Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat clima...Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.展开更多
The integrated perception capable of detecting and monitoring varieties of activities is one of the ultimate purposes of wearable electronics and intelligent robots.Limited by the space occupation,it lacks practical f...The integrated perception capable of detecting and monitoring varieties of activities is one of the ultimate purposes of wearable electronics and intelligent robots.Limited by the space occupation,it lacks practical feasibility to stack multiple types of single sensors on each other.Herein,a high-sensitivity dual-function capacitive sensor with proximity sensing and pressure sensing is proposed.The fringing electric field can be confined in the proximity-sensitive area by fibrous loop-patterned electrode,leading to more stolen charges when object approaching and thus a high proximity sensitivity.The high-permittivity doped structured dielectric layer reduces the compressive stiffness and enhances the rate of compression-caused increase in the equivalent relative permittivity of the dielectric layer,resulting in a larger increase in capacitance and thus a high pressure sensitivity.The electrodes and dielectric layer together compose the capacitor and act as the sensor without taking up additional space.The decoupling of proximity-sensing and pressure-sensing modes can be achieved by decrease or increase in capacitance.Combined with array distribution and sequential scanning,the sensors can be used for detection of motion trajectory,contour recognition,pressure distribution.展开更多
基金supported by SGC project5 entitled"Mobile Biochar Production for Methane Emission Reduction and Soil Amendment".Grant Agreement#CCR20014supported in part by NSF CBET#1856112supported in part by an F3 R&D GSR Award (Farms Food Future Innovation Initiative (or F3),as funded by US Dept.of Commerce,Economic Development Administration Build Back Better Regional Challenge).
文摘Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.
基金the National Key Research and Development Program of China(No.2021YFB2011500)the National Natural Science Foundation of China(Nos.52025055 and 51905415)+4 种基金Institutional Foundation of The First Affiliated Hospital of Xi’an Jiaotong University,the China Gas Turbine Establishment of Aero Engine Corporation of China(No.GJCZ-2019-0039)the National Postdoctoral Program for Innovative Talents(No.BX20180251)Young Talent Fund of University Association for Science and Technology in Shaanxi,China(No.20200404)Basic Research Program of Natural Science of Shaanxi Province of China(Nos.2019JLM-5 and 2021JLM-42)Shaanxi University Youth Innovation Team.
文摘The integrated perception capable of detecting and monitoring varieties of activities is one of the ultimate purposes of wearable electronics and intelligent robots.Limited by the space occupation,it lacks practical feasibility to stack multiple types of single sensors on each other.Herein,a high-sensitivity dual-function capacitive sensor with proximity sensing and pressure sensing is proposed.The fringing electric field can be confined in the proximity-sensitive area by fibrous loop-patterned electrode,leading to more stolen charges when object approaching and thus a high proximity sensitivity.The high-permittivity doped structured dielectric layer reduces the compressive stiffness and enhances the rate of compression-caused increase in the equivalent relative permittivity of the dielectric layer,resulting in a larger increase in capacitance and thus a high pressure sensitivity.The electrodes and dielectric layer together compose the capacitor and act as the sensor without taking up additional space.The decoupling of proximity-sensing and pressure-sensing modes can be achieved by decrease or increase in capacitance.Combined with array distribution and sequential scanning,the sensors can be used for detection of motion trajectory,contour recognition,pressure distribution.