8,539 research outputs found
Simulation of metal powder packing behaviour in laser-based powder bed fusion
Laser-based powder bed fusion (L-PBF) is a method of additive manufacturing, in which metal powder is fused into solid parts, layer by layer. L-PBF shows high promise for manufacture of functional Tungsten parts, but the development of Tungsten powder feedstock for L-PBF processing is demanding and expensive. Therefore, computer simulation is explored as a possible tool for Tungsten powder feedstock development at EOS Finland Oy, with whom this thesis was made.
The aim of this thesis was to develop a simulation model of the recoating process of an EOS M 290 L-PBF system, as well as a validation method for the simulation. The validated simulation model can be used to evaluate the applicability of the used simulation software (FLOW-3D DEM) in powder material development, and possibly use the model as a platform for future application with Tungsten powder. In order to reduce complexity and uncertainties, the irregular Tungsten powder is not yet simulated, and a well-known, spherical EOS IN718 powder feedstock was used instead.
The validation experiment is based on building a low, enclosed wall using the M 290 L-PBF system. Recoated powder is trapped inside as the enclosure is being built, making it possible to remove the sampled powder from a known volume. This enables measuring the powder packing density (PD) of the powder bed. The experiment was repeated five times and some sources of error were also quantified. Average PD was found to be 52 % with a standard deviation of 0.2 %.
The simulation was modelled after the IN718 powder and corresponding process used in the M 290 system. Material-related input values were found by dynamic image analysis, pycnometry, rheometry, and from literature. PD was measured with six different methods, and the method considered as most analogous to the practical validation experiment yielded a PD of 52 %. Various particle behavior phenomena were also observed and analyzed.
Many of the powder bed characterization methods found in literature were not applicable to L-PBF processing or were not representative of the simulated conditions. Many simulation studies were also found to use no validation, or used a validation method which is not based on the investigated phenomena. The validation model developed in this thesis accurately represents the simulated conditions and is found to produce reliable and repeatable results. The simulation model was parametrized with values acquired from practical experiments or literature and closely matched the validation experiment, and could therefore be considered a truthful representation of the powder recoating process of an EOS M 290. The model can be used as a platform for future development of Tungsten powder simulation
Development of Flame Retardant and Antibacterial Dual Functionalised Flexible Polyurethane Foam
Flexible Polyurethane foam (PUF), with its unique properties, such as lightweight and softness, has been utilised extensively. Nevertheless, owing to the intrinsic high flammability and low ignition temperature, PUF-associated fire risks are always a concern. During PUF’s combustion, excessive heat and toxic gases can be generated, threatening the health and life of human beings and causing huge property loss. Consequently, improving the flame retardancy of the PUF is of importance. Later, the global COVID-19 pandemic broke out in 2019, leading to the public’s increased awareness of maintaining good hygiene conditions. Since PUF products are frequently in contact with humans daily, rendering the PUF with bacterial-killing properties should also be addressed.
