Search results for "MODY"

showing 10 items of 4576 documents

Dynamics of supercooled confined water measured by deep inelastic neutron scattering

2017

In this paper, we present the results of deep inelastic neutron scattering (DINS) measurements on supercooled water confined within the pores (average pore diameter ~ 20 Å) of a disordered hydrophilic silica matrix obtained through hydrolysis and polycondensation of the alkoxide precursor Tetra-Methyl-Ortho-Silicate via the sol-gel method. Experiments were performed at two temperatures (250 K and 210 K, i.e., before and after the putative liquid–liquid transition of supercooled confined water) on a “wet” sample with hydration h ~ 40% w/w, which is high enough to have water-filled pores but low enough to avoid water crystallization. A virtually “dry” sample at h ~ 7% was also inve…

liquid-liquid transitionMaterials sciencePhysics and Astronomy (miscellaneous)HydrogenThermodynamicschemistry.chemical_element02 engineering and technologyNeutron scatteringKinetic energy01 natural sciencesInelastic neutron scatteringMomentumchemistry.chemical_compoundsilica xerogelconfined water0103 physical sciences010306 general physicsSupercoolingliquid–liquid transitionSettore FIS/07021001 nanoscience & nanotechnologyconfined water; hydrogen mean kinetic energy; liquid–liquid transition; silica xerogel; Physics and Astronomy (miscellaneous)Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)chemistryhydrogen mean kinetic energyAlkoxideWater of crystallization0210 nano-technology
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Experimental evidence for a liquid-liquid crossover in deeply cooled confined water.

2014

International audience; In this work we investigate, by means of elastic neutron scattering, the pressure dependence of mean square displacements (MSD) of hydrogen atoms of deeply cooled water confined in the pores of a three-dimensional disordered SiO 2 xerogel; experiments have been performed at 250 and 210 K from atmospheric pressure to 1200 bar. The " pressure anomaly " of supercooled water (i.e., a mean square displacement increase with increasing pressure) is observed in our sample at both temperatures; however, contrary to previous simulation results and to the experimental trend observed in bulk water, the pressure effect is smaller at lower (210 K) than at higher (250 K) temperatur…

liquid-liquid transitionPhase transitionPACS: 64.70.Ja 64.70.pm 25.40.DnMaterials scienceNeutron diffractionGeneral Physics and AstronomyThermodynamicsNeutron scatteringSettore FIS/03 - Fisica Della MateriaPhase TransitionNuclear magnetic resonanceWater Movementsglass transitionElastic neutron scattering[PHYS.COND]Physics [physics]/Condensed Matter [cond-mat]SupercoolingElastic neutron scattering; calorimetry; glass transition; liquid-liquid transitionAtmospheric pressure[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry Molecular Biology/Structural Biology [q-bio.BM]Calorimetry Differential ScanningWaterSilicon DioxideSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Cold Temperature[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biomolecules [q-bio.BM]Neutron DiffractionModels ChemicalGlass transitioncalorimetryHydrophobic and Hydrophilic InteractionsAmbient pressureBar (unit)HydrogenPhysical review letters
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The boson peak of deeply cooled confined water reveals the existence of a low-temperature liquid-liquid crossover.

2014

International audience; The Boson peak of deeply cooled water confined in the pores of a silica xerogel is studied by inelastic neutron scattering at different hydration levels to separate the contributions from matrix, water on the pore surfaces and "internal" water. Our results reveal that at high hydration level, where the contribution from internal water is dominant, the temperature dependence of the Boson peak intensity shows an inflection point at about 225 K. The complementary use of differential scanning calorimetry to describe the thermodynamics of the system allows identifying the inflection point as the signature of a water liquid-liquid crossover.

liquid-liquid transition[SDV.BBM.BS] Life Sciences [q-bio]/Biochemistry Molecular Biology/Structural Biology [q-bio.BM]CrossovereducationGeneral Physics and Astronomyinelastic neutron scatteringInelastic neutron scatteringSettore FIS/03 - Fisica Della MateriaMatrix (geology)Differential scanning calorimetryPhysical and Theoretical ChemistryPhysics::Atmospheric and Oceanic PhysicsCondensed matter physicsCalorimetry Differential Scanning[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry Molecular Biology/Structural Biology [q-bio.BM]ChemistrySolvationwater anomalieWaterSilicon DioxideSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Cold Temperaturewater anomalies; differential scanning calorimetry; inelastic neutron scattering; liquid-liquid transitionInflection pointChemical physicsThermodynamicsBoson peakdifferential scanning calorimetryGelsPorosityIntensity (heat transfer)
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Termodynaaminen tasapainotila ja lämpöopin pääsäännöt lukio-opetuksessa

2009

Tässä tutkielmassa perehdyttiin lukiolaisten käsityksiin termodynaamisesta tasapainotilasta sekä lämpöopin ensimmäisestä ja toisesta pääsäännöstä. Tasapainotilan käsite on fysiikan tietorakenteen hierarkiassa korkealla, mutta tästä huolimatta nuorten käsityksiä siihen liittyen on tutkittu vain vähän. Ensimmäisen ja toisen pääsäännön ymmärtäminen sekä niiden soveltaminen on havaittu aiempien tutkimusten mukaan ongelmalliseksi vielä korkeakoulutasollakin. Tutkimus suoritettiin oppikirja-analyysin ja oppilaskyselyn avulla. Oppikirja-analyysiss ä tutkittiin kahta Suomen lukioissa käytettävää oppikirjaa, Tammen kustantamaa Fysiikka-kirjaa sekä WSOY:n kustantamaa Physica-kirjaa. Analyysin tavoitt…

lukiolaisettermodynamiikkaoppikirjatlämpötilalämpöfysiikkalämpöoppi
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Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions

