Study on the Graphite-Based Cementitious Material for the Soil Moisture Detective Probe

2011 ◽  
Vol 328-330 ◽  
pp. 1627-1631 ◽  
Author(s):  
Li Yao ◽  
Xiao Chu Liu ◽  
Hua Long Wu ◽  
Wen Xiong Li
Keyword(s):  
Mechanical Properties ◽  
Soil Moisture ◽  
Irrigation System ◽  
Cementitious Material ◽  
Metal Material ◽  
Conductive Properties ◽  
Probe Material

Soil moisture detective probe is an important part of automatic irrigation system. Soil moisture probe is usually made of metal material which is easy to be corroded and passivated as long-term working in the damp soil, especially containing acid, alkali and salt. We developed a new soil moisture probe material - the graphite-based cementitious material. The mechanical properties and the conductive properties of the material were tested and we found the graphite-based cementitious material which contains 30% to 50% of graphite could be an applicable material for the soil moisture probe.

Effect of Red Mud on Mechanical Properties of Loess–Containing Aluminosilicate Based Cementitious Materials

2009 ◽  
Vol 610-613 ◽  
pp. 155-160
Author(s):  
Jian Hua Wan ◽  
Heng Hu Sun ◽  
Ying Ying Wang ◽  
Chao Li
Keyword(s):  
Mechanical Properties ◽  
Red Mud ◽  
Cementitious Materials ◽  
Cementitious Material ◽  
The Other ◽  
Term Strength ◽  
Other Hand ◽  
Early Strength ◽  
The One

The effect of the thermal treated red mud on mechanical properties of loess –containing aluminosilicate based cementitious materials is investigated. And the characteristic of hydration production is tested using XRD, SEM and EDAX methods. The results show that the thermal treated red mud not only has excellent cementitious properties but also can improve the mechanical properties of loess –containing aluminosilicate based cementitious materials. Moreover when the content of red mud is 5%, the improved effect is optimal. On the one hand, the alkaline ingredients of red mud can promote abundant ettringites to produce at early ages. And the ettringites contribute to early strength of the cementitious material. On the other hand, the content of red mud is too high to improve the long-term strength.

Soil Moisture based Automatic Irrigation System to Improve Water Productivity

2020 ◽  
Vol 7 (04) ◽  
Author(s):  
PRADEEP H K ◽  
JASMA BALASANGAMESHWARA ◽  
K RAJAN ◽  
PRABHUDEV JAGADEESH
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Content ◽  
Irrigation System ◽  
Water Productivity ◽  
Vital Role ◽  
Agricultural Water Management ◽  
Water Management System ◽  
Proposed Model ◽  
Crop Growth Stage ◽  
Experimental Findings

Irrigation automation plays a vital role in agricultural water management system. An efficient automatic irrigation system is crucial to improve crop water productivity. Soil moisture based irrigation is an economical and efficient approach for automation of irrigation system. An experiment was conducted for irrigation automation based on the soil moisture content and crop growth stage. The experimental findings exhibited that, automatic irrigation system based on the proposed model triggers the water supply accurately based on the real-time soil moisture values.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Mechanical Properties of Cement-Treated Soil Mixed with Cellulose Nanofibre

2021 ◽  
Vol 11 (14) ◽  
pp. 6425
Author(s):  
Hidenori Takahashi ◽  
Shinya Omori ◽  
Hideyuki Asada ◽  
Hirofumi Fukawa ◽  
Yusuke Gotoh ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Flexural Strength ◽  
Geotechnical Engineering ◽  
Strength Development ◽  
Soft Ground ◽  
Wood Cellulose ◽  
Treated Soil ◽  
Made In ◽  
Cement Treatment

Cellulose nanofibre (CNF), a material composed of ultrafine fibres of wood cellulose fibrillated to nano-order level, is expected to be widely used because of its excellent properties. However, in the field of geotechnical engineering, almost no progress has been made in the development of techniques for using CNFs. The authors have focused on the use of CNF as an additive in cement treatment for soft ground, where cement is added to solidify the ground, because CNF can reduce the problems associated with cement-treated soil. This paper presents the results of a study on the method of mixing CNF, the strength and its variation obtained by adding CNF, and the change in permeability. CNF had the effect of mixing the cement evenly and reducing the variation in the strength of the treated soil. The CNF mixture increased the strength at the initial age but reduced the strength development in the long term. The addition of CNF also increased the flexural strength, although it hardly changed the permeability.

scholarly journals High-strength and fibrous capsule–resistant zwitterionic elastomers

