929 resultados para shape and surface modeling
Resumo:
Depuis que la haute énantiopureté est nécessaire dans l’industrie pharmaceutique, les études visant à découvrir les mécanismes pour l’hydrogénation énantiosélective de cétones ou céto-esters sur les surfaces, et à rechercher de nouveaux et plus performants catalyseurs asymétriques, sont d’une grande importance. La microscopie à effet tunnel (STM), la spectroscopie infrarouge de réflexion-absorption, la spectroscopie de désorption à température programmée et la spectrométrie de photoélectrons induits par rayons X sont des méthodes performantes facilitant la compréhension des mécanismes de réaction. En plus de nous permettre de comprendre les mécanismes réactionnels, les études peuvent fournir des informations sur la dynamique des réactions en catalyse hétérogène ainsi que sur le développement de la théorie de la fonctionnelle de la densité (DFT) afin de calculer des interactions faibles dans les processus de surface. D’autres parts, les calculs DFT fournissent une aide essentielle à l’interprétation des données de STM et spectroscopie de surface. Dans cette thèse, certains cétones et céto-esters sur la surface de platine sont étudiées par les techniques sophistiquées mentionnées ci-dessus. Mes études démontrent que la combinaison de l’utilisation de la spectroscopie de routine, des nanotechnologies et de nombreux calculs élaborés, est une méthode efficace pour étudier les réactions à la surface car ces techniques explorent les différents aspects de la surface ainsi que s’entraident mutuellement lors de certaines interprétations.
Resumo:
The engineering of liquid behavior on surfaces is important for infrastructure, transportation, manufacturing, and sensing. Surfaces can be rendered superhydrophobic by microstructuring, and superhydrophobic devices could lead to practical corrosion inhibition, self-cleaning, fluid flow control, and surface drag reduction. To more fully understand how liquid interacts with microstructured surfaces, this dissertation introduces a direct method for determining droplet solid-liquid-vapor interfacial geometry on microstructured surfaces. The technique performs metrology on molten metal droplets deposited onto microstructured surfaces and then frozen. Unlike other techniques, this visualization technique can be used on large areas of curved and opaque microstructured surfaces to determine contact line. This dissertation also presents measurements and models for how curvature and flexing of microstructured polymers affects hydrophobicity. Increasing curvature of microstructured surfaces leads to decreased slide angle for liquid droplets suspended on the surface asperities. For a surface with regularly spaced asperities, as curvature becomes more positive, droplets suspended on the tops of asperities are suspended on fewer asperities. Curvature affects superhydrophobicity because microscopic curvature changes solid-liquid interaction, pitch is altered, and curvature changes the shape of the three phase contact line. This dissertation presents a model of droplet interactions with curved microstructured surfaces that can be used to design microstructure geometries that maintain the suspension of a droplet when curved surfaces are covered with microstructured polymers. Controlling droplet dynamics could improve microfluidic devices and the shedding of liquids from expensive equipment, preventing corrosion and detrimental performance. This dissertation demonstrates redirection of dynamic droplet spray with anisotropic microstructures. Superhydrophobic microstructured surfaces can be economically fabricated using metal embossing masters, so this dissertation describes casting-based microfabrication of metal microstructures and nanostructures. Low melting temperature metal was cast into flexible silicone molds which were themselves cast from microfabricated silicon templates. The flexibility of the silicone mold permits casting of curved surfaces, which this dissertation demonstrates by fabricating a cylindrical metal roller with microstructures. The metal microstructures can be in turn used as a reusable molding tool. This dissertation also describes an industrial investment casting process to produce aluminum molds having integrated microstructures. Unlike conventional micromolding tools, the aluminum mold was large and had complex curved surfaces. The aluminum was cast into curved microstructured ceramic molds which were themselves cast from curved microstructured rubber. Many structures were successfully cast into the aluminum with excellent replication fidelity, including circular, square, and triangular holes. This dissertation demonstrates molding of large, curved surfaces having surface microstructures using the aluminum mold. This work contributes a more full understanding of the phenomenon of superhydrophobicity and techniques for the economic fabrication of superhydrophobic microstructures.
