Pub Date : 2023-04-05DOI: 10.3389/fnano.2023.1146772
H. Contreras, P. Alarcón-Zapata, E. Nova-Lamperti, V. Ormazábal, M. Varas-Godoy, C. Salomon, F. Zúñiga
Introduction: Extracellular vesicles (EVs) are secreted from all types of cells and are involved in the trafficking of proteins, metabolites, and genetic material from cell to cell. According to their biogenesis and physical properties, EVs are often classified as small EVs (including exosomes) or large EVs, and large oncosomes. A variety of methods are used for isolated EVs; however, they have several limitations, including vesicle deformation, reduced particle yield, and co-isolate protein contaminants. Here we present an optimized fast and low-cost methodology to isolate small EVs (30–150 nm) from biological fluids comparing two SEC stationary phases, G200/120 and G200/140 columns. Methods: The optimization parameters considered were a) the selection of the stationary phase, b) the eluate volume per fraction, and c) the selection of the enriched 30–150 nm EVs-fractions. The efficiency and separation profile of each UF/SEC fraction was evaluated by Nanoparticle tracking analysis (NTA), flow cytometry, total protein quantification, and Western blot. Results: Both columns can isolate predominantly small EVs with low protein contaminants from plasma, urine, saliva, and HEK293-derived EV from collection medium. Column G200/ 40 offers a more homogeneous enrichment of vesicles between 30 and 150 nm than G200/120 [76.1 ± 4.4% with an average size of 85.9 ± 3.6 nm (Mode: 72.8 nm)] in the EV collection medium. The enrichment, estimated as the vesicle-to-protein ratio, was 1.3 × 1010 particles/mg protein for G200/40, obtaining a more significant EVs enrichment compared to G200/120. The optimized method delivers 0.8 ml of an EVs-enriched-outcome, taking only 30 min per sample. Using plasma, the enrichment of small EVs from the optimized method was 70.5 ± 0.18%, with an average size of 119.4 ± 6.9 nm (Mode: 120.3 nm), and the enrichment of the vesicle isolation was 4.8 × 1011 particles/mg protein. The average size of urine and saliva -EVs samples was 147.5 ± 3.4 and 111.9 ± 2.5 nm, respectively. All the small EVs isolated from the samples exhibit the characteristic cup-shaped morphology observed by Transmission electron microscopy (TEM). Discussion: This study suggests that the combination of methods is a robust, fast, and improved strategy for isolating small EVs.
{"title":"Comparative study of size exclusion chromatography for isolation of small extracellular vesicle from cell-conditioned media, plasma, urine, and saliva","authors":"H. Contreras, P. Alarcón-Zapata, E. Nova-Lamperti, V. Ormazábal, M. Varas-Godoy, C. Salomon, F. Zúñiga","doi":"10.3389/fnano.2023.1146772","DOIUrl":"https://doi.org/10.3389/fnano.2023.1146772","url":null,"abstract":"Introduction: Extracellular vesicles (EVs) are secreted from all types of cells and are involved in the trafficking of proteins, metabolites, and genetic material from cell to cell. According to their biogenesis and physical properties, EVs are often classified as small EVs (including exosomes) or large EVs, and large oncosomes. A variety of methods are used for isolated EVs; however, they have several limitations, including vesicle deformation, reduced particle yield, and co-isolate protein contaminants. Here we present an optimized fast and low-cost methodology to isolate small EVs (30–150 nm) from biological fluids comparing two SEC stationary phases, G200/120 and G200/140 columns. Methods: The optimization parameters considered were a) the selection of the stationary phase, b) the eluate volume per fraction, and c) the selection of the enriched 30–150 nm EVs-fractions. The efficiency and separation profile of each UF/SEC fraction was evaluated by Nanoparticle tracking analysis (NTA), flow cytometry, total protein quantification, and Western blot. Results: Both columns can isolate predominantly small EVs with low protein contaminants from plasma, urine, saliva, and HEK293-derived EV from collection medium. Column G200/ 40 offers a more homogeneous enrichment of vesicles between 30 and 150 nm than G200/120 [76.1 ± 4.4% with an average size of 85.9 ± 3.6 nm (Mode: 72.8 nm)] in the EV collection medium. The enrichment, estimated as the vesicle-to-protein ratio, was 1.3 × 1010 particles/mg protein for G200/40, obtaining a more significant EVs enrichment compared to G200/120. The optimized method delivers 0.8 ml of an EVs-enriched-outcome, taking only 30 min per sample. Using plasma, the enrichment of small EVs from the optimized method was 70.5 ± 0.18%, with an average size of 119.4 ± 6.9 nm (Mode: 120.3 nm), and the enrichment of the vesicle isolation was 4.8 × 1011 particles/mg protein. The average size of urine and saliva -EVs samples was 147.5 ± 3.4 and 111.9 ± 2.5 nm, respectively. All the small EVs isolated from the samples exhibit the characteristic cup-shaped morphology observed by Transmission electron microscopy (TEM). Discussion: This study suggests that the combination of methods is a robust, fast, and improved strategy for isolating small EVs.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47186866","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 : 2023-03-30DOI: 10.3389/fnano.2023.1055527
B. van de Ven, U. Alegre-Ibarra, P. J. Lemieszczuk, P. Bobbert, Hans-Christian Ruiz Euler, W. G. van der Wiel
Inspired by the highly efficient information processing of the brain, which is based on the chemistry and physics of biological tissue, any material system and its physical properties could in principle be exploited for computation. However, it is not always obvious how to use a material system’s computational potential to the fullest. Here, we operate a dopant network processing unit (DNPU) as a tuneable extreme learning machine (ELM) and combine the principles of artificial evolution and ELM to optimise its computational performance on a non-linear classification benchmark task. We find that, for this task, there is an optimal, hybrid operation mode (“tuneable ELM mode”) in between the traditional ELM computing regime with a fixed DNPU and linearly weighted outputs (“fixed-ELM mode”) and the regime where the outputs of the non-linear system are directly tuned to generate the desired output (“direct-output mode”). We show that the tuneable ELM mode reduces the number of parameters needed to perform a formant-based vowel recognition benchmark task. Our results emphasise the power of analog in-matter computing and underline the importance of designing specialised material systems to optimally utilise their physical properties for computation.
{"title":"Dopant network processing units as tuneable extreme learning machines","authors":"B. van de Ven, U. Alegre-Ibarra, P. J. Lemieszczuk, P. Bobbert, Hans-Christian Ruiz Euler, W. G. van der Wiel","doi":"10.3389/fnano.2023.1055527","DOIUrl":"https://doi.org/10.3389/fnano.2023.1055527","url":null,"abstract":"Inspired by the highly efficient information processing of the brain, which is based on the chemistry and physics of biological tissue, any material system and its physical properties could in principle be exploited for computation. However, it is not always obvious how to use a material system’s computational potential to the fullest. Here, we operate a dopant network processing unit (DNPU) as a tuneable extreme learning machine (ELM) and combine the principles of artificial evolution and ELM to optimise its computational performance on a non-linear classification benchmark task. We find that, for this task, there is an optimal, hybrid operation mode (“tuneable ELM mode”) in between the traditional ELM computing regime with a fixed DNPU and linearly weighted outputs (“fixed-ELM mode”) and the regime where the outputs of the non-linear system are directly tuned to generate the desired output (“direct-output mode”). We show that the tuneable ELM mode reduces the number of parameters needed to perform a formant-based vowel recognition benchmark task. Our results emphasise the power of analog in-matter computing and underline the importance of designing specialised material systems to optimally utilise their physical properties for computation.