Combination Of Simulations Research Articles

Less-deformable erythrocyte subpopulations biomechanically induce endothelial inflammation in sickle cell disease

AbstractSickle cell disease (SCD) is canonically characterized by reduced red blood cell (RBC) deformability, leading to microvascular obstruction and inflammation. Although the biophysical properties of sickle RBCs are known to influence SCD vasculopathy, the contribution of poor RBC deformability to endothelial dysfunction has yet to be fully explored. Leveraging interrelated in vitro and in silico approaches, we introduce a new paradigm of SCD vasculopathy in which poorly deformable sickle RBCs directly cause endothelial dysfunction via mechanotransduction, during which endothelial cells sense and pathophysiologically respond to aberrant physical forces independently of microvascular obstruction, adhesion, or hemolysis. We demonstrate that perfusion of sickle RBCs or pharmacologically-dehydrated healthy RBCs into small venule-sized “endothelialized” microfluidics leads to pathologic physical interactions with endothelial cells that directly induce inflammatory pathways. Using a combination of computational simulations and large venule-sized endothelialized microfluidics, we observed that perfusion of heterogeneous sickle RBC subpopulations with varying deformability, as well as suspensions of dehydrated normal RBCs admixed with normal RBCs, leads to aberrant margination of the less-deformable RBC subpopulations toward the vessel walls, causing localized, increased shear stress. Increased wall stress is dependent on the degree of subpopulation heterogeneity and oxygen tension and leads to inflammatory endothelial gene expression via mechanotransductive pathways. Our multifaceted approach demonstrates that the presence of sickle RBCs with reduced deformability leads directly to pathological physical (ie, direct collisions and/or compressive forces) and shear-mediated interactions with endothelial cells and induces an inflammatory response, thereby elucidating the ubiquity of vascular dysfunction in SCD.

Enhancing Numerical Simulations through Advanced Data Analysis In Computational Mathematics

Improving numerical models through advanced data analysis in computational mathematics is a major step forward in many areas of science and engineering. The main goal of this study is to find ways to make accuracy, speed, and the ability to predict better by combining advanced data analysis techniques with computer simulation techniques. The study looks at how machine learning algorithms, statistical methods, and traditional computer methods can work together to solve hard, multidimensional problems. Algorithms for machine learning, like neural networks and support vector machines, are used to find trends and connections in very big datasets. These algorithms can give us information that other methods might miss. These new ideas make it easier to make models and programs that are more realistic. Statistical methods, like regression analysis and Bayesian reasoning, are used to measure error and make computer results more reliable. The goal of the study is to lower the cost of computing and raise the rate at which computer models converge by using these methods. A big part of this study is using these advanced methods to solve problems in the real world, like in material science, fluid dynamics, and climate models. Case studies show how combining computer simulations and data analysis can help make predictions that are more accurate and help people make better decisions. The study also looks at the problems that come with how hard these advanced methods are to compute and how much data they need, and it suggests ways to fix these problems. This study shows how mixing advanced data analysis with computer models in computational mathematics can change things. The results show how important it is to use methods from different fields to solve difficult science and engineering issues. This makes it possible for more accurate and useful models that can lead to new ideas and discoveries in many areas. This combination not only makes numerical models more powerful, but it also creates new study and use opportunities in computer mathematics.

Influences of human milk proteins on the release of human milk odors: Non-covalent interactions between α-lactalbumin and key odor skeleton compounds

Human milk (HM) provides optimal nutrition for infants, but infant formula (IF) serves as a potential alternative to HM when breastfeeding is not an option. However, IF possesses a more intense aroma than HM, and it is often challenging to reduce this disparity due to its stringent production regulations. Therefore, investigating the interaction between HM proteins and odor molecules is essential for comprehending the distinct odor characteristics of HM and guiding improvements in IF to mimic the aroma of HM. This research aims to characterize the HM odor and explore the influence of HM α-lactalbumin (HMLB) on the release of HM odor skeleton compounds (OSC) using a combination of computer simulation, human perceptions, and instrumental analyses. A total of 20 OSCs were identified. Notably, the release of most of these compounds was negatively correlated with the HM protein content, with the strongest negative correlations being observed for hexanal, nonanal, and decanal (|R| ≥ 0.7, P < 0.01). The molecular docking simulations demonstrated that HMLB inhibited the volatilization of hexanal, nonanal, and decanal, thereby increasing the odor threshold of these odor compounds (61.94 %, 241.5 %, and 198.6 %). This inhibition was mainly achieved through the formation of hydrogen bonding and hydrophobic interactions, a finding corroborated by multi-spectroscopic analysis. Overall, the experimental results provide valuable insights into the odor mechanism of HM and contribute to the development of IF that mimics the HM odor.

