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26 results for “cesium”
Precise Lifetime Measurement of the Cesium 5²D₅⸝₂ State
<p>This repository contains data and software related to an experiment in which we determine the lifetime of the cesium 5<sup>2</sup>D<sub>5/2</sub> state using atoms in a vapor cell. More information is available in the following paper:</p> <ul> <li>arXiv:1912.10089</li> </ul> <p>We provide the data and Python scripts for data evaluation in six folders. We zipped these folders with Windows 10 Enterprise, Version 1903. In the following, we describe how to use data and scripts to get the lifetime results published in our paper.</p> <p> </p> <p><strong>Raw Time-Tags</strong></p> <p>Here, we provide the raw measurement data. We perform several experiment cycles. An excitation laser is switched on at the beginning of each cycle. In the middle of the cycle, it is switched off. We use two single-photon counting modules (SPCM): one detects fluorescence photons emitted by the atoms, the other reference light from the excitation laser beam. We record the arrival times of those photons with respect to the beginning of the cycle. These time delays can be used to create a histogram and to determine the lifetime of the cesium 5<sup>2</sup>D<sub>5/2</sub> state.</p> <p>For each measurement, we provide two data files which are encoded in ‘UTF-8’:</p> <ul> <li>‘figx_xxx_reference_time_tags.dat’</li> <li>‘figx_xxx_fluorescence_time_tags.dat’</li> </ul> <p>where ‘figx_xxx’ is a unique tag indicating the figure and point to which this data corresponds in our paper. The ‘figx_xxx_fluorescence_raw_data.dat’ and ‘figx_xxx_reference_raw_data.dat’ files contain the raw time delays in picoseconds of the fluorescence and the reference photons, respectively.</p> <p>We provide raw time delays in the following folders:</p> <ul> <li>‘fig3_time_tags’: The data used in figure 3.</li> <li>‘fig4_time_tags’: The data used in figure 4. This folder has six subfolders, named ‘point_x’, where x indicates to which point of figure 4 the data belongs. The data of the subfolders ‘point_x_y’ was used for points x and y of figure 4 (the time-tags of the fluorescence photons were split into two sub-datasets with equal size).</li> <li>‘fig5_time_tags’: The data underlying figure 5. This folder has subfolders from ‘23C’ to ‘116C’ where the name indicates the temperature in units of °C of the vapor cell during the measurement. Note that the various measurements have different cycle lengths because reabsorption makes the decay of the fluorescence signal longer. For the lifetime value at a temperature of 23 °C, we used the lifetime which we found in figure 4. For some measurements, the time-tags of the reference SPCM are missing because only one SPCM was available for these measurements.</li> </ul> <p> </p> <p><strong>Histograms</strong></p> <p>Since the files of the raw measurement data are large, we also provide histograms of the time tags. For all datasets discussed above, we generated a histogram with a bin length of 5 ns. We save these histograms with the same file name as the files with the raw time tags but with the ending ‘_histo’ instead of ‘_time_tags’, e.g., ‘fig3_fluorescence_histo.dat’ and ‘fig3_reference_histo.dat’.</p> <p>We always provide two file formats:</p> <ul> <li>a data file (.dat), containing rows with the start time of a bin in microseconds, and the number of SPCM counts due to the fluorescence signal until the start of the next bin, separated by a comma. These files are encoded in ‘UTF-8’.</li> <li>a NumPy compressed array format file (.npz), which includes two arrays: The first array is called ‘time’ and contains the starting times of the bins. The second array is called ‘counts’ and includes the corresponding measured number of fluorescence photons per bin. It is possible to load the arrays into a Python script with numpy.load (tested with NumPy version 1.18.1).</li> </ul> <p> </p> <p><strong>Additional Information on the Measurements</strong></p> <p>We provide a JavaScript Object Notation file (.json) for each measurement. These files provide the following information about every measurement: temperature of the cell, number of detected photons, photons per cycle, and the total measurement duration. They are named ‘figx_xxx_info.json’, where ‘figx_xxx’ is the same indicator as discussed in section ‘Raw Time-Tags’.</p> <p> </p> <p><strong>Scripts</strong></p> <p>This folder contains two sample scripts to illustrate how our data can be processed with Python. The first Python script (generate_histograms.py) generates a histogram of the photon arrival times. The second Python script performs a fit in order to determine the lifetime of the cesium 5<sup>2</sup>D<sub>5/2</sub> state. We wrote these scripts with Python 3.6.5. To avoid errors, one should download all zipped folders and extract them to the same folder.</p> <ul> <li>The script ‘generate_histograms.py’ processes the fluorescence photon detection events stored in the folder ‘fig3_time_tags’. The file ‘fig3 _fluorescence_time_tags.dat’ is read into the script, and a histogram is generated. To run the script, the following Python libraries are required: NumPy (version 1.18.1), os (version 0.1.4), and json (version 2.0.9).