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49053314","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 : 2023-03-29DOI: 10.3389/fnano.2023.1132783
R. Hans, P. Yadav, M. Zaman, Rajaram Poolla, D. Thavaselvam
Brucellosis is the most widespread and serious zoonotic disease worldwide which affects livestock, sylvatic wildlife, marine dwellers, and humans. It is acquired through Alphaproteobacteria which belong to the genus Brucella and is categorized as a potential bio-threat agent. In this study, we developed a rapid and direct differential whole cell (WC) agglutination-based assay for its on-field detection. The recombinant outer membrane (rOmp28) protein-derived specific mice IgG polyclonal antibodies (pAbs) of Brucella were purified using affinity chromatography and conjugated with functionalized gold nanoparticles (AuNPs) for rapid agglutination. A positive blot of 32 kDa protein revealed specific immuno-reactivity of rOmp28-pAbs using immunoblot analysis. For the synthesis of AuNPs, the conventional “Turkevich method” was optimized at a concentration < 1 mM of gold precursor for obtaining 50-nm-sized particles. Also, their physico-chemical characteristics were analyzed using UV-visible spectrophotometry, Fourier transform infra-red spectroscopy (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential (ζ, ZP), and fluorescence spectroscopy. Furthermore, these AuNPs were functionalized with N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) to prepare modified carboxylated AuNPs. For bioconjugation with Brucella rOmp28 IgG pAbs, antibody-conjugated functionalized AuNP constructs were prepared and characterized using FT-IR analysis with strong N–H deformations. Subsequently, these bioconjugated AuNPs were used to develop a direct-differential slide agglutination assay with a detection limit of 104 CFU mL−1. The sensitivity of this assay was compared with standard double-antibody sandwich ELISA (S-ELISA) using rOmp28 IgG pAbs with an LOD of 103 CFU mL−1 and a detection range of 102–108 CFU mL−1. No intraspecies cross-reactivity was observed based on evaluation of its specificity with a battery of closely related bacterial species. In conclusion, the increased sensitivity and specificity of the developed agglutination assay obtained using bioconjugated functionalized AuNPs is ≥ 98% for the detection of Brucella. Therefore, it can be used as an alternate rapid method of direct WC detection of bacteria as it is simple, robust, and cost-effective, with minimal time of reaction in the case of early disease diagnosis.
布鲁氏菌病是世界上传播最广和最严重的人畜共患疾病，影响牲畜、森林野生动物、海洋生物和人类。它是通过属于布鲁氏菌属的阿尔法变形菌获得的，被归类为潜在的生物威胁剂。在这项研究中，我们开发了一种快速和直接的基于差异全细胞(WC)凝集的现场检测方法。采用亲和层析技术纯化重组外膜(rommp28)蛋白衍生的布鲁氏菌特异性小鼠IgG多克隆抗体(pAbs)，并与功能化金纳米颗粒(AuNPs)偶联进行快速凝集。32 kDa蛋白的阳性免疫印迹分析显示rommp28 - pab具有特异性免疫反应性。对于AuNPs的合成，优化了传统的“Turkevich法”，在金前驱体浓度< 1 mM时，可获得50纳米大小的颗粒。采用紫外可见分光光度法、傅里叶变换红外光谱法(FT-IR)、拉曼光谱法、x射线衍射法(XRD)、扫描电镜法(SEM)、透射电镜法(TEM)、动态光散射法(DLS)、ζ电位法(ζ， ZP)和荧光光谱法对其理化性质进行了分析。然后用N-(3-二甲氨基丙基)-N′-乙基碳二亚胺盐酸盐(EDC)和N-羟基琥珀酰亚胺(NHS)功能化这些AuNPs，制备改性的羧化AuNPs。为了与布鲁氏菌rom28 IgG pab生物偶联，制备了抗体偶联的功能化AuNP结构体，并使用具有强N-H变形的FT-IR分析对其进行了表征。随后，将这些生物偶联的AuNPs用于直接差分玻片凝集试验，检测限为104 CFU mL−1。与标准双抗体夹心ELISA (S-ELISA)相比，该方法的灵敏度较高，检测限为103 CFU mL - 1，检测范围为102-108 CFU mL - 1。基于与一系列密切相关的细菌物种的特异性评估，未观察到种内交叉反应。综上所述，利用生物偶联功能化AuNPs获得的凝集试验检测布鲁氏菌的灵敏度和特异性均提高了≥98%。因此，在疾病早期诊断的情况下，它具有简单、可靠、成本低、反应时间短的优点，可作为直接WC检测细菌的替代快速方法。
