs and process scenarios. Nevertheless, the capabilities and limitations of traditional and advanced manufacturing technologies do define the bounds for new product development. Thus, it is important that the designers have access to methods and tools that enable them to model and simulate product performance and associated manufacturing process performance to realize functional high value products. The motivation for this dissertation research stems from ongoing development of a novel high temperature superconducting (HTS) magnet assembly, which operates in cryogenic environment. Its complexity requires the convergence of multidisciplinary expertise during design and prototyping. The research applies knowledge-based modelling to aid manufacturing process analysis and decision making in the design of mechanical components of the HTS magnet. Further, it explores the feasibility of using AM in the production of the HTS magnet assembly. The developed approach uses product-process integrated modelling based on physical experiments to generate quantitative and qualitative information that define process-structure-property-performance interactions for given material-process combinations. The resulting interactions are then integrated into a graph-based model that can aid in design space exploration to assist early design and manufacturing decision-making. To do so, test components are fabricated using two metal AM processes: wire and arc additive manufacturing and selective laser melting. Metal alloys (stainless steel, mild steel, high-strength low-alloyed steel, aluminium, and copper alloys) commonly used in structural applications are tested for their mechanical-, thermal-, and electrical properties. In addition, microstructural characterization of the alloys is performed to further understand the impact of manufacturing process parameters on material properties. The integrated modelling approach combines the collected experimental data, existing analytical and empirical relationships, and other data-driven models (e.g., finite element models, machine learning models) in the form of a decision support system that enables optimal selection of material, manufacturing technology, process parameters, and other control variables for attaining desired structure, property, and performance characteristics of the final printed component. The manufacturing decision making is performed through implementation of a probabilistic model i.e., a Bayesian network model, which is robust, modular, and can be adapted for other manufacturing systems and product designs. The ability of the model to improve throughput and quality of additive manufacturing processes will boost sustainable manufacturing goals

Life cycle assessment in biorefineries : case studies and methodological development

Fossil resources are gradually depleting and becoming more expensive. Therefore, new ways to fuel our economy should be sought. Being a renewable carbon source, biomass will take a key role in the transition to a more sustainable economy. However, while potentially renewable, biomass relies on an intensive cultivation step and it will not be able to deliver a constant and endless supply without inducing other harmful effects. Therefore sustainability assessments of biorefineries are highly relevant. After an introductory first chapter, the sustainability concept and assessment methodologies are studied in chapter two. Based on this information, the life cycle framework is applied in chapter three, in which it is shown that a food and feed company processing wheat can switch to a fossil fuel replacing biorefinery without inducing efficiency losses. On the other hand, the replacement of fossil fuels goes at the cost of other resources such as land, water, minerals, etc. A profound study of the supply chain of different sources of biomass illustrates that the valorization of domestic organic waste and farm residues is an environmentally benign opportunity. These types of biomass however, have lower conversion efficiencies compared to agricultural crops such as silage maize because they often contain more difficult molecules to process such as lignocelluloses requiring more pre- and post-treatment. It is demonstrated that these different types of organic resources can be efficiently converted to a highly energetic biomethane by anaerobic digestion while maintaining nutrients in the digestate, which can be used as fertilizer. Additional emissions causing acidification and eutrophication should however be avoided by good agricultural management. The fourth chapter of this dissertation focuses on methodological development. The quantification of sustainability is a complex task and therefore more research is required to improve assessment techniques. A first identified bottleneck is the acquirement of reliable data. While this is the key to obtain useful results from a life cycle study, it is especially difficult to gather mass and energy balances of future production processes. For this purpose, engineering modules are developed of 22 processes that are commonly used in industry which can be used in prospective sustainability assessments. Although challenges are identified, an application in a case study illustrated the operability and reliability of the approach. The second part of this chapter focuses on the allocation procedure of LCA. It is illustrated that this methodological attribute should be linked to the goal and scope of the assessment. System expansion can give interesting insights in economy wide assessments to assess different product mixes and markets, whereas partitioning is a useful approach in product policies and supply chain improvement. For the latter, exergy is identified as a useful parameter to quantify the physical value of both mass and energy. In a last part of the methodological chapter, an indicator of sustainable development is proposed that focuses on the broader concept of sustainable development. The indicator weighs the antropospheric benefit, quantified as satisfaction by a product or service and the labor quality and quantity, with the ecological burden, quantified as resource and emission impact. These factors are weighted with macro-scale aspects such as the human development index, unemployment rate and the world’s ecological footprint. Overall, it can be concluded that society will have to take better care of its available resources. Biorefineries can have a role in this development by optimally utilizing the available biomass. However, a strong policy is needed that analyzes supply and demand interactions and related impacts such as land use, water use and field emissions. Life cycle assessment will take an essential role in these developments, both in a top-down perspective by analyzing direct and indirect effects of product mixes and markets, as in a bottom-up approach by analyzing and optimizing production chains. On the other hand, more collaborative research is required to better understand different aspects of sustainable development and to search for better ways for a proper assessment of different scopes and scales