ANÁLISIS NUMÉRICO Y EXPERIMENTAL DEL DESGASTE ABRASIVO DE DOS ACEROS UTILIZADOS EN APEROS DE LABRANZA

This study combines computer simulation using the Discrete Element Method (DEM) with field experiments to assess the resistance to abrasive wear of AISI 1010 and AISI C1064 steels in tillage tools. It was found that the wear on AISI 1010 was over 50% higher than on AISI C1064. The DEM model accurately predicted wear (e=0.005g, R^2=99.8%), regardless of operational conditions and steel characteristics. The mean absolute errors of the simulation compared to field tests were 0.01937 g for AISI C1064 and 0.08619 g for AISI 1010.

Effect of emitter tip spacing on Si vacuum field emitter arrays

This paper presents a qualitative and quantitative analysis of close-packed vacuum field emitter arrays. Through a combination of computational simulations and experimental verifications, the relationship between emitter spacing and electric field screening is studied. In order to obtain a uniform electron emission and large current densities from a field emitter array, it is essential to minimize the screening effect between the adjacent field emitters. As previously demonstrated, sharpening the emitter tips, reducing the background doping concentration of the emitters, and reducing the anode–cathode distance can suppress the screening effect. Field emitter arrays with different sizes and emitter spacings are fabricated and characterized. Decreasing the array size and increasing emitter spacing lead to a larger average current per emitter (19 nA/tip at an anode voltage of 250 V). However, larger current densities (up to 3.3 A/cm2) are observed in close-packed arrays. In very large arrays with a small emitter spacing, the current is scaled with the emitter area (∼4.2 nA/emitter at an anode voltage of 250 V), indicating a small current contribution from the sides of the array.

Visible-light photocatalytic activity of rare-earth-metal-doped TiO2: Experimental analysis and machine learning for virtual design

Modification with rare-earth (RE) metals has emerged as an important approach for enhancing the properties of titanium dioxide. Herein, the visible-light photocatalytic activity of RE-TiO2 (RE: Tm, Er, Nd, Dy, Lu, La, Ho, Pr, Tb, Sc, Ce, Yb, Sm, Gd, Y, or Eu) was investigated using a combination of computer simulations and experimental techniques. The RE-TiO2 photocatalysts were characterised using advanced experimental techniques, including X-ray diffraction, X-ray photoelectron spectroscopy, luminescence, diffuse reflectance spectroscopy, and specific surface area measurements. Furthermore, a quantitative structure–activity relationship analysis was conducted by applying a partial least-squares machine learning algorithm. The Ho-TiO2 sample exhibited the highest photocatalytic activity under visible-light irradiation. Notably, the observed activity was not due to an up-conversion process, originating instead from slight bandgap narrowing caused by new sub-bandgap states from the RE 4 f levels.

Probing the hierarchical dynamics of DNA-sperm nuclear transition protein complexes through fuzzy interaction and mesoscale condensation.

Nuclear transition protein TNP1 is a crucial player mediating histone-protamine exchange in condensing spermatids. A unique combination of intrinsic disorder and multivalent properties turns TNP1 into an ideal agent for orchestrating the formation of versatile TNP-DNA assemblies. Despite its significance, the physicochemical property and the molecular mechanism followed by TNP1 for histone replacement and DNA condensation are still poorly understood. This study reports the first-time in vitro expression and purification of human TNP1 and investigates the hierarchical dynamics of TNP1-DNA interaction using a combination of computational simulations, biochemical assays, fluorescence imaging, and atomic force microscopy. We explored three crucial facets of TNP1-DNA interactions. Initially, we delve into the molecular binding process that entails fuzzy interactions between TNP1 and DNA at the atomistic scale. Subsequently, we analyze how TNP1 binding affects the electrostatic and mechanical characteristics of DNA and influences its morphology. Finally, we study the biomolecular condensation of TNP1-DNA when subjected to high concentrations. The findings of our study set the foundation for comprehending the potential involvement of TNP1 in histone replacement and DNA condensation in spermatogenesis.