This dissertation delivers studies on introducing flame retardancy to the PUF via a surface engineering method named the layer-by-layer (LbL) assembly. Due to the consequent COVID-19 situation, this thesis expands the investigations to endow the PUF with antibacterial performances. Preliminary research on fabricating a newly emerged two-dimensional material called MXene (Ti3C2) and chitosan (CH) as flame retardants (FRs) to impart fire safety performances to the PUF was conducted. With only 6.9 wt.% mass added to the PUF, unprecedented fire resistance and smoke suppression properties were received. It was revealed that the FR mechanism was ascribed to the hybrid coating’s excellent barrier and carbonisation effects. Further investigations on improving the PUFs’ biodegradability identified synergistic effects between the MXene with the CH and phytic acid, demonstrating the great potential for reducing the toxicity and improving the eco-friendliness of the PUFs. Additionally, this thesis analysed the FR and antibacterial dual-functionalised PUFs. The synthesised MXene, CH, and silver ion hybridised coating endows the foam with exceptional bactericidal properties with decreases of 99.7 % in gram-negative bacteria and 88.9 % in gram-positive bacteria compared with the unmodified counterpart. Excellent flame retardancy possessed by the dual-functionalised PUFs was discovered. The compatibility of the two functional coatings was evaluated and confirmed. The results manifest the great potential for eradicating the fire risks of PUFs and providing traditional PUF products with antibacterial properties, further expanding PUF’s applications
Systematic analyses with genomic and metabolomic insights reveal a new species, Ophiocordyceps indica sp. nov. from treeline area of Indian Western Himalayan region
Ophiocordyceps is a species-rich genus in the order Hypocreales (Sordariomycetes, Ascomycota) depicting a fascinating relationship between microbes and insects. In the present study, a new species, Ophiocordyceps indica sp. nov., is discovered infecting lepidopteran larvae from tree line locations (2,202–2,653 m AMSL) of the Kullu District, Himachal Pradesh, Indian Western Himalayan region, using combinations of morphological and molecular phylogenetic analyses. A phylogeny for Ophiocordyceps based on a combined multigene (nrSSU, nrLSU, tef-1α, and RPB1) dataset is provided, and its taxonomic status within Ophiocordycipitaceae is briefly discussed. Its genome size (~59 Mb) revealed 94% genetic similarity with O. sinensis; however, it differs from other extant Ophiocordyceps species based on morphological characteristics, molecular phylogenetic relationships, and genetic distance. O. indica is identified as the second homothallic species in the family Ophiocordycipitaceae, after O. sinensis. The presence of targeted marker components, viz. nucleosides (2,303.25 μg/g), amino acids (6.15%), mannitol (10.13%), and biological activity data, suggests it to be a new potential source of nutraceutical importance. Data generated around this economically important species will expand our understanding regarding the diversity of Ophiocordyceps-like taxa from new locations, thus providing new research avenues
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Thermophoresis of electrolyte solutions and protein-ligand systems
Thermophoresis or thermodiffusion is the mass transport driven by a temperature gradient.
This thesis focuses on the thermophoretic motion of ionic compounds in a biological context
and is motivated by a practical application, in which thermodiffusion is used to monitor
protein-ligand reactions. Proteins are complex molecules containing non-ionic and ionic
groups. While recent studies of non-ionic compounds found a strong correlation between
thermodiffusion and hydration, it is unclear how this correlation changes when molecules
are charged. To separate ionic from non-ionic contributions, it is reasonable to look first
into the thermophoretic motion of simple salts without large organic side groups and to
study in the next step complex protein-ligand systems, which typically contain hydrophobic
and hydrophilic groups. The systematic studies of aqueous solutions of simple salts should
reveal differences between ionic and non-ionic systems and should give further information
about ion and ion specific effects. Due to the high complexity of protein-ligand systems,
complementary methods should be used to gain a better understanding of the interactions
between different components that are present in the system. This will help to understand
how the thermophoretic behavior of the free protein differs from that of the protein-ligand
complex formed.
Study of the thermophoretic behavior of ionic systems indicates that several correlations,
which were found for aqueous solutions of non-ionic solutes are no longer valid for ionic
solutes. For non-ionic solutes hydrogen bonds primarily influence the thermophoretic behavior.
In case of ionic solutes, although both electrostatic interactions and hydrogen bonds
are present, it is found that thermophoretic behavior is influenced by electrostatic interactions.
Focusing on the specific ion effects for ionic systems in the context of the Hofmeister
series, a change of the anion is found to influence the thermophoretic behavior more than
a change of the cation. Further, a correlation between thermophoretic behavior and hydrophilicity
of the ionic solutes is found, which underlines the sensitivity of thermodiffusion
to changes in hydration. Based on this sensitivity, a preliminary model is developed for describing
the non-monotonous variation of Soret coefficient ST with concentration for aqueous
solutions of alkali iodide salts. To study the thermodiffusion of binding reactions, we also
use complementary methods such as Isothermal Titration Calorimetry (ITC) and a thermophoretic
microfluidic cell. As systems, we have chosen EDTA-CaCl2 and protein-ligand
systems (binding of Bovine Carbonic Anhydrase I (BCA I) with two aryl sulfonamide ligands). To gain deeper insight into the complex formation reactions thermophoretic data
(non-equilibrium process) are compared with thermodynamic data (equilibrium process) to
establish a mathematical relation between ST and Gibb’s free energy ΔG. For EDTA-CaCl2
and protein-ligand systems, the derived relation holds valid, which enables calculation of ΔG
at a particular temperature from ST
Establiment d’un mètode d’anà lisi de glicans biomarcadors de cà ncer de pà ncrees per cromatografia de lÃquids acoblada a l’espectrometria de masses
Treballs Finals de Grau de QuÃmica, Facultat de QuÃmica, Universitat de Barcelona, Any: 2023, Tutora: Estela Giménez LópezGlycoproteins are proteins that have oligosaccharides covalently attached to the peptide backbone. These carbohydrates are also known as glycans. Protein glycans play a significant role in various cellular processes, including cell-cell recognition, signaling, and adhesion on cell surfaces. However, glycans undergo structural changes in many diseases, such as cancer. Therefore, there is a need to establish new analytical methods that aid in identifying and quantifying glycans to detect the presence of diseases.
