Pub Date : 2017-10-01DOI: 10.1109/PRIMEASIA.2017.8280377
Mutanizam Abdul Mubin, A. Marzuki, M. T. Mustaffa, M. F. Ain, T. Zulkifli
This paper presents the design and simulation of a low-power MedRadio band low noise amplifier (LNA) using standard 0.18 μm CMOS process. This LNA utilizes current reuse and active shunt feedback circuit techniques to achieve (on simulation) very low power operation with gain of more than 18 dB, noise figure of less than 5 dB, and input return loss of more than 10 dB between 401 MHz to 406 MHz MedRadio band. Total power consumption of this LNA is just under 0.6 mW where approximately 0.1 mW is due to the active shunt feedback network. The design and simulation were done in Cadence IC5 with Silterra's 0.18 μm CMOS technology.
{"title":"Design and simulation of a low-power 0.18 μm CMOS MedRadio band LNA","authors":"Mutanizam Abdul Mubin, A. Marzuki, M. T. Mustaffa, M. F. Ain, T. Zulkifli","doi":"10.1109/PRIMEASIA.2017.8280377","DOIUrl":"https://doi.org/10.1109/PRIMEASIA.2017.8280377","url":null,"abstract":"This paper presents the design and simulation of a low-power MedRadio band low noise amplifier (LNA) using standard 0.18 μm CMOS process. This LNA utilizes current reuse and active shunt feedback circuit techniques to achieve (on simulation) very low power operation with gain of more than 18 dB, noise figure of less than 5 dB, and input return loss of more than 10 dB between 401 MHz to 406 MHz MedRadio band. Total power consumption of this LNA is just under 0.6 mW where approximately 0.1 mW is due to the active shunt feedback network. The design and simulation were done in Cadence IC5 with Silterra's 0.18 μm CMOS technology.","PeriodicalId":335218,"journal":{"name":"2017 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia)","volume":"36 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122269094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/PRIMEASIA.2017.8280368
Noor Faezah Ismail, N. A. M. Yunus, N. Sulaiman, M. N. Mohtar, I. Halin, D. Ahmad
The electrowetting (EW) operation was demonstrated to observe the effect of Joule heating and electrolysis. Joule heating is an electrothermal effect, which is induced from the conductivity of electrode that enables the charge to flow through it. Electrolysis is a decomposition of liquid into gas when it is in direct contact with activated electrode. The experiments were conducted using Potassium Chloride, KCl solution. The voltage supply used was in AC and the frequency and voltage were varied. The experiment objective was to see the effect of Joule heating on the flowing of droplet.
{"title":"Joule heating effect on microdroplet electrowetting platform chip","authors":"Noor Faezah Ismail, N. A. M. Yunus, N. Sulaiman, M. N. Mohtar, I. Halin, D. Ahmad","doi":"10.1109/PRIMEASIA.2017.8280368","DOIUrl":"https://doi.org/10.1109/PRIMEASIA.2017.8280368","url":null,"abstract":"The electrowetting (EW) operation was demonstrated to observe the effect of Joule heating and electrolysis. Joule heating is an electrothermal effect, which is induced from the conductivity of electrode that enables the charge to flow through it. Electrolysis is a decomposition of liquid into gas when it is in direct contact with activated electrode. The experiments were conducted using Potassium Chloride, KCl solution. The voltage supply used was in AC and the frequency and voltage were varied. The experiment objective was to see the effect of Joule heating on the flowing of droplet.","PeriodicalId":335218,"journal":{"name":"2017 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126282803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-13DOI: 10.1109/PRIMEASIA.2017.8280366
A. Irmanova, A. P. James
Analog memory is of great importance in neurocomputing technologies field, but still remains difficult to implement. With emergence of memristors in VLSI technologies the idea of designing scalable analog data storage elements finds its second wind. A memristor, known for its history dependent resistance levels, independently can provide blocks of binary or discrete state data storage. However, using single memristor to save the analog value is practically limited due to the device variability and implementation complexity. In this paper, we present a new design of discrete state memory cell consisting of sub-cells constructed from a memristor and its resistive network. A memristor in the sub-cells provides the storage element, while its resistive network is used for programming its resistance. Several sub-cells are then connected in parallel, resembling potential divider configuration. The output of the memory cell is the voltage resulting from distributing the input voltage among the sub-cells. Here, proposed design was programmed to obtain 10 and 27 different output levels depending on the configuration of the combined resistive networks within the sub-cell. Despite the simplicity of the circuit, this realization of multilevel memory provides increased number of output levels compared to previous designs of memory technologies based on memristors. Simulation results of proposed memory are analyzed providing explicit data on the issues of distinguishing discrete analog output levels and sensitivity of the cell to oscillations in write signal patterns.