Bioinspired rational design of bi-material 3D printed soft-hard interfaces

Durable interfacing of hard and soft materials is a major design challenge caused by the ensuing stress concentrations. In nature, soft-hard interfaces exhibit remarkable mechanical performance, with failures rarely happening at the interface. Here, we mimic the strategies observed in nature to design efficient soft-hard interfaces. We base our geometrical designs on triply periodic minimal surfaces (i.e., Octo, Diamond, and Gyroid), collagen-like triple helices, and randomly distributed particles. A combination of computational simulations and experimental techniques, including uniaxial tensile and quad-lap shear tests, are used to characterize the mechanical performance of the interfaces. Our analyses suggest that smooth interdigitated connections, compliant gradient transitions, and either decreasing or constraining strain concentrations lead to simultaneously strong and tough interfaces. We generate additional interfaces where the abovementioned toughening mechanisms work synergistically to create soft-hard interfaces with strengths approaching the upper achievable limit and enhancing toughness values by 50%, as compared to the control group.

Evidence of bimolecular layer of ethanol on graphite at 190K - Experimental and simulation studies

Adsorption mechanism of ethanol on graphite is comprehensively investigated with a combined experimental measurements and computer simulation. The unique feature of the interplay of clustering and molecular layering of ethanol is highlighted, and ethanol serves as an ideal adsorbate because it behaves as a species intermediate between simple gases and water. For simple gases such as argon and krypton, molecular layering is a dominant mechanism for temperatures above their bulk triple point temperatures, while for water the mechanism of clustering is the dominant one. The intermediate feature of ethanol lies in the ethyl group that interacts with graphite while the hydroxyl group induces intermolecular interactions which are stronger than the adsorbate-graphite interaction. It is this strong intermolecular interaction that leads to two-stage mechanism of monolayer formation, with discrete cluster formation and growth in the form of oligomers (dominantly in tetramers and pentamers), followed by the coalescence of growing clusters. The interplay of clustering and coalescence of growing clusters depends on temperature, and for low temperature at 190 K, a bilayer formation was observed with network of hydrogen bonding holding two adsorbate layers, exposing the ethyl groups to the gas phase. As the temperature is increased to 298 K, the hydroxyl groups are no longer limited to the interlayer region between the first and second adsorbate layers but have the freedom to expose themselves to the gas phase, which results in multilayering of the third and higher layers.

Historical Assembly of Andean Tree Communities.

Patterns of species diversity have been associated with changes in climate across latitude and elevation. However, the ecological and evolutionary mechanisms underlying these relationships are still actively debated. Here, we present a complementary view of the well-known tropical niche conservatism (TNC) hypothesis, termed the multiple zones of origin (MZO) hypothesis, to explore mechanisms underlying latitudinal and elevational gradients of phylogenetic diversity in tree communities. The TNC hypothesis posits that most lineages originate in warmer, wetter, and less seasonal environments in the tropics and rarely colonize colder, drier, and more seasonal environments outside of the tropical lowlands, leading to higher phylogenetic diversity at lower latitudes and elevations. In contrast, the MZO hypothesis posits that lineages also originate in temperate environments and readily colonize similar environments in the tropical highlands, leading to lower phylogenetic diversity at lower latitudes and elevations. We tested these phylogenetic predictions using a combination of computer simulations and empirical analyses of tree communities in 245 forest plots located in six countries across the tropical and subtropical Andes. We estimated the phylogenetic diversity for each plot and regressed it against elevation and latitude. Our simulated and empirical results provide strong support for the MZO hypothesis. Phylogenetic diversity among co-occurring tree species increased with both latitude and elevation, suggesting an important influence on the historical dispersal of lineages with temperate origins into the tropical highlands. The mixing of different floras was likely favored by the formation of climatically suitable corridors for plant migration due to the Andean uplift. Accounting for the evolutionary history of plant communities helps to advance our knowledge of the drivers of tree community assembly along complex climatic gradients, and thus their likely responses to modern anthropogenic climate change.