In the present study, a reference method for the separation and identification of labelled glycans using capillary liquid chromatography (capLC) coupled with ultraviolet (UV) and mass spectrometry (MS) detection will be developed. First, standard glycans selected as model will be derivatized with aniline (AN) and procainamide (ProA) labels. To assess their degree of derivatization, they will be analysed by matrix assisted laser desorption ionization mass spectrometry (MALDI-MS). Finally, these labelled glycans will serve for the development of a reference analytical method by capLC-UV and capLC-MS.
This reference method will be used in the future to test the status of the chromatographic system in glycoprotein biomarker research. For instance, for the analysis of the N-glycans of human alpha-1-acid glycoprotein (hAGP) under study as a potential biomarker of pancreatic cancer
Leveraging a machine learning based predictive framework to study brain-phenotype relationships
An immense collective effort has been put towards the development of methods forquantifying brain activity and structure. In parallel, a similar effort has focused on collecting experimental data, resulting in ever-growing data banks of complex human in vivo neuroimaging data. Machine learning, a broad set of powerful and effective tools for identifying multivariate relationships in high-dimensional problem spaces, has proven to be a promising approach toward better understanding the relationships between the brain and different phenotypes of interest. However, applied machine learning within a predictive framework for the study of neuroimaging data introduces several domain-specific problems and considerations, leaving the overarching question of how to best structure and run experiments ambiguous. In this work, I cover two explicit pieces of this larger question, the relationship between data representation and predictive performance and a case study on issues related to data collected from disparate sites and cohorts. I then present the Brain Predictability toolbox, a soft- ware package to explicitly codify and make more broadly accessible to researchers the recommended steps in performing a predictive experiment, everything from framing a question to reporting results. This unique perspective ultimately offers recommen- dations, explicit analytical strategies, and example applications for using machine learning to study the brain
Spatial and temporal hierarchical decomposition methods for the optimal power flow problem
The subject of this thesis is the development of spatial and temporal decomposition
methods for the optimal power flow problem, such as in the transmissiondistribution
network topologies. In this context, we propose novel decomposition
interfaces and effectivemethodology for both the spatial and temporal dimensions
applicable to linear and non-linear representations of the OPF problem.
These two decomposition strategies are combined with a Benders-based algorithmand
have advantages in model building time, memory management and solving
time. For example, in the 2880-period linear problems, the decomposition finds
optimal solutions up to 50 times faster and allows even larger instances to be solved;
and in multi-period non-linear problems with 48 periods, close-to-optimal feasible
solutions are found 7 times faster.
With these decompositions, detailed networks can be optimized in coordination,
effectively exploiting the value of the time-linked elements in both transmission and
distribution levels while speeding up the solution process, preserving privacy, and
adding flexibility when dealing with different models at each level.
In the non-linear methodology, significant challenges, such as active set determination,
instability and non-convex overestimations, may hinder its effectiveness,
and they are addressed, making the proposed methodology more robust and stable.
A test network was constructed by combining standard publicly available networks
resulting in nearly 1000 buses and lines with up to 8760 connected periods;
several interfaces were presented depending on the problemtype and its topology
using a modified Benders algorithm. Insight was given into why a Benders-based
decomposition was used for this type of problem instead of a common alternative:
ADMM.
