Efficient visible and near-infrared photoluminescent attapulgite-based lanthanide one-dimensional nanomaterials assembled by ion-pairing interactions

2014 ◽  
Vol 43 (21) ◽  
pp. 7903-7910 ◽  
Author(s):  
Jun Xu ◽  
Ye Zhang ◽  
Hao Chen ◽  
Weisheng Liu ◽  
Yu Tang
Keyword(s):  
Near Infrared ◽  
Ion Pairing ◽  
Hybrid Nanomaterials ◽  
One Dimensional ◽  
Pairing Interactions

Efficient photoluminescent attapulgite-based one-dimensional lanthanide hybrid nanomaterials are first fabricated by ion-pairing interactions.

Pyrrole-bridged quinones: π-electronic systems that modulate electronic structures by tautomerism and deprotonation

2021 ◽  
Author(s):  
Shinya Sugiura ◽  
Hiromitsu Maeda
Keyword(s):  
Infrared Absorption ◽  
Electronic Structures ◽  
Near Infrared ◽  
Ion Pairing ◽  
Anion Binding ◽  
Electronic Systems

A new series of π-extended quinone derivatives containing a pyrrole bridge exhibited NH/OH-type tautomerization and anion binding along with deprotonation that induced near-infrared absorption and ion-pairing assemblies.

The length controllable synthesis and near-infrared photoluminescence of one-dimensional ternary Cu4Bi4S9 semiconductor nanobelts

2014 ◽  
Vol 49 ◽  
pp. 180-186 ◽  
Author(s):  
Jing Li ◽  
Xiaoxu wang ◽  
Ruibin Liu ◽  
Lijie shi ◽  
Muhammad Arshad Kamran ◽  
...  
Keyword(s):  
Near Infrared ◽  
Controllable Synthesis ◽  
One Dimensional

scholarly journals Using a One-Dimensional Convolutional Neural Network on Visible and Near-Infrared Spectroscopy to Improve Soil Phosphorus Prediction in Madagascar

2021 ◽  
Vol 13 (8) ◽  
pp. 1519
Author(s):  
Kensuke Kawamura ◽  
Tomohiro Nishigaki ◽  
Andry Andriamananjara ◽  
Hobimiarantsoa Rakotonindrina ◽  
Yasuhiro Tsujimoto ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Near Infrared ◽  
Soil Phosphorus ◽  
Predictive Ability ◽  
Available P ◽  
Accurate Estimation ◽  
One Dimensional ◽  
P Content ◽  
Soil Available P

As a proximal soil sensing technique, laboratory visible and near-infrared (Vis-NIR) spectroscopy is a promising tool for the quantitative estimation of soil properties. However, there remain challenges for predicting soil phosphorus (P) content and availability, which requires a reliable model applicable for different land-use systems to upscale. Recently, a one-dimensional convolutional neural network (1D-CNN) corresponding to the spectral information of soil was developed to considerably improve the accuracy of soil property predictions. The present study investigated the predictive ability of a 1D-CNN model to estimate soil available P (oxalate-extractable P; Pox) content in soils by comparing it with partial least squares (PLS) and random forest (RF) regressions using soil samples (n = 318) collected from natural (forest and non-forest) and cultivated (upland and flooded rice fields) systems in Madagascar. Overall, the 1D-CNN model showed the best predictive accuracy (R2 = 0.878) with a highly accurate prediction ability (ratio of performance to the interquartile range = 2.492). Compared to the PLS model, the RF and 1D-CNN models indicated 4.37% and 23.77% relative improvement in root mean squared error values, respectively. Based on a sensitivity analysis, the important wavebands for predicting soil Pox were associated with iron (Fe) oxide, organic matter (OM), and water absorption, which were previously known wavelength regions for estimating P in soil. These results suggest that 1D-CNN corresponding spectral signatures can be expected to significantly improve the predictive ability for estimating soil available P (Pox) from Vis-NIR spectral data. Rapid and accurate estimation of available P content in soils using our results can be expected to contribute to effective fertilizer management in agriculture and the sustainable management of ecosystems. However, the 1D-CNN model will require a large dataset to extend its applicability to other regions of Madagascar. Thus, further updates should be tested in future studies using larger datasets from a wide range of ecosystems in the tropics.