Energy. A continuing bibliography with indexes, issue 18

This issue of Energy lists 1038 reports, journal articles, and other documents announced between April 1, 1978 and June 30, 1978 in Scientific and Technical Aerospace Reports (STAR) or in International Aerospace Abstracts (IAA). The coverage includes regional, national and international energy systems; research and development on fuels and other sources of energy; energy conversion, transport, transmission, distribution and storage, with special emphasis on use of hydrogen and of solar energy. Also included are methods of locating or using new energy resources. Of special interest is energy for heating, lighting, for powering aircraft, surface vehicles, or other machinery

DarkSide-20k: A 20 tonne two-phase LAr TPC for direct dark matter detection at LNGS

This paper describes a preliminary design for the experiment, in which the DarkSide-20k LAr TPC is deployed within a shield/veto with a spherical Liquid Scintillator Veto (LSV) inside a cylindrical Water Cherenkov Veto (WCV

Energy: A continuing bibliography with indexes, issue 20

A bibliography is presented which lists 1250 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System from October 1, 1978 through December 31, 1978

SUPERCONDUCTING RADIO FREQUENCY MATERIALS SCIENCE THROUGH NEAR-FIELD MAGNETIC MICROSCOPY

Superconducing Radio-Frequency (SRF) cavities are the backbone of a new generation of particle accelerators used by the high energy physics community. Nowadays, the applications of SRF cavities have expanded far beyond the needs of basic science. The proposed usages include waste treatment, water disinfection, material strengthening, medical applications and even use as high-Q resonators in quantum computers. A practical SRF cavity needs to operate at extremely high rf fields while remaining in the low-loss superconducting state. State of the art Nb cavities can easily reach quality factors Q>2x10^10 at 1.3 GHz. Currently, the performance of the SRF cavities is limited by surface defects which lead to cavity breakdown at high accelerating gradients. Also, there are efforts to reduce the cost of manufacturing SRF cavities, and the cost of operation. This will require an R&D effort to go beyond bulk Nb cavities. Alternatives to bulk Nb are Nb-coated Copper and Nb3Sn cavities. When a new SRF surface treatment, coating technique, or surface optimization method is being tested, it is usually very costly and time consuming to fabricate a full cavity. A rapid rf characterization technique is needed to identify deleterious defects on Nb surfaces and to compare the surface response of materials fabricated by different surface treatments. In this thesis a local rf characterization technique that could fulfill this requirement is presented. First, a scanning magnetic microwave microscopy technique was used to study SRF grade Nb samples. Using this novel microscope the existence of surface weak-links was confirmed through their local nonlinear response. Time-Dependent Ginzburg-Landau (TDGL) simulations were used to reveal that vortex semiloops are created by the inhomogenious magnetic field of the magnetic probe, and contribute to the measured response. Also, a system was put in place to measure the surface resistance of SRF cavities at extremely low temperatures, down to T=70 mK, where the predictions for the surface resistance from various theoretical models diverge. SRF cavities require special treatment during the cooldown and measurement. This includes cooling the cavity down at a rate greater than 1K/minute, and very low ambient magnetic field B<50 nT. I present solutions to both of these challenges