Resumo:
This dissertation focuses on design challenges caused by secondary impacts to printed wiring assemblies (PWAs) within hand-held electronics due to accidental drop or impact loading. The continuing increase of functionality, miniaturization and affordability has resulted in a decrease in the size and weight of handheld electronic products. As a result, PWAs have become thinner and the clearances between surrounding structures have decreased. The resulting increase in flexibility of the PWAs in combination with the reduced clearances requires new design rules to minimize and survive possible internal collisions impacts between PWAs and surrounding structures. Such collisions are being termed ‘secondary impact’ in this study. The effect of secondary impact on board-level drop reliability of printed wiring boards (PWBs) assembled with MEMS microphone components, is investigated using a combination of testing, response and stress analysis, and damage modeling. The response analysis is conducted using a combination of numerical finite element modeling and simplified analytic models for additional parametric sensitivity studies.
Resumo:
The catastrophic event of red tide has happened in the Strait of Hormuz, the Persian Gulf and Gulf of Oman from late summer 2008 to spring 2009. With its devastating effects, the phenomenon shocked all the countries located in the margin of the Persian Gulf and the Gulf of Oman and caused considerable losses to fishery industries, tourism, and tourist and trade economy of the region. In the maritime cruise carried out by the Persian Gulf and Gulf of Oman Ecological Research Institute, field data, including temperature, salinity, chlorophyll-a, dissolved oxygen and algal density were obtained for this research. Satellite information was received from MODIS and MERIS and SeaWiFS sensors. Temperature and surface chlorophyll images were obtained and compared with the field data and data of PROBE model. The results obtained from the present research indicated that with the occurrence of harmful algal blooms (HAB), the Chlorophyll-a and the dissolved oxygen contents increased in the surface water. Maximum algal density was seen in the northern coasts of the Strait of Hormuz. Less concentration of algal density was detected in deep and surface offshore water. Our results show that the occurred algal bloom was the result of seawater temperature drop, water circulation and the adverse environmental pollutions caused by industrial and urban sewages entering the coastal waters in this region of the Persian Gulf ,This red tide phenomenon was started in the Strait of Hormuz and eventually covered about 140,000 km2 of the Persian Gulf and total area of Strait of Hormuz and it survived for 10 months which is a record amongst the occurred algal blooms across the world. Temperature and chlorophyll satellite images were proportionate to the measured values obtained by the field method. This indicates that satellite measurements have acceptable precisions and they can be used in sea monitoring and modeling.
Resumo:
This thesis proposes a generic visual perception architecture for robotic clothes perception and manipulation. This proposed architecture is fully integrated with a stereo vision system and a dual-arm robot and is able to perform a number of autonomous laundering tasks. Clothes perception and manipulation is a novel research topic in robotics and has experienced rapid development in recent years. Compared to the task of perceiving and manipulating rigid objects, clothes perception and manipulation poses a greater challenge. This can be attributed to two reasons: firstly, deformable clothing requires precise (high-acuity) visual perception and dexterous manipulation; secondly, as clothing approximates a non-rigid 2-manifold in 3-space, that can adopt a quasi-infinite configuration space, the potential variability in the appearance of clothing items makes them difficult to understand, identify uniquely, and interact with by machine. From an applications perspective, and as part of EU CloPeMa project, the integrated visual perception architecture refines a pre-existing clothing manipulation pipeline by completing pre-wash clothes (category) sorting (using single-shot or interactive perception for garment categorisation and manipulation) and post-wash dual-arm flattening. To the best of the author’s knowledge, as investigated in this thesis, the autonomous clothing perception and manipulation solutions presented here were first proposed and reported by the author. All of the reported robot demonstrations in this work follow a perception-manipulation method- ology where visual and tactile feedback (in the form of surface wrinkledness captured by the high accuracy depth sensor i.e. CloPeMa stereo head or the predictive confidence modelled by Gaussian Processing) serve as the halting criteria in the flattening and sorting tasks, respectively. From scientific perspective, the proposed visual perception architecture addresses the above challenges by parsing and grouping 3D clothing configurations hierarchically from low-level curvatures, through mid-level surface shape representations (providing topological descriptions and 3D texture representations), to high-level semantic structures and statistical descriptions. A range of visual features such as Shape Index, Surface Topologies Analysis and Local Binary Patterns have been adapted within this work to parse clothing surfaces and textures and several novel features have been devised, including B-Spline Patches with Locality-Constrained Linear coding, and Topology Spatial Distance to describe and quantify generic landmarks (wrinkles and folds). The essence of this proposed architecture comprises 3D generic surface parsing and interpretation, which is critical to underpinning a number of laundering tasks and has the potential to be extended to other rigid and non-rigid object perception and manipulation tasks. The experimental results presented in this thesis demonstrate that: firstly, the proposed grasp- ing approach achieves on-average 84.7% accuracy; secondly, the proposed flattening approach is able to flatten towels, t-shirts and pants (shorts) within 9 iterations on-average; thirdly, the proposed clothes recognition pipeline can recognise clothes categories from highly wrinkled configurations and advances the state-of-the-art by 36% in terms of classification accuracy, achieving an 83.2% true-positive classification rate when discriminating between five categories of clothes; finally the Gaussian Process based interactive perception approach exhibits a substantial improvement over single-shot perception. Accordingly, this thesis has advanced the state-of-the-art of robot clothes perception and manipulation.