{"title":"Multi-level memristive memory with resistive networks","authors":"A. Irmanova, A. P. James","doi":"10.1109/PRIMEASIA.2017.8280366","DOIUrl":"https://doi.org/10.1109/PRIMEASIA.2017.8280366","url":null,"abstract":"Analog memory is of great importance in neurocomputing technologies field, but still remains difficult to implement. With emergence of memristors in VLSI technologies the idea of designing scalable analog data storage elements finds its second wind. A memristor, known for its history dependent resistance levels, independently can provide blocks of binary or discrete state data storage. However, using single memristor to save the analog value is practically limited due to the device variability and implementation complexity. In this paper, we present a new design of discrete state memory cell consisting of sub-cells constructed from a memristor and its resistive network. A memristor in the sub-cells provides the storage element, while its resistive network is used for programming its resistance. Several sub-cells are then connected in parallel, resembling potential divider configuration. The output of the memory cell is the voltage resulting from distributing the input voltage among the sub-cells. Here, proposed design was programmed to obtain 10 and 27 different output levels depending on the configuration of the combined resistive networks within the sub-cell. Despite the simplicity of the circuit, this realization of multilevel memory provides increased number of output levels compared to previous designs of memory technologies based on memristors. Simulation results of proposed memory are analyzed providing explicit data on the issues of distinguishing discrete analog output levels and sensitivity of the cell to oscillations in write signal patterns.","PeriodicalId":335218,"journal":{"name":"2017 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132622143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-31DOI: 10.1109/PRIMEASIA.2017.8280375
N. Hadis, A. A. Manaf, S. H. Ngalim, S. H. Herman, K. Sawada, N. A. Fauzi
In this paper, the implementation of fluidic-based memristor sensor in bio-sensing application is presented. The sensor was fabricated using sol-gel spin coating technique and chemically-modified with antidengue virus NS1 glycoprotein monoclonal antibody before being presented with its ligand, NS1 glycoprotein. Four different concentrations of NS1 glycoprotein (52 nM, 104 nM, 208 nM and 416 nM) were tested on the modified sensor. Each sensor has nine wells, which function to increase the binding area for trapping more viral proteins. To test whether the efficiency of the sensor is attributed by the surface area of each well, four different diameters of the well were fabricated: 0.5 mm, 1 mm, 1.5 mm and 2 mm. These sensors were characterized using field emission scanning electron microscope (FESEM) and semiconductor characterization system (current-voltage (I-V)). FESEM images of the wells show different surface morphologies prior to biochemical treatment, after the bound-antibody modification and after the presentation of viral protein. Off-on resistance ratio extracted from I-V curve between the antibody-bound sensor with and without the viral protein. Analysis shows that the loop area increases as the NS1 glycoprotein applied to the modified sensor. The area within the loop also increases as the concentration of the NS1 glycoprotein increases. The most significant change in loop area is observed upon introduction of 416 nM. Memristor sensor with 2 mm-well diameter recorded the highest sensitivity when compared to the other three well diameters. The recorded sensitivity for the 2 mm-well diameter is 6.53 × 10−3 nM−1 according to fluidic-based platform. These findings conclude that specific-binding between dengue virus antibody and NS1 glycoprotein of dengue virus can be detected by the sensor via the change in electrical conductivity.
{"title":"Fabrication of fluidic-based memristor sensor for dengue virus detection","authors":"N. Hadis, A. A. Manaf, S. H. Ngalim, S. H. Herman, K. Sawada, N. A. Fauzi","doi":"10.1109/PRIMEASIA.2017.8280375","DOIUrl":"https://doi.org/10.1109/PRIMEASIA.2017.8280375","url":null,"abstract":"In this paper, the implementation of fluidic-based memristor sensor in bio-sensing application is presented. The sensor was fabricated using sol-gel spin coating technique and chemically-modified with antidengue virus NS1 glycoprotein monoclonal antibody before being presented with its ligand, NS1 glycoprotein. Four different concentrations of NS1 glycoprotein (52 nM, 104 nM, 208 nM and 416 nM) were tested on the modified sensor. Each sensor has nine wells, which function to increase the binding area for trapping more viral proteins. To test whether the efficiency of the sensor is attributed by the surface area of each well, four different diameters of the well were fabricated: 0.5 mm, 1 mm, 1.5 mm and 2 mm. These sensors were characterized using field emission scanning electron microscope (FESEM) and semiconductor characterization system (current-voltage (I-V)). FESEM images of the wells show different surface morphologies prior to biochemical treatment, after the bound-antibody modification and after the presentation of viral protein. Off-on resistance ratio extracted from I-V curve between the antibody-bound sensor with and without the viral protein. Analysis shows that the loop area increases as the NS1 glycoprotein applied to the modified sensor. The area within the loop also increases as the concentration of the NS1 glycoprotein increases. The most significant change in loop area is observed upon introduction of 416 nM. Memristor sensor with 2 mm-well diameter recorded the highest sensitivity when compared to the other three well diameters. The recorded sensitivity for the 2 mm-well diameter is 6.53 × 10−3 nM−1 according to fluidic-based platform. These findings conclude that specific-binding between dengue virus antibody and NS1 glycoprotein of dengue virus can be detected by the sensor via the change in electrical conductivity.","PeriodicalId":335218,"journal":{"name":"2017 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128009625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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