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Scientific Papers
Publications citing the applications of openQCM (by Novaetech S.r.l.) instruments and accessories in scientific research.
The list of scientific papers published on the most important journals showing the usage of openQCM in several scientific fields, such as thin film deposition, chemical sensors, biological research and biosensors.
Because of the large number of publications, we are reorganizing everything by subject areas. This will take some time. Thank you for your patience
2024
Sehit, Ekin; Yao, Guiyang; Battocchio, Giovanni; Radfar, Rahil; Trimpert, Jakob; Mroginski, Maria A; Süssmuth, Roderich; Altintas, Zeynep
In: ACS sensors, 2024.
Abstract | Links | BibTeX | Tags: Antigens, Drinking water, epitope imprinting, in silico-designed epitope-mediated adenovirus receptors, molecular dynamics, Monomers, openQCM Q-1, QCM, QCM sensor, Receptors, sensors, virus detection
@article{sehit2024computationally,
title = {Computationally Designed Epitope-Mediated Imprinted Polymers versus Conventional Epitope Imprints for the Detection of Human Adenovirus in Water and Human Serum Samples},
author = {Ekin Sehit and Guiyang Yao and Giovanni Battocchio and Rahil Radfar and Jakob Trimpert and Maria A Mroginski and Roderich Süssmuth and Zeynep Altintas},
url = {https://pubs.acs.org/doi/full/10.1021/acssensors.3c02374},
doi = {https://doi.org/10.1021/acssensors.3c02374},
year = {2024},
date = {2024-03-15},
urldate = {2024-03-15},
journal = {ACS sensors},
publisher = {ACS Publications},
abstract = {Detection of pathogenic viruses for point-of-care applications has attracted great attention since the COVID-19 pandemic. Current virus diagnostic tools are laborious and expensive, while requiring medically trained staff. Although user-friendly and cost-effective biosensors are utilized for virus detection, many of them rely on recognition elements that suffer major drawbacks. Herein, computationally designed epitope-imprinted polymers (eIPs) are conjugated with a portable piezoelectric sensing platform to establish a sensitive and robust biosensor for the human pathogenic adenovirus (HAdV). The template epitope is selected from the knob part of the HAdV capsid, ensuring surface accessibility. Computational simulations are performed to evaluate the conformational stability of the selected epitope. Further, molecular dynamics simulations are executed to investigate the interactions between the epitope and the different functional monomers for the smart design of eIPs. The HAdV epitope is imprinted via the solid-phase synthesis method to produce eIPs using in silico-selected ingredients. The synthetic receptors show a remarkable detection sensitivity (LOD: 102 pfu mL–1) and affinity (dissociation constant (Kd): 6.48 × 10–12 M) for HAdV. Moreover, the computational eIPs lead to around twofold improved binding behavior than the eIPs synthesized with a well-established conventional recipe. The proposed computational strategy holds enormous potential for the intelligent design of ultrasensitive imprinted polymer binders.},
keywords = {Antigens, Drinking water, epitope imprinting, in silico-designed epitope-mediated adenovirus receptors, molecular dynamics, Monomers, openQCM Q-1, QCM, QCM sensor, Receptors, sensors, virus detection},
pubstate = {published},
tppubtype = {article}
}
Detection of pathogenic viruses for point-of-care applications has attracted great attention since the COVID-19 pandemic. Current virus diagnostic tools are laborious and expensive, while requiring medically trained staff. Although user-friendly and cost-effective biosensors are utilized for virus detection, many of them rely on recognition elements that suffer major drawbacks. Herein, computationally designed epitope-imprinted polymers (eIPs) are conjugated with a portable piezoelectric sensing platform to establish a sensitive and robust biosensor for the human pathogenic adenovirus (HAdV). The template epitope is selected from the knob part of the HAdV capsid, ensuring surface accessibility. Computational simulations are performed to evaluate the conformational stability of the selected epitope. Further, molecular dynamics simulations are executed to investigate the interactions between the epitope and the different functional monomers for the smart design of eIPs. The HAdV epitope is imprinted via the solid-phase synthesis method to produce eIPs using in silico-selected ingredients. The synthetic receptors show a remarkable detection sensitivity (LOD: 102 pfu mL–1) and affinity (dissociation constant (Kd): 6.48 × 10–12 M) for HAdV. Moreover, the computational eIPs lead to around twofold improved binding behavior than the eIPs synthesized with a well-established conventional recipe. The proposed computational strategy holds enormous potential for the intelligent design of ultrasensitive imprinted polymer binders.