BED PROTECTION FOR EXTREME STORM SURGE INFLOW THROUGH FAILING SLUICEGATES

At the northern part of The Netherlands the closure dam Afsluitdijk is situated. It is the primary flood defense that closes off Lake IJssel from the Wadden Sea to protect the northern provinces against storm surges. This structure was built in the 1930’s and needed to be improved to withstand the foreseen increase in storm surge conditions and sea level rise. It consists of a 32 km long dam with five discharge sluices for regulating the water level at Lake IJssel. Three of these sluices are located in the west end of the dam and two in the east end. Due to climate change larger discharges are foreseen. Therefore two new sluices were built in between the three old sluices at Den Oever in the west end of the dam to increase the capacity. A new bed protection was designed at Lake IJssel to ensure the stability of the old and new sluices. This bed protection needs to withstand the inflow during the worst case scenario that one sluice does not close during a 45 hour storm surge. This event has a probability of occurrence of 1/1,000,000 per year. During this extreme load case, water flows from the Wadden Sea through the open sluice gates into Lake IJssel. The water level difference is up to 6.6 m. This causes discharges up to 3600 m3/s and currents that are supercritical with speeds up to 9 m/s. Erosion of the bed cannot be prevented entirely with these high velocities. The length of the bed protection is designed large enough to keep the scour hole away from the sluices. The bed protection consists of a structural and a natural part. The natural part was introduced to minimize the length of the structural protection, reducing the construction costs and CO2 footprint. For this design approach the erosion resistant boulder clay layers in the subsoil were taken into account as natural bed protection, ‘Building with Nature’. To achieve the custom made design was a challenge. To predict the flow behavior in combination with the erosion process was extremely complex. This could not be predicted with the conventional formulas and methods. Therefore multiple approaches were used and combined. This resulted in the design being based on the combination of computer simulations, 2D and 3D model tests and calculations with conventional formulas. The structural part of the bed protection has a length of 24 m. The first 19 m is a concrete slab with a sheet pile at the end. The last 5 m consists of grouted rock. The thickness of the concrete slab and grouted rock is 1-1.5 m. This large thickness is required to prevent uplift due to the supercritical flow. Further downstream of this structural bed protection a scour hole will develop. At this location the boulder clay forms the natural part of the bed protection. The expected development of the flow field and geometry of the scour hole during the 45 hour storm surge was determined. The scour resistance of the boulder clay was based on laboratory tests with samples taken on site. This lead to the conclusion that the boulder clay reduces the development of the scour hole enough to ensure the stability of the structural part of the bed protection and the stability of the sluices.

Stability of binary precipitates in Cu-Ni-Si-Cr alloys investigated through active learning

Binary complexes that can be found in copper alloys are investigated in this work through a combination of computer simulations and machine learning. Copper alloys are made of a copper matrix and a combination of single alloying elements in n-ary forms. Due to the coexistence of different types of phases in this matrix, complex regions exist for which information on their precise atomistic structure is missing. In order to uncover such information, we apply active learning and generate moment tensor potentials. This development is based on quantum-mechanical calculations. This approach allows the on-the-fly relaxation of many thousands of potentially novel candidates and check their stability. The ground-state energy of these structures is used to build active learning-generated convex hulls, which are in turn being compared to those from the simulations and the AFLOW database. This procedure provides an insight to additional new stable copper alloy relevant binary complexes. Here, in view of Cu–Ni–Si–Cr alloys, the binary complexes Cu–Si, Ni–Si, Cr–Si, Cr–Ni, Cu–Ni, and Cu–Cr have been investigated. Their stability and the identification of novel stable candidates are discussed based on energetic arguments and the analysis of the respective phonon dispersion. The pipeline followed in this work is able to successfully predict binary phases in Cu–Ni–Si–Cr alloys, specifically for the Cu-Si, Ni–Si, Cr–Ni and Cu–Ni complexes, and to extend the already reported structures in the AFLOW library. In the end, we show the applicability of a predicted Cu–Si stable phase and the developed machine learned potentials at the larger scale of atomistic simulations for the calculation of their mechanical properties and melting behavior. This work provides a computationally efficient framework for material structure prediction and calculation of their properties at a quantum-mechanical accuracy.

Research progress in molecular dynamics of high-performance PBO fibers

This article reviews the application and development of molecular dynamics in the field of poly(p-benzobisoxazole) (PBO) molecules, including the use of molecular dynamics simulations to calculate the theoretical Young’s modulus of PBO molecules and discuss them from the perspective of molecular theory Combine the rotational isomerism state theory with the long molecular dynamics simulation of small fragments to evaluate the limit length of the persistence vector a. The molecular dynamics calculation is used to study the molecular motion behavior of isolated rigid rod molecules such as PBO. Combining computer simulation technology and X-ray diffraction data collected by the imaging board system to analyze the crystal structure of the PBO fiber, and use molecular dynamics and dynamic modeling to establish the PBO/epoxy interface and study its performance.