</li> <li>The script ‘fit_data.py’ loads the file ‘fig3_fluorescence_histogram.npz’ from the folder ‘histograms\ fig3_time_tags’ in NumPy arrays. We perform a least-square fit on the histogram of the fluorescence decay. From the fit, we get the lifetime of the cesium 5<sup>2</sup>D<sub>5/2</sub> state. Optionally, it is possible to print a fit report and to plot the fit with its residuals. The following Python libraries are required to run the script: NumPy (version 1.18.1), os (version 0.1.4), json (version 2.0.9), pyplot from matplotlib (version 3.1.1), and Parameters, ExponentialModel, and ConstantModel from LmFit (version 1.0.0).</li> </ul> <p> </p> <p><strong>Figures</strong></p> <p>In the folder ‘figures’, we provide the values of the points which we used to generate figure 4 and figure 5. For both figures, we made a JavaScript Object Notation file (.json) where the data of every point is stored in a dictionary. This data contains the fit result of the lifetime and the temperature of the measurement. Additionally, it contains the corresponding errors and the units of every value.</p>
Temporal evolution of plutonium concentrations and isotopic ratios, cesium activity concentrations, granulometric parameters and organic matter properties in the Ukedo–Takase Rivers draining the Difficult-To-Return Zone in Fukushima, Japan (2013–2020)
<p>The current dataset was compiled to investigate the temporal evolution of plutonium concentrations, isotopic ratios and radiocesium activity concentrations in flood sediment deposits collected in the Ukedo and Takase Rivers, draining a part of the Difficult-to-Return Zone, in Fukushima Prefecture, from 2013 to 2020. These radionuclides were released in large quantities during the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident that occurred in March 2011 in Northeastern Japan (Steinhauser et al., 2014). Models showed that ~ 80 % of radionuclide releases occurred over the ocean (Mathieu et al., 2018; MEXT, 2011). The radioactive plume is drained by several coastal rivers to the Pacific Ocean, and sediment-bound radionuclide transfers in these rivers are mainly controlled by the occurrence of typhoons and tropical storms (Evrard et al., 2021). The objective of the research relying on the current database is to investigate the temporal changes in Pu signatures that occurred between 2013 and 2020 in flood sediment deposits collected in the Ukedo and the Takase Rivers, and to identify potential factors controlling these changes by the means of statistical approach.</p> <p>The current dataset comprises an Excel file including the variables description, and the data itself.</p>
Data for "Automated analysis of surface facets: the example of cesium telluride"
<p>The AiiDA archives of the high-throughput calculations presented in the paper "Automated analysis of surface facets: the example of cesium telluride".</p> <p>The file "Cs2Te_surfaces_workflows.aiida" contains the actual calculation data and the files with suffix "*.yaml" contain configuration files of the workflows.</p>
Dynamic viscosity of liquid cesium at different temperatures
<p><strong>Dynamic viscosity of liquid cesium at different temperatures</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>This silvery metal with a golden cast is the most reactive and one of the softest of all metals. It melts just above room temperature. It is about half as abundant as lead and 70 times as abundant as silver. The primary difficulty associated with the production of pure cesium is that cesium is always found together with rubidium in nature and is also mixed with other alkali metals. Because cesium and rubidium are very similar chemically, their separation presented numerous problems before the advent of ion-exchange methods and ion-specific complexing agents such as crown ethers. Once pure salts have been prepared, it is a straightforward task to convert them to the free metal. Cesium metal is produced in rather limited amounts because of its relatively high cost. Cesium has application in thermionic power converters that generate electricity directly within nuclear reactors or from the heat produced by radioactive decay. Cesium is difficult to handle because it reacts spontaneously in air. If a metal sample has a large enough surface area, it can burn to form superoxides. Cesium superoxide has a more reddish cast. Cesium is the most electropositive and most alkaline element, and thus, more easily than all other elements, it loses its single valence electron and forms ionic bonds with nearly all the inorganic and organic anions. Rubidium and cesium are miscible in all proportions and have complete solid solubility.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>50 0.598</p> <p>100 0.469</p> <p>150 0.389</p> <p>200 0.334</p> <p>250 0.294</p> <p>300 0.264</p> <p>350 0.24</p> <p>400 0.221</p> <p>450 0.206</p> <p>500 0.192</p> <p>550 0.181</p> <p>600 0.171</p> <p>650 0.163</p> <p>700 0.156</p> <p>750 0.149</p> <p>800 0.143</p> <p>850 0.138</p> <p>900 0.134</p> <p>950 0.129</p> <p>1000 0.125</p> <p>1050 0.122</p> <p>1100 0.119</p> <p>1150 0.116</p> <p>1200 0.113</p> <p>1250 0.11</p> <p>1300 0.108</p> <p>1350 0.106</p> <p>1400 0.104</p> <p>1450 0.102</p> <p>1500 0.1</p> <p>1550 0.098</p> <p>1600 0.097</p> <p>1650 0.095</p> <p>1700 0.094</p> <p>1750 0.092</p> <p>1800 0.091</p> <p>1850 0.090</p> <p>1900 0.089</p> <p>1950 0.088</p> <p>2000 0.086</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Data for "Exploring Cesium-Tellurium phase space via high-throughput calculations beyond the generalized-gradient approximation"