{"title":"A rapid direct-differential agglutination assay for Brucella detection using antibodies conjugated with functionalized gold nanoparticles","authors":"R. Hans, P. Yadav, M. Zaman, Rajaram Poolla, D. Thavaselvam","doi":"10.3389/fnano.2023.1132783","DOIUrl":"https://doi.org/10.3389/fnano.2023.1132783","url":null,"abstract":"Brucellosis is the most widespread and serious zoonotic disease worldwide which affects livestock, sylvatic wildlife, marine dwellers, and humans. It is acquired through Alphaproteobacteria which belong to the genus Brucella and is categorized as a potential bio-threat agent. In this study, we developed a rapid and direct differential whole cell (WC) agglutination-based assay for its on-field detection. The recombinant outer membrane (rOmp28) protein-derived specific mice IgG polyclonal antibodies (pAbs) of Brucella were purified using affinity chromatography and conjugated with functionalized gold nanoparticles (AuNPs) for rapid agglutination. A positive blot of 32 kDa protein revealed specific immuno-reactivity of rOmp28-pAbs using immunoblot analysis. For the synthesis of AuNPs, the conventional “Turkevich method” was optimized at a concentration < 1 mM of gold precursor for obtaining 50-nm-sized particles. Also, their physico-chemical characteristics were analyzed using UV-visible spectrophotometry, Fourier transform infra-red spectroscopy (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential (ζ, ZP), and fluorescence spectroscopy. Furthermore, these AuNPs were functionalized with N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) to prepare modified carboxylated AuNPs. For bioconjugation with Brucella rOmp28 IgG pAbs, antibody-conjugated functionalized AuNP constructs were prepared and characterized using FT-IR analysis with strong N–H deformations. Subsequently, these bioconjugated AuNPs were used to develop a direct-differential slide agglutination assay with a detection limit of 104 CFU mL−1. The sensitivity of this assay was compared with standard double-antibody sandwich ELISA (S-ELISA) using rOmp28 IgG pAbs with an LOD of 103 CFU mL−1 and a detection range of 102–108 CFU mL−1. No intraspecies cross-reactivity was observed based on evaluation of its specificity with a battery of closely related bacterial species. In conclusion, the increased sensitivity and specificity of the developed agglutination assay obtained using bioconjugated functionalized AuNPs is ≥ 98% for the detection of Brucella. Therefore, it can be used as an alternate rapid method of direct WC detection of bacteria as it is simple, robust, and cost-effective, with minimal time of reaction in the case of early disease diagnosis.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43843906","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 : 2023-03-13DOI: 10.3389/fnano.2023.1135408
D. Quinn, F. Cichos
Colloidal crystals are interesting as functional structures due to their emergent photonic properties like photonic stop bands and bandgaps that can be used to redirect light. They are commonly formed by a drying process that is assisted by capillary forces at the drying fronts. In this manuscript, we demonstrate the optically induced dynamic thermofluidic assembly of 2D and 3D colloidal crystals. We quantify in experiment and simulation the structure formation and identify thermo-osmosis and temperature induced depletion interactions as the key contributors to the colloidal crystal formation. The non-equilibrium nature of the assembly of colloidal crystals and its dynamic control by laser-induced local heating promise new possibilities for a versatile formation of photonic structures inaccessible by equilibrium processes.