CFD Modelling and Analysis for Green Environment of Traditional Buildings

With the enhancement of people’s awareness of heritage protection, research communities focusing on the natural ventilation of the layouts of ancient buildings have paid more attention to the planning and protection of these buildings. Based on the relationship between the natural ventilation environment and the layout of the building, we can reduce the adverse effects of energy consumption and outdoor wind, improve the environment and quality around the building, and achieve harmony between humans and nature. In this study, Fluent software was used to simulate the wind environment of Xingguo Temple. The advantages of combining computer simulation software with ancient building protection planning are illustrated by comparing the wind environment before and after the temple reconstruction with Fluent software. Through the simulation of the building’s wind environment, some suggestions are put forward for the early layout of the outdoor environment in the ancient building reconstruction planning area.

Exploration of the anti-liver injury active components of Shaoyao Gancao decoction by network pharmacology and experiments in vivo

BackgroundShaoyao Gancao decoction (SGD), a classic traditional Chinese herbal formula, has been widely used to treat febrile diseases in the clinic for centuries. In recent years, a growing number of studies have found that SGD has a favorable anti-liver injury effect. PurposeIn this study, we want to know the potential active components of SGD treatment in liver injury. Study Design: A novel method combining computer simulation and in vivo experiment was established for the first time and used to investigate this problem. MethodsA network pharmacology was used to explore the active components of SGD treatment in liver injury, and preliminarily verified the results of network pharmacology through molecular docking. To further understand the active compounds of SGD in the treatment of liver injury, we compared the prototypes and metabolites of SGD in healthy rats and rats with liver injury after oral administration. In addition, a UPLC-MS/MS method was developed and successfully applied to investigate the pharmacokinetics of 9 compounds of SGD in healthy and liver injury rats. ResultsIt showed that SGD exerted protective effects against liver injury by the active components of liquiritin and albiflorin, etc. The values of the AUC0–t, AUC0-∞, t1/2, Tmax were significantly different after oral administration of SGD in healthy and liver injury rats. This indicates that the pharmacokinetic study in the pathological state of liver injury can provide more valuable information for guiding clinical medication. ConclusionIn this study, the integration of network pharmacology and experiments in vivo provides a novel strategy to explore active components of TCMs to treat diseases.

Configurational Entropy-Enabled Thermostability of Cell Membranes in Extremophiles: From Molecular Mechanism to Bioinspired Design.

Understanding physicochemical interactions and mechanisms related to the cell membranes of lives under extreme conditions is of essential importance but remains scarcely explored. Here, using a combination of computer simulations and experiments, we demonstrate that the structural integrity and controllable permeability of cell membranes at high temperatures are predominantly directed by configurational entropy emerging from distorted intermolecular organization of bipolar tethered lipids peculiar to the extremophiles. Detailed simulations across multiple scales─from an all-atom exploration of molecular mechanism to a mesoscale examination of its universal nature─suggest that this configurational entropy effect can be generalized to diverse systems, such as block copolymers. This offers biomimetic inspiration for designing heat-tolerant materials based on entropy, as validated by our experiments of synthetic polymers. The findings provide new insight into the basic nature of the mechanism underlying the adaptation of organisms to extreme conditions and might open paths for designed materials inspired by entropic effects in biological systems.

Decreasing the W-Cr solid solution decomposition rate: Theory, modelling and experimental verification

Tungsten-based alloys are essential materials in the nuclear fusion reactors’ development. Particularly, tungsten-chromium single solid solution is interesting for the combination of a good oxidation behaviour and lack of lower-melting-point phases. The W-Cr system has a miscibility gap though and the solid solution within the particular condition is inherently metastable/unstable and tends to decompose forming a Cr-rich phase. In this study, we have combined computer simulations and experimental work to find additional alloying elements to promote the stability of W-Cr solid solution. The results showed that alloying with Ta may result in lowering the stabilising temperature of the alloy, positively affecting the decomposition rate. Experiments performed on a W-Cr-Ta alloy showed prolonged solid solution lifetime when compared to W-Cr alloy. Formation of the third decomposed phase, enriched in Ta, was observed and changes in the chromium diffusion in the alloy were identified to be the governing factor for slowing down the decomposition.