Okur, Salih; Hashem, Tawheed; Bogdanova, Evgenia; Hodapp, Patrick; Heinke, Lars; Bräse, Stefan; Wöll, Christof
Optimized Detection of Volatile Organic Compounds Utilizing Durable and Selective Arrays of Tailored UiO-66-X SURMOF Sensors Journal Article
In: ACS sensors, 2024.
Abstract | Links | BibTeX | Tags: Adsorption, Liquids, Metal organic frameworks, openQCM Q-1, QCM-D, sensors, Volatile organic compounds
@article{okur2024optimized,
title = {Optimized Detection of Volatile Organic Compounds Utilizing Durable and Selective Arrays of Tailored UiO-66-X SURMOF Sensors},
author = {Salih Okur and Tawheed Hashem and Evgenia Bogdanova and Patrick Hodapp and Lars Heinke and Stefan Bräse and Christof Wöll},
url = {https://pubs.acs.org/doi/abs/10.1021/acssensors.3c01575},
doi = {https://doi.org/10.1021/acssensors.3c01575},
year = {2024},
date = {2024-02-06},
urldate = {2024-01-01},
journal = {ACS sensors},
publisher = {ACS Publications},
abstract = {Metal–organic frameworks (MOFs), with their well-defined and highly flexible nanoporous architectures, provide a material platform ideal for fabricating sensors. We demonstrate that the efficacy and specificity of detecting and differentiating volatile organic compounds (VOCs) can be significantly enhanced using a range of slightly varied MOFs. These variations are obtained via postsynthetic modification (PSM) of a primary framework. We alter the original MOF’s guest adsorption affinities by incorporating functional groups into the MOF linkers, which yields subtle changes in responses. These responses are subsequently evaluated by using machine learning (ML) techniques. Under severe conditions, such as high humidity and acidic environments, sensor stability and lifespan are of utmost importance. The UiO-66-X MOFs demonstrate the necessary durability in acidic, neutral, and basic environments with pH values ranging from 2 to 11, thus surpassing most other similar materials. The UiO-66-NH2 thin films were deposited on quartz-crystal microbalance (QCM) sensors in a high-temperature QCM liquid cell using a layer-by-layer pump method. Three different, highly stable surface-anchored MOFs (SURMOFs) of UiO-66-X obtained via the PSM approach (X: NH2, Cl, and N3) were employed to fabricate arrays suitable for electronic nose applications. These fabricated sensors were tested for their capability to distinguish between eight VOCs. Data from the sensor array were processed using three distinct ML techniques: linear discriminant (LDA), nearest neighbor (k-NN), and neural network analysis methods. The discrimination accuracies achieved were nearly 100% at high concentrations and over 95% at lower concentrations (50–100 ppm).},
keywords = {Adsorption, Liquids, Metal organic frameworks, openQCM Q-1, QCM-D, sensors, Volatile organic compounds},
pubstate = {published},
tppubtype = {article}
}
Metal–organic frameworks (MOFs), with their well-defined and highly flexible nanoporous architectures, provide a material platform ideal for fabricating sensors. We demonstrate that the efficacy and specificity of detecting and differentiating volatile organic compounds (VOCs) can be significantly enhanced using a range of slightly varied MOFs. These variations are obtained via postsynthetic modification (PSM) of a primary framework. We alter the original MOF’s guest adsorption affinities by incorporating functional groups into the MOF linkers, which yields subtle changes in responses. These responses are subsequently evaluated by using machine learning (ML) techniques. Under severe conditions, such as high humidity and acidic environments, sensor stability and lifespan are of utmost importance. The UiO-66-X MOFs demonstrate the necessary durability in acidic, neutral, and basic environments with pH values ranging from 2 to 11, thus surpassing most other similar materials. The UiO-66-NH2 thin films were deposited on quartz-crystal microbalance (QCM) sensors in a high-temperature QCM liquid cell using a layer-by-layer pump method. Three different, highly stable surface-anchored MOFs (SURMOFs) of UiO-66-X obtained via the PSM approach (X: NH2, Cl, and N3) were employed to fabricate arrays suitable for electronic nose applications. These fabricated sensors were tested for their capability to distinguish between eight VOCs. Data from the sensor array were processed using three distinct ML techniques: linear discriminant (LDA), nearest neighbor (k-NN), and neural network analysis methods. The discrimination accuracies achieved were nearly 100% at high concentrations and over 95% at lower concentrations (50–100 ppm).
