Investigation of Local Dynamics on the Sub-micron Scale in Organic Blends Using an Ultrafast Confocal Microscope

2010 ◽  
Vol 1270 ◽  
Author(s):  
Giulia Grancini ◽  
Dario Polli ◽  
Jenny Clark ◽  
Tersilla Virgili ◽  
Giulio Cerullo ◽  
...  
Keyword(s):  
Excited State ◽  
Confocal Microscopy ◽  
Polymer Blends ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Electronic States ◽  
Pump Probe ◽  
Peculiar Behaviour ◽  
Spatio Temporal ◽  
Probe Spectroscopy

AbstractWe introduce a novel instrument combining femtosecond pump-probe spectroscopy and confocal microscopy for spatio-temporal imaging of excited-state dynamics of phase-separated polymer blends. Phenomena occurring at interfaces between different materials are crucial for optimizing the device performances, but are poorly understood due to the variety of possible electronic states and processes involved and to their complicated dynamics. Our instrument (with 200-fs temporal resolution and 300-nm spatial resolution) provides new insights into the properties of polymer blends, revealing spatially variable photo-relaxation paths and dynamics and highlighting a peculiar behaviour at the interface between the phase-separated domains.

Integration of Core-Edge Spectroscopy Methods for the Study of Polymers

1996 ◽  
Vol 54 ◽  
pp. 154-155
Author(s):  
E. G. Rightor
Keyword(s):  
Excited State ◽  
Polymer Blends ◽  
Gas Phase ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Electronic States ◽  
Core Electron ◽  
Bulk Solids ◽  
Development Application

Core edge spectroscopy methods are versatile tools for investigating a wide variety of materials. They can be used to probe the electronic states of materials in bulk solids, on surfaces, or in the gas phase. This family of methods involves promoting an inner shell (core) electron to an excited state and recording either the primary excitation or secondary decay of the excited state. The techniques are complimentary and have different strengths and limitations for studying challenging aspects of materials. The need to identify components in polymers or polymer blends at high spatial resolution has driven development, application, and integration of results from several of these methods.

scholarly journals Ultrafast dynamics in the excited state of green fluorescent protein (wt) studied by frequency-resolved femtosecond pump-probe spectroscopy

2002 ◽  
Vol 4 (6) ◽  
pp. 1072-1081 ◽  
Author(s):  
Kathrin Winkler ◽  
Jörg Lindner ◽  
Vinod Subramaniam ◽  
Thomas M. Jovin ◽  
Peter Vöhringer
Keyword(s):  
Excited State ◽  
Green Fluorescent Protein ◽  
Fluorescent Protein ◽  
Ultrafast Dynamics ◽  
Pump Probe ◽  
Green Fluorescent ◽  
Probe Spectroscopy

scholarly journals A Simple Spatio–Temporal Data Fusion Method Based on Linear Regression Coefficient Compensation

2020 ◽  
Vol 12 (23) ◽  
pp. 3900
Author(s):  
Bingxin Bai ◽  
Yumin Tan ◽  
Gennadii Donchyts ◽  
Arjen Haag ◽  
Albrecht Weerts
Keyword(s):  
Linear Regression ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Fusion Method ◽  
Temporal Data ◽  
Resolution Image ◽  
Coarse Resolution ◽  
Fine Spatial Resolution ◽  
Spatio Temporal

High spatio–temporal resolution remote sensing images are of great significance in the dynamic monitoring of the Earth’s surface. However, due to cloud contamination and the hardware limitations of sensors, it is difficult to obtain image sequences with both high spatial and temporal resolution. Combining coarse resolution images, such as the moderate resolution imaging spectroradiometer (MODIS), with fine spatial resolution images, such as Landsat or Sentinel-2, has become a popular means to solve this problem. In this paper, we propose a simple and efficient enhanced linear regression spatio–temporal fusion method (ELRFM), which uses fine spatial resolution images acquired at two reference dates to establish a linear regression model for each pixel and each band between the image reflectance and the acquisition date. The obtained regression coefficients are used to help allocate the residual error between the real coarse resolution image and the simulated coarse resolution image upscaled by the high spatial resolution result of the linear prediction. The developed method consists of four steps: (1) linear regression (LR), (2) residual calculation, (3) distribution of the residual and (4) singular value correction. The proposed method was tested in different areas and using different sensors. The results show that, compared to the spatial and temporal adaptive reflectance fusion model (STARFM) and the flexible spatio–temporal data fusion (FSDAF) method, the ELRFM performs better in capturing small feature changes at the fine image scale and has high prediction accuracy. For example, in the red band, the proposed method has the lowest root mean square error (RMSE) (ELRFM: 0.0123 vs. STARFM: 0.0217 vs. FSDAF: 0.0224 vs. LR: 0.0221). Furthermore, the lightweight algorithm design and calculations based on the Google Earth Engine make the proposed method computationally less expensive than the STARFM and FSDAF.

scholarly journals Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring

2018 ◽  
Vol 10 (12) ◽  
pp. 1950 ◽  
Author(s):  
Luca Cenci ◽  
Luca Pulvirenti ◽  
Giorgio Boni ◽  
Nazzareno Pierdicca
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Added Value ◽  
Sar Images ◽  
Radar Images ◽  
Spatio Temporal ◽  
Set Up ◽  
The Impact ◽  
Hydrological Applications

The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.

Excited State Phononic Processes in Semiconductor Nanocrystals Revealed by Excitonic State-Resolved Pump/Probe Spectroscopy

2019 ◽  
Vol 123 (6) ◽  
pp. 3868-3875 ◽  
Author(s):  
Brenna R. Walsh ◽  
Colin Sonnichsen ◽  
Timothy G. Mack ◽  
Jonathan I. Saari ◽  
Michael M. Krause ◽  
...  
Keyword(s):  
Excited State ◽  
Semiconductor Nanocrystals ◽  
Pump Probe ◽  
Excitonic State ◽  
Probe Spectroscopy

Effective temporal resolution in pump-probe spectroscopy with strongly chirped pulses

2010 ◽  
Vol 82 (5) ◽  
Author(s):  
D. Polli ◽  
D. Brida ◽  
S. Mukamel ◽  
G. Lanzani ◽  
G. Cerullo
Keyword(s):  
Temporal Resolution ◽  
Pump Probe ◽  
Chirped Pulses ◽  
Probe Spectroscopy

Full temporal resolution of the two-step photoinduced energy–electron transfer in a fullerene–oligothiophene–fullerene triad using sub-10 fs pump–probe spectroscopy

2001 ◽  
Vol 345 (1-2) ◽  
pp. 33-38 ◽  
Author(s):  
P.A. van Hal ◽  
R.A.J. Janssen ◽  
G. Lanzani ◽  
G. Cerullo ◽  
M. Zavelani-Rossi ◽  
...  
Keyword(s):  
Electron Transfer ◽  
Temporal Resolution ◽  
Energy Electron ◽  
Pump Probe ◽  
Probe Spectroscopy
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