Scaling‐up the biodiversity–ecosystem functioning relationship: the effect of environmental heterogeneity on transgressive overyielding

Knowledge of how biodiversity sustains ecosystem function comes predominantly from studies focused on small spatial scales. Thus, we know relatively little about the role of biodiversity at larger scales of space and time where habitats become increasingly heterogeneous. Efforts to upscale the relationship between biodiversity and function have yielded inconclusive results. Given that increasing habitat heterogeneity is a ubiquitous consequence of increasing spatial scale, we asked: as habitat heterogeneity increases, can single species continue to maintain ecosystem function? Or, does transgressive overyielding (functioning of species mixture divided by the functioning of the highest functioning single species) change with habitat heterogeneity? We addressed this using a combination of computer simulations, an experiment and a meta‐analysis. The three parts followed the same rationale: habitat heterogeneity was increased by aggregating local habitats with different conditions into larger and more heterogeneous landscapes. The computer simulations showed that, on average, transgressive overyielding increased with habitat heterogeneity because monoculture functioning decreased with habitat heterogeneity. We tested this expectation experimentally by varying the strain richness from one to five species across 10800 bacterial communities in five different habitats defined by sub‐inhibitory concentrations of antibiotics. On average, the experimental results concurred with the simulations. We tested the generality of this result using a meta‐analysis of 26 published experiments that manipulated habitat conditions and species richness. This confirmed that transgressive overyielding tended to increase with habitat heterogeneity but only when species were specialised to different habitats and were not inhibited in mixtures by negative species interactions. This was not the case in several experiments used in our meta‐analysis where one species maximised functioning across all habitats, contrary to the assumptions of many ecological models. Our results illustrate the importance of biodiversity at larger spatial scales with more heterogeneity but also highlights contingencies that this pattern depends on.

Quantifying membrane binding and diffusion with fluorescence correlation spectroscopy diffusion laws

Many transient processes in cells arise from the binding of cytosolic proteins to membranes. Quantifying this membrane binding and its associated diffusion in the living cell is therefore of primary importance. Dynamic photonic microscopies, e.g., single/multiple particle tracking, fluorescence recovery after photobleaching, and fluorescence correlation spectroscopy (FCS), enable non-invasive measurement of molecular mobility in living cells and their plasma membranes. However, FCS with a single beam waist is of limited applicability with complex, non-Brownian, motions. Recently, the development of FCS diffusion laws methods has given access to the characterization of these complex motions, although none of them is applicable to the membrane binding case at the moment. In this study, we combined computer simulations and FCS experiments to propose an FCS diffusion law for membrane binding. First, we generated computer simulations of spot-variation FCS (svFCS) measurements for a membrane binding process combined to 2D and 3D diffusion at the membrane and in the bulk/cytosol, respectively. Then, using these simulations as a learning set, we derived an empirical diffusion law with three free parameters: the apparent binding constant KD, the diffusion coefficient on the membrane D2D, and the diffusion coefficient in the cytosol, D3D. Finally, we monitored, using svFCS, the dynamics of retroviral Gag proteins and associated mutants during their binding to supported lipid bilayers of different lipid composition or at plasma membranes of living cells, and we quantified KD and D2D in these conditions using our empirical diffusion law. Based on these experiments and numerical simulations, we conclude that this new approach enables correct estimation of membrane partitioning and membrane diffusion properties (KD and D2D) for peripheral membrane molecules.

Phase equilibrium, dynamics and rheology of phospholipid-ethanol mixtures: a combined molecular dynamics, NMR and viscometry study.

Binary mixtures of ethanol and phospholipids DOPC and DOPE have been investigated in a composition range relevant for topical drug delivery applications. This was done using a combined computer simulation and experimental approach where molecular dynamics simulations of ethanol-lipid mixtures with different compositions were performed. Several key properties including diffusion coefficients, longitudinal relaxation times, and shear viscosity were computed. In addition, diffusion coefficients, viscosities and NMR longitudinal relaxation times were measured experimentally for comparison and in order to validate the results from simulation. Diffusion coefficients and relaxation times obtained from simulations are in good agreement with results from NMR and computed viscosities are in reasonable agreement with viscometry experiments indicating that the simulations provide a realistic description of the ethanol-phospholipid mixtures. Structural changes in the simulated systems were investigated using an analysis based on radial distribution functions. This showed that the structure of ethanol-DOPC mixtures remains essentially unchanged in the investigated concentration range while ethanol-DOPE mixtures undergo structural rearrangements with the tendency for forming small aggregates on the 100 ns time scale consisting of less than 10 lipids. Although our simulations and experiments indicate that no larger aggregates form, they also show that DOPE has stronger aggregation tendency than DOPC. This highlights the importance of the character of the lipid headgroup for lipid aggregation in ethanol and gives new insights into phase equilibrium, dynamics and rheology that could be valuable for the development of advanced topical drug delivery formulations.