2023
Malhotra, Jaskaran Singh; Reichert, Per Holger; Sundberg, Jonas
A Quartz Crystal Resonator Modified with a Metal-Organic Framework for Sensing of Benzene, Ethylbenzene, Toluene and Xylenes in Water Proceedings Article
In: 2023 IEEE SENSORS, pp. 1–4, IEEE 2023.
Abstract | Links | BibTeX | Tags: Adsorption, analyte discrimination, BTEX sensor, Harmonic analysis, metal-organic frameworks, openQCM, QCM, Resonant frequency, Sensitivity, sensors, Stability analysis
@inproceedings{malhotra2023quartz,
title = {A Quartz Crystal Resonator Modified with a Metal-Organic Framework for Sensing of Benzene, Ethylbenzene, Toluene and Xylenes in Water},
author = {Jaskaran Singh Malhotra and Per Holger Reichert and Jonas Sundberg},
url = {https://ieeexplore.ieee.org/abstract/document/10325196},
doi = {https://doi.org/10.1109/SENSORS56945.2023.10325196},
year = {2023},
date = {2023-11-28},
urldate = {2023-11-28},
booktitle = {2023 IEEE SENSORS},
pages = {1--4},
organization = {IEEE},
abstract = {This work describes the use of a quartz crystal microbalance (QCM) based sensor for gravimetric sensing of benzene, toluene, ethylbenzene, and xylenes (BTEX). A film of a Cu-based metal-organic framework (MOF) capable of BTEX adsorption is deposited on the gold electrode of a quartz resonator (10 MHz). The sensor is operated under constant flow of water, simultaneously measuring frequency shifts in multiple harmonics. Introduction of BTEX compounds in the water shifts the frequency, enabling detection. Analysis of deviation in the 3 rd and 5 th harmonics enables discrimination of response from either of the BTEX molecules. The response time further enables understanding of diffusion kinetics of each molecule into the framework.},
keywords = {Adsorption, analyte discrimination, BTEX sensor, Harmonic analysis, metal-organic frameworks, openQCM, QCM, Resonant frequency, Sensitivity, sensors, Stability analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
This work describes the use of a quartz crystal microbalance (QCM) based sensor for gravimetric sensing of benzene, toluene, ethylbenzene, and xylenes (BTEX). A film of a Cu-based metal-organic framework (MOF) capable of BTEX adsorption is deposited on the gold electrode of a quartz resonator (10 MHz). The sensor is operated under constant flow of water, simultaneously measuring frequency shifts in multiple harmonics. Introduction of BTEX compounds in the water shifts the frequency, enabling detection. Analysis of deviation in the 3 rd and 5 th harmonics enables discrimination of response from either of the BTEX molecules. The response time further enables understanding of diffusion kinetics of each molecule into the framework.
Liu, Qiangqiang; Yang, Hua; Chen, Jiankui; Yin, Zhouping
Multi-Frame Super Resolution with Dual Pyramid Multi-Attention Network for Droplet Measurement Journal Article
In: IEEE Transactions on Instrumentation and Measurement, 2023.