<p>The AiiDA archives of the high-throughput calculations presented in the paper "Exploring Cesium-Tellurium Phase Space via High-Throughput Density-Functional Theory Calculations".</p> <ul> <li>"calc_mp_Cs-Te.aiida" contains the calculations of the structures originating from the Materials Project database.</li> <li>"calc_oqmd_Cs-Te.aiida" contains the calculations of the structures originating from the open quantum materials database.</li> <li>"calc_mp_Cs-Te_manipulated.aiida" contains the calculations of the structures derived from chemically similar structures originating from the Materials Project database.</li> <li>"calc_oqmd_Cs-Te_manipulated.aiida" contains the calculations of the structures derived from chemically similar structures originating from the open quantum materials database.</li> <li>"calc_Cs5Te3_experimental.aiida" contains the calculations of the additional experimental structure added to the dataset.</li> </ul>
Data underlying: Precision Measurement of the Excited State Lande g-factor and Diamagnetic Shift of the Cesium D2 Line
<p>This is the spectroscopic data used in the work "Precision Measurement of the Excited State Lande g-factor and Diamagnetic Shift of the Cesium D2 Line" by Hans Stærkind, Kasper Jensen, Vincent O. Boer, Esben Thade Petersen and Eugene S. Polzik.</p> <p>Scripts for calculations done in the article are also included.</p>
Data underlying: High-Field Optical Cesium Magnetometer for Magnetic Resonance Imaging
<p>This is the data used in the work "High-Field Optical Cesium Magnetometer for Magnetic Resonance Imaging" by Hans Stærkind, Kasper Jensen, Vincent O. Boer, Esben Thade Petersen and Eugene S. Polzik.</p> <p>Scripts for calculations done in the article are also included.</p>
Intraoperative Placement of Cesium-131 Permanent Interstitial Brachytherapy in Head and Neck Cancer
ClinicalTrials.gov study NCT02794675. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Surgical Resection and Intraoperative Cesium-131 Brachytherapy for Head and Neck Cancer
ClinicalTrials.gov study NCT02467738. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Local structure and dynamics in methylammonium, formamidinium and cesium tin(II) mixed−halide perovskites from 119Sn solid−state NMR
<p>Raw and processed NMR data in Bruker Topspin format</p>
Supplementary materials for "Effect of cesium ions on the mycelium growth and zoospores motility in the oomycete Phytophthora infestans" article
<p>This archive contains supplementary materials for Safonov et al. (2020) article.</p> <p>Each of the three subfolders (series a-c) contains data regarding the corresponding series of zoospore tracking experiments: “video fragments” subfolder with analyzed recordings and “excluded regions” subfolder with ROI-files. ROI-files contain ROIs needed to exclude certain parts of a video frame from analysis (for example, if they contain any debris that can be falsely recognized by the program as a zoospore). Each ROI-file corresponds to its video fragment: for example, “excluded regions control 3 mM a” is a ROI-file for “control 3 mM a”.</p>
Cesium-131 Seed Brachytherapy Plus Subtotal Resection for Lung Cancer Patients
ClinicalTrials.gov study NCT01757158. IPD Sharing: NO. Countries: 1. Publications: 0.
Prospective Evaluation of Focal Brachytherapy Using Cesium-131 For Patients With Low Risk Prostate Cancer
ClinicalTrials.gov study NCT02290366. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Observation of Outcomes and Side Effects of Cesium-131 in Combination With External Beam Radiation for the Treatment of Intermediate to High Risk Prostate Cancer
ClinicalTrials.gov study NCT00621413. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Trial Combining Pembrolizumab and Cesium 131 Brachytherapy With Salvage Surgery in HNSCC
ClinicalTrials.gov study NCT04340258. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study of Cesium-131 Brachytherapy Following Sub-Lobar Resection for Early Stage Non Small Cell Lung Cancer
ClinicalTrials.gov study NCT01237171. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Mouse blood gene expression after administration of 137 Cesium
GEO Series GSE118616. Mus musculus. 152 samples. Type: Expression profiling by array.
IceBridge Scintrex CS-3 Cesium Magnetometer L1B Geolocated Magnetic Anomalies, Version 1
This data set contains magnetic field readings taken over Greenland using the Scintrex CS-3 Cesium Magnetometer instrument. The data were collected as part of Operation IceBridge funded aircraft survey campaigns.
IceBridge Scintrex CS-3 Cesium Magnetometer L0 Raw Magnetic Field, Version 1
This data set contains magnetic field readings and fluxgate values taken over Greenland using the Scintrex CS-3 Cesium Magnetometer. The data were collected as part of Operation IceBridge funded aircraft survey campaigns.
IceBridge Geometrics 823A Cesium Magnetometer L0 Raw Magnetic Field, Version 1
This data set contains magnetic field readings taken over Antarctica using the Geometrics 823 Sensor/Magnetometer. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC), with additional support from NASA Operation IceBridge.
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