{"title":"Thermofluidic assembly of colloidal crystals","authors":"D. Quinn, F. Cichos","doi":"10.3389/fnano.2023.1135408","DOIUrl":"https://doi.org/10.3389/fnano.2023.1135408","url":null,"abstract":"Colloidal crystals are interesting as functional structures due to their emergent photonic properties like photonic stop bands and bandgaps that can be used to redirect light. They are commonly formed by a drying process that is assisted by capillary forces at the drying fronts. In this manuscript, we demonstrate the optically induced dynamic thermofluidic assembly of 2D and 3D colloidal crystals. We quantify in experiment and simulation the structure formation and identify thermo-osmosis and temperature induced depletion interactions as the key contributors to the colloidal crystal formation. The non-equilibrium nature of the assembly of colloidal crystals and its dynamic control by laser-induced local heating promise new possibilities for a versatile formation of photonic structures inaccessible by equilibrium processes.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46751099","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 : 2023-03-10DOI: 10.3389/fnano.2023.1112100
Xiuyu Wang, Xiaoman Wang, Q. Ren, Haocheng Cai, J. Xin, Yuxin Lang, Xiaofei Xiao, Z. Lan, J. You, W. E. Sha
Introduction: Many researchers have explored the bound states in the continuum (BICs) as a particular bound wave state which can be used to achieve a very high Q-factor. High-Q factor devices, typically based on the bound states in the continuum (BICs), are well used in the fields of hypersensitive biochemical sensors, non-linear effects enhancement, plasmon lasers, and hi-performance filtering. However, symmetrical-protected BIC is difficult to achieve experimentally high-Q factor because it strongly depends on the geometry and can be destroyed by any slight disturbance in the potential well. Methods: Therefore, we proposed a parameter-adjusted Friedrich-Wintergen BIC based on the analysis model of time-coupled model theory, where the target system parameters can be tuned to achieve high-Q excitation. Results: Moreover, considering the tunability and flexibility of the components in various practical applications, we integrate active materials into metasurface arrays with the help of external stimuli to achieve modulation of high-Q resonances. Our results demonstrate that an optical resonator based on FW-BIC can modulate the BIC state by changing the intermediate gap. Discussion: The BIC state and the high-Q factor Fano resonance can be dynamically tuned by adding temperature-sensitive VO 2 material.
{"title":"Temperature-controlled optical switch metasurface with large local field enhancement based on FW-BIC","authors":"Xiuyu Wang, Xiaoman Wang, Q. Ren, Haocheng Cai, J. Xin, Yuxin Lang, Xiaofei Xiao, Z. Lan, J. You, W. E. Sha","doi":"10.3389/fnano.2023.1112100","DOIUrl":"https://doi.org/10.3389/fnano.2023.1112100","url":null,"abstract":"Introduction: Many researchers have explored the bound states in the continuum (BICs) as a particular bound wave state which can be used to achieve a very high Q-factor. High-Q factor devices, typically based on the bound states in the continuum (BICs), are well used in the fields of hypersensitive biochemical sensors, non-linear effects enhancement, plasmon lasers, and hi-performance filtering. However, symmetrical-protected BIC is difficult to achieve experimentally high-Q factor because it strongly depends on the geometry and can be destroyed by any slight disturbance in the potential well. Methods: Therefore, we proposed a parameter-adjusted Friedrich-Wintergen BIC based on the analysis model of time-coupled model theory, where the target system parameters can be tuned to achieve high-Q excitation. Results: Moreover, considering the tunability and flexibility of the components in various practical applications, we integrate active materials into metasurface arrays with the help of external stimuli to achieve modulation of high-Q resonances. Our results demonstrate that an optical resonator based on FW-BIC can modulate the BIC state by changing the intermediate gap. Discussion: The BIC state and the high-Q factor Fano resonance can be dynamically tuned by adding temperature-sensitive VO 2 material.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48799570","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 : 2023-02-28DOI: 10.3389/fnano.2023.1121492
A. Jaman, A. Goossens, J. J. L. van Rijn, L. van der Zee, T. Banerjee