Abstract | Links | BibTeX | Tags: Convolution, droplet, Feature extraction, Image restoration, openQCM, QCM, sensors, Superresolution
@article{liu2023multi,
title = {Multi-Frame Super Resolution with Dual Pyramid Multi-Attention Network for Droplet Measurement},
author = {Qiangqiang Liu and Hua Yang and Jiankui Chen and Zhouping Yin},
url = {https://ieeexplore.ieee.org/document/10155258},
doi = {https://doi.org/10.1109/TIM.2023.3287262},
year = {2023},
date = {2023-06-19},
urldate = {2023-06-19},
journal = {IEEE Transactions on Instrumentation and Measurement},
publisher = {IEEE},
abstract = {Accurate visual measurement of micrometer-scale flying droplets in inkjet printing remains a challenge due to low image resolution caused by severe image conditions. Multi-frame super resolution (MFSR) has the potential to break through the measurement bottleneck. However, most existing MFSR methods are not satisfactory in multi-frame information utilization, especially for fast-motion scenes, and they often suffer from detail loss. In this study, focusing on multi-frame information utilization and deep feature extraction, we propose a dual pyramid multi-attention network (DPMAN). First, a dual pyramid deformable alignment (DPDA) module is proposed to deal with diverse motion, which extracts explicit offsets to enhance deformable alignment and perform coarse-to-fine alignment. Then, a gated attention fusion (GAF) module is devised to adaptively aggregate the aligned features to emphasize favorable features. Finally, a residual self-attention reconstruction (RSAR) module based on the multi-stage aggregation self-attention architecture is proposed to extract finer deep features for detail restoration. Experimental results on three benchmark datasets demonstrate that DPMAN achieves state-of-the-art performance. DPMAN is applied to droplet image reconstruction and improves the measurement accuracy from 3.34% to 2.52%.},
keywords = {Convolution, droplet, Feature extraction, Image restoration, openQCM, QCM, sensors, Superresolution},
pubstate = {published},
tppubtype = {article}
}
Accurate visual measurement of micrometer-scale flying droplets in inkjet printing remains a challenge due to low image resolution caused by severe image conditions. Multi-frame super resolution (MFSR) has the potential to break through the measurement bottleneck. However, most existing MFSR methods are not satisfactory in multi-frame information utilization, especially for fast-motion scenes, and they often suffer from detail loss. In this study, focusing on multi-frame information utilization and deep feature extraction, we propose a dual pyramid multi-attention network (DPMAN). First, a dual pyramid deformable alignment (DPDA) module is proposed to deal with diverse motion, which extracts explicit offsets to enhance deformable alignment and perform coarse-to-fine alignment. Then, a gated attention fusion (GAF) module is devised to adaptively aggregate the aligned features to emphasize favorable features. Finally, a residual self-attention reconstruction (RSAR) module based on the multi-stage aggregation self-attention architecture is proposed to extract finer deep features for detail restoration. Experimental results on three benchmark datasets demonstrate that DPMAN achieves state-of-the-art performance. DPMAN is applied to droplet image reconstruction and improves the measurement accuracy from 3.34% to 2.52%.
Malhotra, Jaskaran Singh; Kubus, Mariusz; Pedersen, Kasper Steen; Andersen, Simon Ivar; Sundberg, Jonas
Room-temperature monitoring of CH4 and CO2 using a metal-organic framework-based QCM sensor showing inherent analyte discrimination Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: carbon dioxide, CH4, CO2, Dissipation, metal-organic frameworks, methane, openQCM NEXT, QCM, QCM-D, Quartz Crystal Microbalance, sensors
@article{malhotra2023room,
title = {Room-temperature monitoring of CH4 and CO2 using a metal-organic framework-based QCM sensor showing inherent analyte discrimination},
author = {Jaskaran Singh Malhotra and Mariusz Kubus and Kasper Steen Pedersen and Simon Ivar Andersen and Jonas Sundberg},
url = {https://chemrxiv.org/engage/chemrxiv/article-details/646b938eccabde9f6e2fd280},
doi = {https://doi.org/10.26434/chemrxiv-2023-djhp2},
year = {2023},
date = {2023-05-24},
urldate = {2023-05-24},
abstract = {The detection of methane and carbon dioxide is of growing importance due to their negative impact on global warming. This is true both for environmental monitoring, as well as leak detection in industrial processes. Although solid-state sensors are technologically mature, they have limitations that prohibit their use in certain situations, e.g., explosive atmospheres. Thus, there is a need to develop new types of sensor materials. Herein, we demonstrate a simple, low-cost metal-organic framework-based gas leak detection sensor. The system is based on gravimetric sensing using a quartz crystal microbalance. The quartz crystal is functionalized by layer-by-layer growth of a thin metal-organic framework film. This film shows selective uptake of methane or carbon dioxide under atmospheric conditions. The hardware has low cost, simple operation, and theoretically high sensitivity. Overall, the sensor is characterized by simplicity and high robustness. Furthermore, by exploiting the different adsorption kinetics as measured by multiple harmonics analyses, it is possible to discriminate whether the response is due to methane or carbon dioxide. In summary, we demonstrate data relevant towards new applications of metal-organic frameworks and microporous hybrid materials in sensing applications.},
keywords = {carbon dioxide, CH4, CO2, Dissipation, metal-organic frameworks, methane, openQCM NEXT, QCM, QCM-D, Quartz Crystal Microbalance, sensors},
pubstate = {published},
tppubtype = {article}
}
The detection of methane and carbon dioxide is of growing importance due to their negative impact on global warming. This is true both for environmental monitoring, as well as leak detection in industrial processes. Although solid-state sensors are technologically mature, they have limitations that prohibit their use in certain situations, e.g., explosive atmospheres. Thus, there is a need to develop new types of sensor materials. Herein, we demonstrate a simple, low-cost metal-organic framework-based gas leak detection sensor. The system is based on gravimetric sensing using a quartz crystal microbalance. The quartz crystal is functionalized by layer-by-layer growth of a thin metal-organic framework film. This film shows selective uptake of methane or carbon dioxide under atmospheric conditions. The hardware has low cost, simple operation, and theoretically high sensitivity. Overall, the sensor is characterized by simplicity and high robustness. Furthermore, by exploiting the different adsorption kinetics as measured by multiple harmonics analyses, it is possible to discriminate whether the response is due to methane or carbon dioxide. In summary, we demonstrate data relevant towards new applications of metal-organic frameworks and microporous hybrid materials in sensing applications.
