Vacuum Evaporation.

n/

Perfluoroalkylated amphiphiles with a morpholinophosphate or a dimorpholinophosphate polar head group

Some previously synthesized (perfluoroalkyl)alkyldimorpholinophosphates, CnF2n+1CmH2mOP(O)-[N(CH2CH2)(2)O](2), were found remarkably to stabilize heat sterilizable water-in-fluorocarbon reverse emulsions and to have a strong proclivity to self-aggregate into microtubular assemblies when dispersed in water. This series has now been extended in order to allow structure-property relationships to be established and product optimization to be achieved. A new series of even more fluorophilic compounds consisting in bis[(perfluoroalkyl)alkyl]monomorpholinophosphates, (CnF2n+1CmH2mO)(2)P(O)N(CH2CH2)(2)O, was also synthesized. Preliminary surfactant activity and biocompatibility data are presented and compared to data obtained with non-fluorinated analogues

Wasserbestimmung nach dem Destillationsverfahren

n/

Is there a difference between surfactant-stabilised and Pickering emulsions?

What measurable physical properties allow one to distinguish surfactant-stabilised from Pickering emulsions? Whereas surfactants influence oil/water interfaces by lowering the oil/water interfacial tension, particles are assumed to have little effect on the interfacial tension. Here we perform interfacial tension (IFT) measurements on three different systems: (1) soybean oil and water with ethyl cellulose nanoparticles (ECNPs), (2) silicone oil and water with the globular protein bovine serum albumin (BSA), and (3) sodium dodecyl sulfate (SDS) solutions and air. The first two systems contain particles, while the third system contains surfactant molecules. We observe a significant decrease in interfacial tension with increasing particle/molecule concentration in all three systems. We analyse the surface tension data using the Gibbs adsorption isotherm and the Langmuir equation of state for the surface, resulting in surprisingly high adsorption densities for the particle-based systems. These seem to behave very much like the surfactant system: the decrease in tension is due to the presence of many particles at the interface, each with an adsorption energy of a few kBT. Dynamic interfacial tension measurements show that the systems are in equilibrium, and that the characteristic time scale for adsorption is much longer for particle-based systems than for surfactants, in line with their size difference. In addition, the particle-based emulsion is shown to be less stable against coalescence than the surfactant-stabilised emulsion. This leaves us with the conclusion that we are not able to make a clear distinction between the surfactant-stabilised and Pickering emulsions

Size Dependence of a Temperature-Induced Solid–Solid Phase Transition in Copper(I) Sulfide

Determination of the phase diagrams for the nanocrystalline forms of materials is crucial for our understanding of nanostructures and the design of functional materials using nanoscale building blocks. The ability to study such transformations in nanomaterials with controlled shape offers further insight into transition mechanisms and the influence of particular facets. Here we present an investigation of the size-dependent, temperature-induced solid-solid phase transition in copper sulfide nanorods from low- to high-chalcocite. We find the transition temperature to be substantially reduced, with the high chalcocite phase appearing in the smallest nanocrystals at temperatures so low that they are typical of photovoltaic operation. Size dependence in phase trans- formations suggests the possibility of accessing morphologies that are not found in bulk solids at ambient conditions. These other- wise-inaccessible crystal phases could enable higher-performing materials in a range of applications, including sensing, switching, lighting, and photovoltaics

Inferring single-trial neural population dynamics using sequential auto-encoders

Neuroscience is experiencing a revolution in which simultaneous recording of thousands of neurons is revealing population dynamics that are not apparent from single-neuron responses. This structure is typically extracted from data averaged across many trials, but deeper understanding requires studying phenomena detected in single trials, which is challenging due to incomplete sampling of the neural population, trial-to-trial variability, and fluctuations in action potential timing. We introduce latent factor analysis via dynamical systems, a deep learning method to infer latent dynamics from single-trial neural spiking data. When applied to a variety of macaque and human motor cortical datasets, latent factor analysis via dynamical systems accurately predicts observed behavioral variables, extracts precise firing rate estimates of neural dynamics on single trials, infers perturbations to those dynamics that correlate with behavioral choices, and combines data from non-overlapping recording sessions spanning months to improve inference of underlying dynamics

TRAITÉ DE LA FABRICATION DES LIQUEURS ET DE LA DISTILLATION DES ALCOOLS.

n/