The development of in-memory computing hardware components based on different types of resistive materials is an active research area. These materials usually exhibit analog memory states originating from a wide range of physical mechanisms and offer rich prospects for their integration in artificial neural networks. The resistive states are classified as either non-volatile or volatile, and switching occurs when the material properties are triggered by an external stimulus such as temperature, current, voltage, or electric field. The non-volatile resistance state change is typically achieved by the switching layer’s local redox reaction that involves both electronic and ionic movement. In contrast, a volatile change in the resistance state arises due to the transition of the switching layer from an insulator to a metal. Here, we demonstrate volatile resistive switching in twinned LaAlO3 onto which strained thin films of La0.67Sr0.33MnO3 (LSMO) are deposited. An electric current induces phase transition that triggers resistive switching, close to the competing phase transition temperature in LSMO, enabled by the strong correlation between the electronic and magnetic ground states, intrinsic to such materials. This phase transition, characterized by an abrupt resistance change, is typical of a metallic to insulating behavior, due to Joule heating, and manifested as a sharp increase in the voltage with accompanying hysteresis. Our results show that such Joule heating-induced hysteretic resistive switching exhibits different profiles that depend on the substrate texture along the current path, providing an interesting direction toward new multifunctional in-memory computing devices.
{"title":"Morphology control of volatile resistive switching in La0.67Sr0.33MnO3 thin films on LaAlO3 (001)","authors":"A. Jaman, A. Goossens, J. J. L. van Rijn, L. van der Zee, T. Banerjee","doi":"10.3389/fnano.2023.1121492","DOIUrl":"https://doi.org/10.3389/fnano.2023.1121492","url":null,"abstract":"The development of in-memory computing hardware components based on different types of resistive materials is an active research area. These materials usually exhibit analog memory states originating from a wide range of physical mechanisms and offer rich prospects for their integration in artificial neural networks. The resistive states are classified as either non-volatile or volatile, and switching occurs when the material properties are triggered by an external stimulus such as temperature, current, voltage, or electric field. The non-volatile resistance state change is typically achieved by the switching layer’s local redox reaction that involves both electronic and ionic movement. In contrast, a volatile change in the resistance state arises due to the transition of the switching layer from an insulator to a metal. Here, we demonstrate volatile resistive switching in twinned LaAlO3 onto which strained thin films of La0.67Sr0.33MnO3 (LSMO) are deposited. An electric current induces phase transition that triggers resistive switching, close to the competing phase transition temperature in LSMO, enabled by the strong correlation between the electronic and magnetic ground states, intrinsic to such materials. This phase transition, characterized by an abrupt resistance change, is typical of a metallic to insulating behavior, due to Joule heating, and manifested as a sharp increase in the voltage with accompanying hysteresis. Our results show that such Joule heating-induced hysteretic resistive switching exhibits different profiles that depend on the substrate texture along the current path, providing an interesting direction toward new multifunctional in-memory computing devices.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43108590","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 : 2023-02-28DOI: 10.3389/fnano.2023.1128667
Hagar Hendy, Cory E. Merkel
The growing scale and complexity of artificial intelligence (AI) models has prompted several new research efforts in the area of neuromorphic computing. A key aim of neuromorphic computing is to enable advanced AI algorithms to run on energy-constrained hardware. In this work, we propose a novel energy-efficient neuromorphic architecture based on memristors and domino logic. The design uses the delay of memristor RC circuits to represent synaptic computations and a simple binary neuron activation function. Synchronization schemes are proposed for communicating information between neural network layers, and a simple linear power model is developed to estimate the design’s energy efficiency for a particular network size. Results indicate that the proposed architecture can achieve 1.26 fJ per classification per synapse and achieves high accuracy on image classification even in the presence of large noise.