Rohman, Yadi Mulyadi; Sukowati, Riris; Priyanto, Aan; Hapidin, Dian Ahmad; Edikresnha, Dhewa; Khairurrijal, Khairurrijal
Quartz Crystal Microbalance Coated with Polyacrylonitrile/Nickel Nanofibers for High-Performance Methanol Gas Detection Journal Article
In: ACS Omega, 2023.
Abstract | Links | BibTeX | Tags: Alcohols, Nanofibers, nanoparticles, Nickel, openQCM Wi2, QCM, Quartz Crystal Microbalance, sensors
@article{rohman2023quartz,
title = {Quartz Crystal Microbalance Coated with Polyacrylonitrile/Nickel Nanofibers for High-Performance Methanol Gas Detection},
author = {Yadi Mulyadi Rohman and Riris Sukowati and Aan Priyanto and Dian Ahmad Hapidin and Dhewa Edikresnha and Khairurrijal Khairurrijal},
url = {https://pubs.acs.org/doi/full/10.1021/acsomega.3c00760},
doi = {https://doi.org/10.1021/acsomega.3c00760},
year = {2023},
date = {2023-03-29},
urldate = {2023-01-01},
journal = {ACS Omega},
publisher = {ACS Publications},
abstract = {This study describes a sensor based on quartz crystal microbalance (QCM) coated by polyacrylonitrile (PAN) nanofibers containing nickel nanoparticles for methanol gas detection. The PAN/nickel nanofibers composites were made via electrospinning and electrospray methods. The QCM sensors coated with the PAN/nickel nanofiber composite were evaluated for their sensitivities, selectivities, and stabilities. The morphologies and elemental compositions of the sensors were examined using a scanning electron microscope-energy dispersive X-ray. A Fourier Transform Infrared spectrometer was used to investigate the elemental bonds within the nanofiber composites. The QCM sensors coated with PAN/nickel nanofibers offered a high specific surface area to enhance the QCM sensing performance. They exhibited excellent sensing characteristics, including a high sensitivity of 389.8 ± 3.8 Hz/SCCM, response and recovery times of 288 and 251 s, respectively, high selectivity for methanol compared to other gases, a limit of detection (LOD) of about 1.347 SCCM, and good long-term stability. The mechanism of methanol gas adsorption by the PAN/nickel nanofibers can be attributed to intermolecular interactions, such as the Lewis acid–base reaction by PAN nanofibers and hydrogen bonding by nickel nanoparticles. The results suggest that QCM-coated PAN/nickel nanofiber composites show great potential for the design of highly sensitive and selective methanol gas sensors.},
key = {Alcohols,Nanofibers,Nanoparticles,Nickel,Sensors},
keywords = {Alcohols, Nanofibers, nanoparticles, Nickel, openQCM Wi2, QCM, Quartz Crystal Microbalance, sensors},
pubstate = {published},
tppubtype = {article}
}
This study describes a sensor based on quartz crystal microbalance (QCM) coated by polyacrylonitrile (PAN) nanofibers containing nickel nanoparticles for methanol gas detection. The PAN/nickel nanofibers composites were made via electrospinning and electrospray methods. The QCM sensors coated with the PAN/nickel nanofiber composite were evaluated for their sensitivities, selectivities, and stabilities. The morphologies and elemental compositions of the sensors were examined using a scanning electron microscope-energy dispersive X-ray. A Fourier Transform Infrared spectrometer was used to investigate the elemental bonds within the nanofiber composites. The QCM sensors coated with PAN/nickel nanofibers offered a high specific surface area to enhance the QCM sensing performance. They exhibited excellent sensing characteristics, including a high sensitivity of 389.8 ± 3.8 Hz/SCCM, response and recovery times of 288 and 251 s, respectively, high selectivity for methanol compared to other gases, a limit of detection (LOD) of about 1.347 SCCM, and good long-term stability. The mechanism of methanol gas adsorption by the PAN/nickel nanofibers can be attributed to intermolecular interactions, such as the Lewis acid–base reaction by PAN nanofibers and hydrogen bonding by nickel nanoparticles. The results suggest that QCM-coated PAN/nickel nanofiber composites show great potential for the design of highly sensitive and selective methanol gas sensors.