Resumo:
The overarching theme of this thesis is mesoscale optical and optoelectronic design of photovoltaic and photoelectrochemical devices. In a photovoltaic device, light absorption and charge carrier transport are coupled together on the mesoscale, and in a photoelectrochemical device, light absorption, charge carrier transport, catalysis, and solution species transport are all coupled together on the mesoscale. The work discussed herein demonstrates that simulation-based mesoscale optical and optoelectronic modeling can lead to detailed understanding of the operation and performance of these complex mesostructured devices, serve as a powerful tool for device optimization, and efficiently guide device design and experimental fabrication efforts. In-depth studies of two mesoscale wire-based device designs illustrate these principles—(i) an optoelectronic study of a tandem Si|WO3 microwire photoelectrochemical device, and (ii) an optical study of III-V nanowire arrays.
The study of the monolithic, tandem, Si|WO3 microwire photoelectrochemical device begins with development and validation of an optoelectronic model with experiment. This study capitalizes on synergy between experiment and simulation to demonstrate the model’s predictive power for extractable device voltage and light-limited current density. The developed model is then used to understand the limiting factors of the device and optimize its optoelectronic performance. The results of this work reveal that high fidelity modeling can facilitate unequivocal identification of limiting phenomena, such as parasitic absorption via excitation of a surface plasmon-polariton mode, and quick design optimization, achieving over a 300% enhancement in optoelectronic performance over a nominal design for this device architecture, which would be time-consuming and challenging to do via experiment.
The work on III-V nanowire arrays also starts as a collaboration of experiment and simulation aimed at gaining understanding of unprecedented, experimentally observed absorption enhancements in sparse arrays of vertically-oriented GaAs nanowires. To explain this resonant absorption in periodic arrays of high index semiconductor nanowires, a unified framework that combines a leaky waveguide theory perspective and that of photonic crystals supporting Bloch modes is developed in the context of silicon, using both analytic theory and electromagnetic simulations. This detailed theoretical understanding is then applied to a simulation-based optimization of light absorption in sparse arrays of GaAs nanowires. Near-unity absorption in sparse, 5% fill fraction arrays is demonstrated via tapering of nanowires and multiple wire radii in a single array. Finally, experimental efforts are presented towards fabrication of the optimized array geometries. A hybrid self-catalyzed and selective area MOCVD growth method is used to establish morphology control of GaP nanowire arrays. Similarly, morphology and pattern control of nanowires is demonstrated with ICP-RIE of InP. Optical characterization of the InP nanowire arrays gives proof of principle that tapering and multiple wire radii can lead to near-unity absorption in sparse arrays of InP nanowires.
Resumo:
We compare the pore size distribution of a well-characterized activated carbon derived from model-dependent, adsorption integral equation (AIE) methods with those from model-independent, immersion calorimetry and isosteric heat analyses. The AIE approach applied to nitrogen gave a mean pore width of 0.57 nm; the CO2 distribution exhibited wider dispersion. Spherical model application to CO2 and diffusion limitations for nitrogen and argon were proposed as primary reasons for inconsistency. Immersion enthalpy revealed a sharp decrease in available area equivalent to a cut-off due to molecular exclusion when the accessible surface was assessed against probe kinetic diameter. Mean pore width was identified as 0.58 ± 0.02 nm, endorsing the underlying assumptions for the nitrogen-based AIE approach. A comparison of the zero-coverage isosteric heat of adsorption for various non-polar adsorptives by the porous test sample was compared with the same adsorptives in contact with a non-porous reference adsorbent, leading to an energy ratio or adsorption enhancement factor. A linear relationship between the energy ratio and probe kinetic diameter indicated a primary pore size at 0.59 nm. The advantage of this enthalpy, model-independent methods over AIE were due to no assumptions regarding probe molecular shape, and no assumptions for pore shape and/or connectivity.