The methodology is useful mainly in two sets of applications: when highly detailed
long-termlinear operational problems need to be solved, such as in planning
frameworks where the operational problems solved assume no prior knowledge; and
in full AC-OPF problems where prior information from historic solutions can be used
to speed up convergence
Pollution-induced community tolerance in freshwater biofilms – from molecular mechanisms to loss of community functions
Exposure to herbicides poses a threat to aquatic biofilms by affecting their community structure, physiology and function. These changes render biofilms to become more tolerant, but on the downside community tolerance has ecologic costs. A concept that addresses induced community tolerance to a pollutant (PICT) was introduced by Blanck and Wängberg (1988). The basic principle of the concept is that microbial communities undergo pollution-induced succession when exposed to a pollutant over a long period of time, which changes communities structurally and functionally and enhancing tolerance to the pollutant exposure. However, the mechanisms of tolerance and the ecologic consequences were hardly studied up to date. This thesis addresses the structural and functional changes in biofilm communities and applies modern molecular methods to unravel molecular tolerance mechanisms.
Two different freshwater biofilm communities were cultivated for a period of five weeks, with one of the communities being contaminated with 4 μg L-1 diuron. Subsequently, the communities were characterized for structural and functional differences, especially focusing on their crucial role of photosynthesis. The community structure of the autotrophs was assessed using HPLC-based pigment analysis and their functional alterations were investigated using Imaging-PAM fluorometry to study photosynthesis and community oxygen profiling to determine net primary production. Then, the molecular fingerprints of the communities were measured with meta-transcriptomics (RNA-Seq) and GC-based community metabolomics approaches and analyzed with respect to changes in their molecular functions. The communities were acute exposed to diuron for one hour in a dose-response design, to reveal a potential PICT and uncover related adaptation to diuron exposure. The combination of apical and molecular methods in a dose-response design enabled the linkage of functional effects of diuron exposure and underlying molecular mechanisms based on a sensitivity analysis.
Chronic exposure to diuron impaired freshwater biofilms in their biomass accrual. The contaminated communities particularly lost autotrophic biomass, reflected by the decrease in specific chlorophyll a content. This loss was associated with a change in the molecular fingerprint of the communities, which substantiates structural and physiological changes. The decline in autotrophic biomass could be due to a primary loss of sensitive autotrophic organisms caused by the selection of better adapted species in the course of chronic exposure. Related to this hypothesis, an increase in diuron tolerance has been detected in the contaminated communities and molecular mechanisms facilitating tolerance have been found. It was shown that genes of the photosystem, reductive-pentose phosphate cycle and arginine metabolism were differentially expressed among the communities and that an increased amount of potential antioxidant degradation products was found in the contaminated communities. This led to the hypothesis that contaminated communities may have adapted to oxidative stress, making them less sensitive to diuron exposure. Moreover, the photosynthetic light harvesting complex was altered and the photoprotective xanthophyll cycle was increased in the contaminated communities. Despite these adaptation strategies, the loss of autotrophic biomass has been shown to impair primary production. This impairment persisted even under repeated short-term exposure, so that the tolerance mechanisms cannot safeguard primary production as a key function in aquatic systems.:1. The effect of chemicals on organisms and their functions .............................. 1
1.1 Welcome to the anthropocene .......................................................................... 1
1.2 From cellular stress responses to ecosystem resilience ................................... 3
1.2.1 The individual pursuit for homeostasis ....................................................... 3
1.2.2 Stability from diversity ................................................................................. 5
1.3 Community ecotoxicology - a step forward in monitoring the effects of chemical
pollution? ................................................................................................................. 6
1.4 Functional ecotoxicological assessment of microbial communities ................... 9
1.5 Molecular tools – the key to a mechanistic understanding of stressor effects
from a functional perspective in microbial communities? ...................................... 12
2. Aims and Hypothesis ......................................................................................... 14
2.1 Research question .......................................................................................... 14
2.2 Hypothesis and outline .................................................................................... 15
2.3 Experimental approach & concept .................................................................. 16
2.3.1 Aquatic freshwater biofilms as model community ..................................... 16
2.3.2 Diuron as model herbicide ........................................................................ 17
2.3.3 Experimental design ................................................................................. 18
3. Structural and physiological changes in microbial communities after chronic
exposure - PICT and altered functional capacity ................................................. 21
3.1 Introduction ..................................................................................................... 21
3.2 Methods .......................................................................................................... 23