2022
Xu, Jiexiong
Heavy Metal Detection Methods in Water using Quartz Crystal Microbalance PhD Thesis
Purdue University Graduate School, 2022.
Abstract | Links | BibTeX | Tags: biosensors, environment, ligand binding interactions, Quartz Crystal Microbalance, sensors
@phdthesis{xu2022heavy,
title = {Heavy Metal Detection Methods in Water using Quartz Crystal Microbalance},
author = {Jiexiong Xu},
url = {https://hammer.purdue.edu/articles/thesis/Heavy_Metal_Detection_Methods_in_Water_using_Quartz_Crystal_Microbalance/19684002},
doi = {https://doi.org/10.25394/PGS.19684002.v1},
year = {2022},
date = {2022-05-02},
urldate = {2022-01-01},
school = {Purdue University Graduate School},
abstract = {According to the World Health Organization, long-term exposures to heavy metal toxicants such as arsenic (As) and lead (Pb), even at the parts per billion (ppb, μg/L) level, can cause severe health problems such as cancer, skin lesions, and cardiovascular diseases. Therefore, an accurate and rapid heavy metal toxicant monitoring technique is needed. This research investigated the proof-of-the concept of a portable sensor for detecting As and Pb in water. The sensor system utilized a Quartz Crystal Microbalance - QCM (openQCM w-i2) system interfaced with a computer as the sensing platform. It was further integrated with a peristaltic pump and required tubing to create the integrated sensing system. It used a 10 MHz AT-cut quartz crystal gold electrode as the sensing substrate. For the determination of As in water, dithiothreitol (DTT) was used as the ligand to be deposited on the gold electrode using the Self-assembly-monolayer method (SAM). For the determination of Pb, a combination of ligands (Chitosan, Glutaraldehyde, and lead ionophore II - CGL) was used and deposited on the gold electrode using the spin-coating method. The system was tested for As in water with specific concentrations (0, 50, 100, and 200 ppb) under laboratory conditions. Similarly, the system was tested for Pb in water with different concentrations (0, 10, 25, 50, and 100 ppb) under laboratory conditions. The resulted change of frequency (with respect to time, in seconds) of the QCM system to different concentrations of the individual analyte was recorded. Subsequently, the recorded data were analyzed to determine the correlation model and coefficient of determination, R2. The maximum R2 values for detecting As and Pb were 0.963 and 0.991, respectively. Thus, this proof-of-the-concept study using the developed QCM-based sensing system for detecting As and Pb in water was successful.},
key = {Biosensor, ligand binding interactions, sensors, environment},
keywords = {biosensors, environment, ligand binding interactions, Quartz Crystal Microbalance, sensors},
pubstate = {published},
tppubtype = {phdthesis}
}
According to the World Health Organization, long-term exposures to heavy metal toxicants such as arsenic (As) and lead (Pb), even at the parts per billion (ppb, μg/L) level, can cause severe health problems such as cancer, skin lesions, and cardiovascular diseases. Therefore, an accurate and rapid heavy metal toxicant monitoring technique is needed. This research investigated the proof-of-the concept of a portable sensor for detecting As and Pb in water. The sensor system utilized a Quartz Crystal Microbalance - QCM (openQCM w-i2) system interfaced with a computer as the sensing platform. It was further integrated with a peristaltic pump and required tubing to create the integrated sensing system. It used a 10 MHz AT-cut quartz crystal gold electrode as the sensing substrate. For the determination of As in water, dithiothreitol (DTT) was used as the ligand to be deposited on the gold electrode using the Self-assembly-monolayer method (SAM). For the determination of Pb, a combination of ligands (Chitosan, Glutaraldehyde, and lead ionophore II - CGL) was used and deposited on the gold electrode using the spin-coating method. The system was tested for As in water with specific concentrations (0, 50, 100, and 200 ppb) under laboratory conditions. Similarly, the system was tested for Pb in water with different concentrations (0, 10, 25, 50, and 100 ppb) under laboratory conditions. The resulted change of frequency (with respect to time, in seconds) of the QCM system to different concentrations of the individual analyte was recorded. Subsequently, the recorded data were analyzed to determine the correlation model and coefficient of determination, R2. The maximum R2 values for detecting As and Pb were 0.963 and 0.991, respectively. Thus, this proof-of-the-concept study using the developed QCM-based sensing system for detecting As and Pb in water was successful.
