![]() Time-resolved X-ray diffraction measurement of the temperature and temperature gradients in silicon during pulsed laser annealing. X-rays generated by femtosecond laser-produced plasmas.in Ultrafast Phenomena VIII (Springer, Berlin, (1993)).Ĭhukhovskii, F. Ultrafast X-ray pulses from laser-produced plasmas. Efficient KαX-ray source from femtosecond laser-produced plasmas. Femtosecond X-ray pulses at 0.4 Å generated by 90° Thomson scattering: a tool for probing the structural dynamics of materials. ![]() Time-resolved X-ray diffraction from laser-excited crystals.in Application of High Field & Short Wavelength Soources (Plenum, New York, in the press). A strong decrease in intensity is seen within a picosecond of heating, resulting from disorder introduced to the layers of cadmium atoms before thermal expansion of the film (which ultimately leads to its destruction) has time to occur. We have studied the response of a Langmuir–Blodgett multilayer film of cadmium arachidate to laser heating by observing changes in the intensity of one Bragg peak for different delays between the perturbing optical pulse and the X-ray probe pulse. Here we show that changes in the X-ray diffraction pattern from an organic film heated by a laser pulse can be monitored on a timescale of less than a picosecond. But these techniques probe only electronic states, whereas time-resolved crystallography should be able to directly monitor atomic positions. Biological processes that can be initiated optically have been studied extensively by ultrafast infrared, visible and ultraviolet spectroscopy 1. An ultimate goal is to study the structure of transient states with a time resolution shorter than the typical period of vibration along a reaction coordinate (around 100 fs). Journal of Controlled Release 285 (2018) 35-45.The extension of time-resolved X-ray diffraction to the subpicosecond domain is an important challenge, as the nature of chemical reactions and phase transitions is determined by atomic motions on these timescales. Image adapted from reference: Claudia Conte, Francesca Mastrotto, Vincenzo Taresco, Aleksandra Tchoryk, Fabiana Quaglia, Snjezana Stolnik, Cameron Alexander. The colloidal stability of RR-NPs was lower than that of nRR-NPs under the different in vitro reducing conditions tested. ![]() with and without L-glutathione reduced (GSH) and dithiothreitol (DTT) are also shown. Size distribution curves of RRNPs and nRR-NPs nanoparticles incubated at 37☌ (30 min) in PBS and under different in vitro reducing conditions i.e. Both RRNPs and nRR-NPs had D H around 120 nm, low size PI and high negative zeta potential values thus both nps had similar colloidal properties. Bar graphs show particle size analysis (hydrodynamic diameter (D H) and polydispersity index (PI)) and zeta potential measurements of unloaded nanoparticles in water. ![]() Characterisation was carried out using a Zetasizer Nano ZS (Malvern Panalytical) instrument. For comparison, non redox-responsive nanoparticles PLGA-PEG nanoparticles (nRR-NPs) were also prepared. The RR-NPs were designed to change surface properties when entering tumour microenvironments, which would in turn enhance their cell internalisation and delivery of drug cargo. Redox-responsive PLGA (poly(lactic-co-glycolic acid)) - PEG (polyethylene glycol) nanoparticles (RR-NPs) were synthesised in a study aimed at developing programmable carrier nanoparticles for drug delivery into lung cancer tumour cells. Image 2: Size and zeta potential characterization of nanoparticles designed for drug deliveryĪn important step in the design of drug carrier nanoparticles is characterisation of particles size and surface change in appropriate environments. Limo, ISAC, School of Pharmacy, University of Nottingham The two population sizes were identified with the 22 nm nps being the major/main population by number (%) distribution in the mixture.įigure courtesy of Marion J. The particle size characterisation was carried out using a DynaPro Plate Reader II (Wyatt) instrument. Large particles scatter much more light than smaller particles, thus the intensity (%) through to number (%) distributions may vary as shown in the exemplar data collected from a mixture of 22 and 200 nm polystyrene nanoparticles. This is especially important where mixed population sizes are present. The figure above illustrates how a comparison of the different distributions gives a better understanding of the sample population. The distribution of particle sizes obtained from DLS measurements is fundamentally an intensity (%) distribution which can also be converted theoretically into volume (%) and number (%) distribution. Image 1: Size analysis of a mixture of polystyrene nanoparticles
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