2022

We have trained the Extreme Minimum Learning Machine (EMLM) machine learning model to predict chemical potentials of individual conformers of multifunctional organic compounds containing carbon, hydrogen, and oxygen. The model is able to predict chemical potentials of molecules that are in the size range of the training data with a root-mean-square error (RMSE) of 0.5 kcal/mol. There is also a linear correlation between calculated and predicted chemical potentials of molecules that are larger than those included in the training set. Finding the lowest chemical potential conformers is useful in condensed phase thermodynamic property calculations, in order to reduce the number of computationa…

lämpökemiatiheysfunktionaaliteoriapotentiaalienergialaskennallinen kemiaCarbonilmakemiaMachine LearningOxygenkoneoppiminentermodynamiikkaThermodynamicsGeneral Materials ScienceOrganic ChemicalsPhysical and Theoretical Chemistryorgaaniset yhdisteetHydrogenThe Journal of Physical Chemistry Letters
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Thermodiffusion motion of electrically charged nanoparticles

2012

AbstractThe present work deals with experimental studies to examine the theoretical model of thermodiffusion of electrically charged nanoparticles. Three different ionic magnetic colloid samples have been synthesized and profoundly analyzed. The theoretical model is a classical one, based on the calculation of the temperature and the electric potential distribution around nanoparticles. The discrepancy between experimental data and theory turns out not to exceed 20%. We focus on applying different approximations between calculated electrical double layer in the theoretical model and experimental determination of the surface charge density of colloidal particles. We assume this is the main r…

magnetic colloidsWork (thermodynamics)Materials scienceCondensed matter physicssoret coefficientPhysicsQC1-999General Physics and AstronomyIonic bondingMagnetic colloidNanoparticleMotion (geometry)Charge densityelectrically charged nanoparticlesClassical mechanicsColloidal particletermodiffusionElectric potentialOpen Physics
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SPH modeling of blood flow in cerebral aneurysms

Gli aneurismi cerebrali sono dilatazioni patologiche di arterie cerebrali. Queste patologie hanno un intrinseco rischio di rottura con conseguenti emorragie intracraniche. Sebbene i meccanismi di formazione, crescita e rottura degli aneurismi cerebrali non sono ancora del tutto compresi, è comunemente riconosciuto che in questi processi i fattori emodinamici giocano un ruolo molto importante. Le simulazioni numeriche possono fornire utili informazioni sull'emodinamica e possono essere usate per applicazioni cliniche. Nei tradizionali metodi numerici basati su una griglia di calcolo il processo di discretizzazione dei vasi cerebrali sui quali insiste un aneurisma è molto complesso. D’altra p…

mechanical platelet activationSmoothed particle hydrodynamics (SPH)parallel computingHemodynamicsMulti-blockOpen-boundariescerebral aneurysmsPressure Poisson EquationSettore ICAR/01 - Idraulica
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Geometric Aspects of Thermodynamics

2016

This chapter deals with mathematical aspects of thermodynamics most of which will be seen to be primarily of geometrical nature. Starting with a short excursion to differentiable manifolds we summarize the properties of functions, of vector fields and of one-forms on thermodynamic manifolds. This summary centers on exterior forms over Euclidean spaces and the corresponding differential calculus. In particular, one-forms provide useful tools for the analysis of thermodynamics. A theorem by Caratheodory is developed which is closely related to the second law of thermodynamics. The chapter closes with a discussion of systems which depend on two variables and for which there is an interesting a…

media_common.quotation_subjectEuclidean geometryExterior derivativeThermodynamicsDifferential calculusVector fieldSecond law of thermodynamicsCanonical transformationTangent vectorDirectional derivativeMathematicsmedia_common
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Analysis of a viscoelastic phase separation model

2020

A new model for viscoelastic phase separation is proposed, based on a systematically derived conservative two-fluid model. Dissipative effects are included by phenomenological viscoelastic terms. By construction, the model is consistent with the second law of thermodynamics, and we study well-posedness of the model, i.e., existence of weak solutions, a weak-strong uniqueness principle, and stability with respect to perturbations, which are proven by means of relative energy estimates. A good qualitative agreement with mesoscopic simulations is observed in numerical tests.

media_common.quotation_subjectFOS: Physical sciencesSecond law of thermodynamics02 engineering and technologySpace (mathematics)01 natural sciencesStability (probability)ViscoelasticityMathematics - Analysis of PDEs0103 physical sciencesFOS: MathematicsGeneral Materials ScienceStatistical physicsUniqueness010306 general physicsMathematical Physicsmedia_commonPhysicsMesoscopic physicsDynamic structure factorMathematical Physics (math-ph)021001 nanoscience & nanotechnologyCondensed Matter PhysicsDissipative system0210 nano-technologyAnalysis of PDEs (math.AP)
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Identical fits of nonnegative matrix/tensor factorization may correspond to different extracted event-related potentials

2010

Nonnegative Matrix / Tensor factorization (NMF/NTF) have been used in the study of EEG, and the fit (explained variation) is often used to evaluate the performance of a nonnegative decomposition algorithm. However, this parameter only reveals the information derived from the mathematical model and just exhibits the reliability of the algorithms, and the property of EEG can not be reflected. If fits of two algorithms are identical, it is necessary to examine whether the desired components extracted by them are identical too. In order to verify this doubt, we performed NMF and NTF on the same dataset of an auditory event-related potentials (ERPs), and found that the identical fits of NMF and …

medicine.diagnostic_testComponent (thermodynamics)Property (programming)business.industryFeature extractionPattern recognitionElectroencephalographyMatrix decompositionNon-negative matrix factorizationTime–frequency analysismedicineArtificial intelligenceNonnegative matrixbusinessMathematicsThe 2010 International Joint Conference on Neural Networks (IJCNN)
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