2021 ◽  
Vol 7 (1) ◽  
pp. eabc5442
Author(s):  
Dianyu Dong ◽  
Caroline Tsao ◽  
Hsiang-Chieh Hung ◽  
Fanglian Yao ◽  
Chenjue Tang ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Mechanical Strength ◽  
High Strength ◽  
Design Principles ◽  
Fibrous Capsule ◽  
High Mechanical Strength ◽  
Capsule Formation ◽  
Locking Mechanism ◽  
Fibrous Capsule Formation

The high mechanical strength and long-term resistance to the fibrous capsule formation are two major challenges for implantable materials. Unfortunately, these two distinct properties do not come together and instead compromise each other. Here, we report a unique class of materials by integrating two weak zwitterionic hydrogels into an elastomer-like high-strength pure zwitterionic hydrogel via a “swelling” and “locking” mechanism. These zwitterionic-elastomeric-networked (ZEN) hydrogels are further shown to efficaciously resist the fibrous capsule formation upon implantation in mice for up to 1 year. Such materials with both high mechanical properties and long-term fibrous capsule resistance have never been achieved before. This work not only demonstrates a class of durable and fibrous capsule–resistant materials but also provides design principles for zwitterionic elastomeric hydrogels.

scholarly journals Effect of Photoinitiator on Precursory Stability and Curing Depth of Thiol-Ene Clickable Gelatin

Polymers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1877
Author(s):  
Kai-Hung Yang ◽  
Gabriella Lindberg ◽  
Bram Soliman ◽  
Khoon Lim ◽  
Tim Woodfield ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Visible Light ◽  
Rheological Properties ◽  
Swelling Ratio ◽  
Sodium Persulfate ◽  
Photo Polymerization ◽  
Gelation Kinetics ◽  
The Stability ◽  
Over Time

Recent advances highlight the potential of photopolymerizable allylated gelatin (GelAGE) as a versatile hydrogel with highly tailorable properties. It is, however, unknown how different photoinitiating system affects the stability, gelation kinetics and curing depth of GelAGE. In this study, sol fraction, mass swelling ratio, mechanical properties, rheological properties, and curing depth were evaluated as a function of time with three photo-initiating systems: Irgacure 2959 (Ig2959; 320–500 nm), lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP; 320–500 nm), and ruthenium/sodium persulfate (Ru/SPS; 400–500 nm). Results demonstrated that GelAGE precursory solutions mixed with either Ig2959 or LAP remained stable over time while the Ru/SPS system enabled the onset of controllable redox polymerization without irradiation during pre-incubation. Photo-polymerization using the Ru/SPS system was significantly faster (<5 s) compared to both Ig2959 (70 s) and LAP (50 s). Plus, The Ru/SPS system was capable of polymerizing a thick construct (8.88 ± 0.94 mm), while Ig2959 (1.62 ± 0.49 mm) initiated hydrogels displayed poor penetration depth with LAP (7.38 ± 2.13 mm) in between. These results thus support the use of the visible light based Ru/SPS photo-initiator for constructs requiring rapid gelation and a good curing depth while Ig2959 or LAP can be applied for photo-polymerization of GelAGE materials requiring long-term incubation prior to application if UV is not a concern.

scholarly journals Electrospun PCL Patches with Controlled Fiber Morphology and Mechanical Performance for Skin Moisturization via Long-Term Release of Hemp Oil for Atopic Dermatitis

Membranes ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 26
Author(s):  
Sara Metwally ◽  
Daniel P. Ura ◽  
Zuzanna J. Krysiak ◽  
Łukasz Kaniuk ◽  
Piotr K. Szewczyk ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Atopic Dermatitis ◽  
Mechanical Performance ◽  
Antibacterial Properties ◽  
Skin Condition ◽  
Fiber Morphology ◽  
Suitable Material ◽  
Hemp Oil ◽  
Skin Moisture

Atopic dermatitis (AD) is a chronic, inflammatory skin condition, caused by wide genetic, environmental, or immunologic factors. AD is very common in children but can occur at any age. The lack of long-term treatments forces the development of new strategies for skin regeneration. Polycaprolactone (PCL) is a well-developed, tissue-compatible biomaterial showing also good mechanical properties. In our study, we designed the electrospun PCL patches with controlled architecture and topography for long-term release in time. Hemp oil shows anti-inflammatory and antibacterial properties, increasing also the skin moisture without clogging the pores. It can be used as an alternative cure for patients that do not respond to traditional treatments. In the study, we tested the mechanical properties of PCL fibers, and the hemp oil spreading together with the release in time measured on skin model and human skin. The PCL membranes are suitable material as patches or bandages, characterized by good mechanical properties and high permeability. Importantly, PCL patches showed release of hemp oil up to 55% within 6 h, increasing also the skin moisture up to 25%. Our results confirmed that electrospun PCL patches are great material as oil carriers indicating a high potential to be used as skin patches for AD skin treatment.

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

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