3.2.1 Biofilm cultivation ...................................................................................... 23
3.2.2 Dry weight and autotrophic index ............................................................. 23
3.2.4 Pigment analysis of periphyton ................................................................. 23
3.2.4.1 In-vivo pigment analysis for community characterization ....................... 24
3.2.4.2 In-vivo pigment analysis based on Imaging-PAM fluorometry ............... 24
3.2.4.3 In-vivo pigment fluorescence for tolerance detection ............................. 26
3.2.4.4 Ex-vivo pigment analysis by high-pressure liquid-chromatography ....... 27
3.2.5 Community oxygen metabolism measurements ....................................... 28
3.3 Results and discussion ................................................................................... 29
3.3.1 Comparison of the structural community parameters ............................... 29
3.3.2 Photosynthetic activity and primary production of the communities after
selection phase ................................................................................................. 33
3.3.3 Acquisition of photosynthetic tolerance .................................................... 34
3.3.4 Primary production at exposure conditions ............................................... 36
3.3.5 Tolerance detection in primary production ................................................ 37
3.4 Summary and Conclusion ........................................................................... 40
4. Community gene expression analysis by meta-transcriptomics ................... 41
4.1 Introduction to meta-transcriptomics ............................................................... 41
4.2. Methods ......................................................................................................... 43
4.2.1 Sampling and RNA extraction................................................................... 43
4.2.2 RNA sequencing analysis ......................................................................... 44
4.2.3 Data assembly and processing................................................................. 45
4.2.4 Prioritization of contigs and annotation ..................................................... 47
4.2.5 Sensitivity analysis of biological processes .............................................. 48
4.3 Results and discussion ................................................................................... 48
4.3.1 Characterization of the meta-transcriptomic fingerprints .......................... 49
4.3.2 Insights into community stress response mechanisms using trend analysis
(DRomic’s) ......................................................................................................... 51
4.3.3 Response pattern in the isoform PS genes .............................................. 63
4.5 Summary and conclusion ................................................................................ 65
5. Community metabolome analysis ..................................................................... 66
5.1 Introduction to community metabolomics ........................................................ 66
5.2 Methods .......................................................................................................... 68
5.2.1 Sampling, metabolite extraction and derivatisation................................... 68
5.2.2 GC-TOF-MS analysis ............................................................................... 69
5.2.3 Data processing and statistical analysis ................................................... 69
5.3 Results and discussion ................................................................................... 70
5.3.1 Characterization of the metabolic fingerprints .......................................... 70
5.3.2 Difference in the metabolic fingerprints .................................................... 71
5.3.3 Differential metabolic responses of the communities to short-term exposure
of diuron ............................................................................................................ 73
5.4 Summary and conclusion ................................................................................ 78
6. Synthesis ............................................................................................................. 79
6.1 Approaches and challenges for linking molecular data to functional
measurements ...................................................................................................... 79
6.2 Methods .......................................................................................................... 83
6.2.1 Summary on the data ............................................................................... 83
6.2.2 Aggregation of molecular data to index values (TELI and MELI) .............. 83
6.2.3 Functional annotation of contigs and metabolites using KEGG ................ 83
6.3 Results and discussion ................................................................................... 85
6.3.1 Results of aggregation techniques ........................................................... 85
6.3.2 Sensitivity analysis of the different molecular approaches and endpoints 86
6.3.3 Mechanistic view of the molecular stress responses based on KEGG
functions ............................................................................................................ 89
6.4 Consolidation of the results – holistic interpretation and discussion ............... 93
6.4.1 Adaptation to chronic diuron exposure - from molecular changes to
community effects.............................................................................................. 93
6.4.2 Assessment of the ecological costs of Pollution-induced community
tolerance based on primary production ............................................................. 94
6.5 Outlook ............................................................................................................ 9
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
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