2018
Nardo, Armando Di; Gonzalez, David Baquero; Baur, Tom; Bernini, Romeo; Bodini, Sergio; Capasso, Sante; Cascetta, Furio; Castaldo, Francesca; Cocco, Michele; Cousin, Philippe; others,
On-line measuring sensors for smart water network monitoring Journal Article
In: EPiC Series in Engineering, vol. 3, pp. 572–581, 2018.
Abstract | Links | BibTeX | Tags: online monitoring, openQCM, partitioning, protection, sensors, smart management, Smart Water Networks
@article{di2018line,
title = {On-line measuring sensors for smart water network monitoring},
author = {Armando Di Nardo and David Baquero Gonzalez and Tom Baur and Romeo Bernini and Sergio Bodini and Sante Capasso and Furio Cascetta and Francesca Castaldo and Michele Cocco and Philippe Cousin and others},
url = {https://ww.easychair.org/publications/paper/R7Cm},
doi = {https://doi.org/10.29007/4fcr},
year = {2018},
date = {2018-12-20},
urldate = {2018-12-20},
journal = {EPiC Series in Engineering},
volume = {3},
pages = {572--581},
publisher = {EasyChair},
abstract = {Smart cities are getting essential to drive economic growth, increase social prospects and improve high-quality lifestyle for citizens. To meet the goal of smart cities, Information and Communications Technology (ICT) have a key role. The application of smart solutions will allow the cities to use ICT and big data to improve infrastructure and services (i.e. network efficiency, protection from contamination, etc.). In the water sector, the integration of smart meters and sensors coupled with cloud computing and the paradigm of “divide and conquer” introduces a novel and smart management of the water network allowing an efficient online monitoring and transforming the traditional water networks into modern Smart WAter Networks (SWAN). The Ctrl+SWAN (Cloud Technologies & ReaL time monitoring+Smart WAter Network) Action Group (AG) was created within the European Innovation Partnership on Water, in order to promote innovation in the water sector by advancing existing smart solutions. The paper presents an update of a previous work on the state of the art on the best On-line Measuring Sensors (OMS) already available on the market and innovative technologies in the Research and Development (R&D) phases.},
key = {online monitoring, partitioning, protection, sensor, smart management, Smart Water Networks},
keywords = {online monitoring, openQCM, partitioning, protection, sensors, smart management, Smart Water Networks},
pubstate = {published},
tppubtype = {article}
}
Smart cities are getting essential to drive economic growth, increase social prospects and improve high-quality lifestyle for citizens. To meet the goal of smart cities, Information and Communications Technology (ICT) have a key role. The application of smart solutions will allow the cities to use ICT and big data to improve infrastructure and services (i.e. network efficiency, protection from contamination, etc.). In the water sector, the integration of smart meters and sensors coupled with cloud computing and the paradigm of “divide and conquer” introduces a novel and smart management of the water network allowing an efficient online monitoring and transforming the traditional water networks into modern Smart WAter Networks (SWAN). The Ctrl+SWAN (Cloud Technologies & ReaL time monitoring+Smart WAter Network) Action Group (AG) was created within the European Innovation Partnership on Water, in order to promote innovation in the water sector by advancing existing smart solutions. The paper presents an update of a previous work on the state of the art on the best On-line Measuring Sensors (OMS) already available on the market and innovative technologies in the Research and Development (R&D) phases.