Resumo:
Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.
Resumo:
Semiconductor nanowires, based on silicon (Si) or germanium (Ge) are leading candidates for many ICT applications, including next generation transistors, optoelectronics, gas and biosensing and photovoltaics. Key to these applications is the possibility to tune the band gap by changing the diameter of the nanowire. Ge nanowires of different diameter have been studied with H termination, but, using ideas from chemistry, changing the surface terminating group can be used to modulate the band gap. In this paper we apply the generalised gradient approximation of density functional theory (GGA-DFT) and hybrid DFT to study the effect of diameter and surface termination using –H, –NH2 and –OH groups on the band gap of (001), (110) and (111) oriented germanium nanowires. We show that the surface terminating group allows both the magnitude and the nature of the band gap to be changed. We further show that the absorption edge shifts to longer wavelength with the –NH2 and –OH terminations compared to the –H termination and we trace the origin of this effect to valence band modifications upon modifying the nanowire with –NH2 or –OH. These results show that it is possible to tune the band gap of small diameter Ge nanowires over a range of ca. 1.1 eV by simple surface chemistry.
Resumo:
Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.
Resumo:
Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.
Resumo:
Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.
Resumo:
Anthropogenic activities and climatic processes heavily influence surface water resources by causing their progressive depletion, which in turn affects both societies and the environment. Therefore, there is an urgent need to understand the contribution of human and climatic dynamics on the variation of surface water availability. Here, this investigation is performed on the contiguous United States (CONUS) using remotely-sensed data. Three anthropogenic (i.e., urban area, population, and irrigation) and two climatic factors (i.e., precipitation and temperature) were selected as potential drivers of changes in surface water extent and the overlap between the increase or decrease in these drivers and the variation of surface water was examined. Most of the river basins experienced a surface water gain due to precipitation increase (eastern CONUS), and a reduction of irrigated land (western CONUS). River basins of the arid southwestern region and some river basins of the northeastern area encountered a surface water loss, essentially induced by population growth, along with a precipitation deficit and a general expansion of irrigated land. To further inspect the role of population growth and urbanization on surface water loss, the spatial interaction between human settlements and surface water depletion was examined by evaluating the frequency of surface water loss as a function of distance from urban areas. The decline of the observed frequency was successfully reproduced with an exponential distance-decay model, proving that surface water losses are more concentrated in the proximity of cities. Climatic conditions influenced this pattern, with more widely distributed losses in arid regions compared to temperate and continental areas. The results presented in this Thesis provide an improved understanding of the effects of anthropogenic and climatic dynamics on surface water availability, which could be integrated in the definition of sustainable strategies for urbanization, water management, and surface water restoration.
Resumo:
Conventional chromatographic columns are packed with porous beads by the universally employed slurry-packing method. The lack of precise control of the particle size distribution, shape and position inside the column have dramatic effects on the separation efficiency. In the first part the thesis an ordered, three-dimensional, pillar-array structure was designed by a CAD software. Several columns, characterized by different fluid distributors and bed length, were produced by a stereolithographic 3D printer and compared in terms of pressure drop and height equivalent to a theroretical plate (HETP). To prevent the release of unwanted substances and to provide a surface for immobilizing a ligand, pillars were coated with one or more of the following materials: titanium dioxide, nanofibrillated cellulose (NFC) and polystyrene. The external NFC layer was functionalized with Cibacron Blue and the dynamic binding capacity of the column was measured by performing three chromatographic cycles, using bovine serum albumin (BSA) as target molecule. The second part of the thesis deals with Covid-19 pandemic related research activities. In early 2020, due to the pandemic outbreak, surgical face masks became an essential non-pharmaceutical intervention to limit the spread. To address the consequent shortage and to support the reconversion of the Italian industry, in late March 2020 a multidisciplinary group of the University of Bologna created the first Italian laboratory able to perform all the tests required for the evaluation and certification of surgical masks. More than 1200 tests were performed on about 350 prototypes, according to the standard EN 14683:2019. The results were analyzed to define the best material properties and masks composition for the production of masks with excellent efficiency. To optimize the usage of surgical masks and to reduce their environmental burden, the variation of their performance over time of usage were investigated as to determine the maximum lifetime.
Direct Visualization Of The Action Of Triton X-100 On Giant Vesicles Of Erythrocyte Membrane Lipids.
Resumo:
The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. In fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. The shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. The Ld domains are then separated from the original vesicle and completely solubilized by TX-100. The insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngomyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.