Corrigendum: Counterion Specificity of Polyelectrolyte Brushes: Role of Specific Ion-Pairing Interactions

ChemPhysChem ◽  
2018 ◽  
Vol 19 (15) ◽  
pp. 1930-1930
Author(s):  
Ran Kou ◽  
Jian Zhang ◽  
Zhen Chen ◽  
Guangming Liu
Keyword(s):  
Ion Pairing ◽  
Polyelectrolyte Brushes ◽  
Pairing Interactions

Separation of ten phosphorylated mono-and disaccharides using HILIC and ion-pairing interactions

2017 ◽  
Vol 972 ◽  
pp. 102-110 ◽  
Author(s):  
Caroline Mathon ◽  
Gregory A. Barding ◽  
Cynthia K. Larive
Keyword(s):  
Ion Pairing ◽  
Pairing Interactions

Slow-Reduction Synthesis of a Thiolate-Protected One-Dimensional Gold Cluster Showing an Intense Near-Infrared Absorption

2015 ◽  
Vol 137 (22) ◽  
pp. 7027-7030 ◽  
Author(s):  
Shinjiro Takano ◽  
Seiji Yamazoe ◽  
Kiichirou Koyasu ◽  
Tatsuya Tsukuda
Keyword(s):  
Infrared Absorption ◽  
Near Infrared ◽  
Gold Cluster ◽  
One Dimensional

scholarly journals Large scale indium tin oxide (ITO) one dimensional gratings for ultrafast signal modulation in the visible spectral region

2020 ◽  
Vol 22 (13) ◽  
pp. 6881-6887 ◽  
Author(s):  
Michele Guizzardi ◽  
Silvio Bonfadini ◽  
Liliana Moscardi ◽  
Ilka Kriegel ◽  
Francesco Scotognella ◽  
...  
Keyword(s):  
Tin Oxide ◽  
Indium Tin Oxide ◽  
Large Scale ◽  
Near Infrared ◽  
Infrared Region ◽  
Visible Spectral Region ◽  
Signal Modulation ◽  
One Dimensional ◽  
Heavily Doped ◽  
Near Infrared Region

Indium tin oxide (ITO) is a heavily doped semiconductor with a plasmonic response in the near infrared region.

Near Infrared High Angular Resolution Observations of Stars and Circumstellar Regions by the Technique of Lunar Occultations

1994 ◽  
Vol 158 ◽  
pp. 376-378
Author(s):  
T. Chandrasekhar ◽  
N. M. Ashok ◽  
Sam Ragland
Keyword(s):  
High Speed ◽  
Near Infrared ◽  
Angular Resolution ◽  
Infrared Region ◽  
High Angular Resolution ◽  
Filter Bandwidth ◽  
One Dimensional ◽  
Near Infrared Region ◽  
System Frequency ◽  
Source Structure

A program of High Angular Resolution observations of stars and their circumstellar regions using the technique of lunar occultations has been initiated at the 1.2 m telescope at Gurushikhar (24°39′ N, 72°47′ E), India. A liquid nitrogen cooled InSb detector based high speed Infrared photometer with millisecond data acquisition capabilities has been developed for the near Infrared region (1–5 μm) and eight occultations have been successfully observed in the K band (2.2 μm). The sources are (IRC No. -10578, +10013, +20034, +30094, +20190, +20200, +20073 and +00198. The diffraction pattern is clearly seen in all the observations. A convolution analysis involving the system frequency response, filter bandwidth and one dimensional source structure has been carried out to fit the data. System capability has been determined to be ~ 6 milliarcseconds.

ChemInform Abstract: One-Dimensional Magnetic Inorganic-Organic Hybrid Nanomaterials

ChemInform ◽  
2011 ◽  
Vol 42 (23) ◽  
pp. no-no
Author(s):  
Jiayin Yuan ◽  
Youyong Xu ◽  
Axel H. E. Mueller
Keyword(s):  
Hybrid Nanomaterials ◽  
One Dimensional ◽  
Organic Hybrid
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