Machine Learning Assisted Multi-Functional Graphene-Based Harmonic Sensors

Hajizadegan, Mehdi; Sakhdari, Maryam; Abbasi, Samira; Chen, Pai‐Yen

doi:10.1109/jsen.2020.3046455

Cited by 11 publications

(8 citation statements)

References 27 publications

(31 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The integration of multiple sensors into one platform is often linked with significant increases in energy consumption and decreases in stability and reliability, while the sensing platform also suffers from signal interferences among the multiple sensing elements . Recently, some multifunctional sensors based on a single sensing element and machine learning have been developed. − However, how to detect multiple environmental parameters simultaneously using a single element is still a challenge.…”

mentioning

confidence: 99%

Machine Learning-Assisted Multifunctional Environmental Sensing Based on a Piezoelectric Cantilever

Liu

Zhu

et al. 2022

ACS Sens.

View full text Add to dashboard Cite

Multifunctional environmental sensing is crucial for various applications in agriculture, pollution monitoring, and disease diagnosis. However, most of these sensing systems consist of multiple sensors, leading to significantly increased dimensions, energy consumption, and structural complexity. They also often suffer from signal interferences among multiple sensing elements. Herein, we report a multifunctional environmental sensor based on one single sensing element. A MoS 2 film was deposited on the surface of a piezoelectric microcantilever (300 × 1000 μm 2 ) and used as both a sensing layer and top electrode to make full use of the changes in multiple properties of MoS 2 after its exposure to various environments. The proposed sensor has been demonstrated for humidity detection and achieved high resolution (0.3% RH), low hysteresis (5.6%), and fast response (1 s) and recovery (2.8 s). Based on the analysis of the magnitude spectra for transmission using machine learning algorithms, the sensor accurately quantifies temperatures and CO 2 concentrations in the interference of humidity with accuracies of 91.9 and 92.1%, respectively. Furthermore, the sensor has been successfully demonstrated for real-time detection of humidity and temperature or CO 2 concentrations for various applications, revealing its great potential in human−machine interactions and health monitoring of plants and human beings.

show abstract

mentioning

confidence: 99%

Machine Learning-Assisted Multifunctional Environmental Sensing Based on a Piezoelectric Cantilever

Liu

Zhu

et al. 2022

ACS Sens.

View full text Add to dashboard Cite

show abstract

“…Machine learning (ML), the branch of artificial intelligence, is defined as computer programs that find hidden correlations and acquire knowledge in large data sets. , ML models are used to provide credible prediction, classification, and decision for complex data, thus being a powerful tool to build smart and high-performance systems. , The most important features of ML are sample categorization, noise reduction, data reprocessing, and object identification/decision. , The workflow presented in Figure summarizes the general processes of ML models designed for material science and the sensing field. , …”

Section: Prototypical Designmentioning

confidence: 99%

“…PCA reduces multidimensional features into primary components. The schematic of the neural network was adapted with permission from ref , which is an open access article distributed under a Creative Commons Attribution 4.0 International License.…”

Section: Prototypical Designmentioning

confidence: 99%

See 1 more Smart Citation

Two-Dimensional Field-Effect Transistor Sensors: The Road toward Commercialization

2022

View full text Add to dashboard Cite

The evolutionary success in information technology has been sustained by the rapid growth of sensor technology. Recently, advances in sensor technology have promoted the ambitious requirement to build intelligent systems that can be controlled by external stimuli along with independent operation, adaptivity, and low energy expenditure. Among various sensing techniques, field-effect transistors (FETs) with channels made of two-dimensional (2D) materials attract increasing attention for advantages such as label-free detection, fast response, easy operation, and capability of integration. With atomic thickness, 2D materials restrict the carrier flow within the material surface and expose it directly to the external environment, leading to efficient signal acquisition and conversion. This review summarizes the latest advances of 2D-materials-based FET (2D FET) sensors in a comprehensive manner that contains the material, operating principles, fabrication technologies, proof-of-concept applications, and prototypes. First, a brief description of the background and fundamentals is provided. The subsequent contents summarize physical, chemical, and biological 2D FET sensors and their applications. Then, we highlight the challenges of their commercialization and discuss corresponding solution techniques. The following section presents a systematic survey of recent progress in developing commercial prototypes. Lastly, we summarize the long-standing efforts and prospective future development of 2D FET-based sensing systems toward commercialization.

show abstract

“…Machine Learning Assisted Multi-Functional Graphene-Based Harmonic Sensors[Hajizadegan et al 2021] S12:PH Watch -Leveraging Pulse Oximeters in Existing Wearables for Reusable, Real-Time Monitoring of PH in Sweat (Demo)[Balaji et al 2019] …”

mentioning

confidence: 99%

Revisão Sistemática em IoT: Sensores Químicos Vestíveis

Araújo

Sgobbi²,

Neto³

et al. 2022

Anais Da X Escola Regional De Informática De Goiás (ERI-GO 2022)

View full text Add to dashboard Cite

As aplicações de saúde têm recebido maior atenção com o uso de Internet das Coisas - IoT, por conta do uso de sensores para o monitoramento remoto, não apenas em ambientes hospitalares, mas também em ambientes domésticos e nas atividades diárias e de rotina. Sensores químicos vestíveis têm sido propostos na área da saúde para o monitoramento contínuo do bem-estar do indivíduo, entretanto, os desafios relacionados à convergência dessas duas áreas ainda necessitam de muita pesquisa para que as soluções sejam efetivamente aplicadas. O objetivo deste artigo é apresentar os resultados de uma revisão sistemática da literatura realizada com o propósito de destacar as aplicações que empregam o uso de sensores químicos vestíveis em contextos de IoT. Os resultados encontrados apresentam vários desafios e questões em aberto de um campo de pesquisa promissor envolvendo IoT e sensores químicos vestíveis.

show abstract

Machine Learning Assisted Multi-Functional Graphene-Based Harmonic Sensors

Cited by 11 publications

References 27 publications

Machine Learning-Assisted Multifunctional Environmental Sensing Based on a Piezoelectric Cantilever

Machine Learning-Assisted Multifunctional Environmental Sensing Based on a Piezoelectric Cantilever

Two-Dimensional Field-Effect Transistor Sensors: The Road toward Commercialization

Revisão Sistemática em IoT: Sensores Químicos Vestíveis

Contact Info

Product

Resources

About