{"title":"Energy-efficient and noise-tolerant neuromorphic computing based on memristors and domino logic","authors":"Hagar Hendy, Cory E. Merkel","doi":"10.3389/fnano.2023.1128667","DOIUrl":"https://doi.org/10.3389/fnano.2023.1128667","url":null,"abstract":"The growing scale and complexity of artificial intelligence (AI) models has prompted several new research efforts in the area of neuromorphic computing. A key aim of neuromorphic computing is to enable advanced AI algorithms to run on energy-constrained hardware. In this work, we propose a novel energy-efficient neuromorphic architecture based on memristors and domino logic. The design uses the delay of memristor RC circuits to represent synaptic computations and a simple binary neuron activation function. Synchronization schemes are proposed for communicating information between neural network layers, and a simple linear power model is developed to estimate the design’s energy efficiency for a particular network size. Results indicate that the proposed architecture can achieve 1.26 fJ per classification per synapse and achieves high accuracy on image classification even in the presence of large noise.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43388241","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 : 2023-02-15DOI: 10.3389/fnano.2023.1127363
I. Tzouvadaki, T. Prodromakis
Nanoscale technologies have brought significant advancements to modern diagnostics, enabling unprecedented bio-chemical sensitivities that are key to disease monitoring. At the same time, miniaturized biosensors and their integration across large areas enabled tessellating these into high-density biosensing panels, a key capability for the development of high throughput monitoring: multiple patients as well as multiple analytes per patient. This review provides a critical overview of various nanoscale biosensing technologies and their ability to unlock high testing throughput without compromising detection resilience. We report on the challenges and opportunities each technology presents along this direction and present a detailed analysis on the prospects of both commercially available and emerging biosensing technologies.
{"title":"Large-scale nano-biosensing technologies","authors":"I. Tzouvadaki, T. Prodromakis","doi":"10.3389/fnano.2023.1127363","DOIUrl":"https://doi.org/10.3389/fnano.2023.1127363","url":null,"abstract":"Nanoscale technologies have brought significant advancements to modern diagnostics, enabling unprecedented bio-chemical sensitivities that are key to disease monitoring. At the same time, miniaturized biosensors and their integration across large areas enabled tessellating these into high-density biosensing panels, a key capability for the development of high throughput monitoring: multiple patients as well as multiple analytes per patient. This review provides a critical overview of various nanoscale biosensing technologies and their ability to unlock high testing throughput without compromising detection resilience. We report on the challenges and opportunities each technology presents along this direction and present a detailed analysis on the prospects of both commercially available and emerging biosensing technologies.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45294184","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 : 2023-02-10DOI: 10.3389/fnano.2023.1146852
Md Golam Morshed, S. Ganguly, Avik W. Ghosh
Neuromorphic computing, commonly understood as a computing approach built upon neurons, synapses, and their dynamics, as opposed to Boolean gates, is gaining large mindshare due to its direct application in solving current and future computing technological problems, such as smart sensing, smart devices, self-hosted and self-contained devices, artificial intelligence (AI) applications, etc. In a largely software-defined implementation of neuromorphic computing, it is possible to throw enormous computational power or optimize models and networks depending on the specific nature of the computational tasks. However, a hardware-based approach needs the identification of well-suited neuronal and synaptic models to obtain high functional and energy efficiency, which is a prime concern in size, weight, and power (SWaP) constrained environments. In this work, we perform a study on the characteristics of hardware neuron models (namely, inference errors, generalizability and robustness, practical implementability, and memory capacity) that have been proposed and demonstrated using a plethora of emerging nano-materials technology-based physical devices, to quantify the performance of such neurons on certain classes of problems that are of great importance in real-time signal processing like tasks in the context of reservoir computing. We find that the answer on which neuron to use for what applications depends on the particulars of the application requirements and constraints themselves, i.e., we need not only a hammer but all sorts of tools in our tool chest for high efficiency and quality neuromorphic computing.
{"title":"Choose your tools carefully: a comparative evaluation of deterministic vs. stochastic and binary vs. analog neuron models for implementing emerging computing paradigms","authors":"Md Golam Morshed, S. Ganguly, Avik W. Ghosh","doi":"10.3389/fnano.2023.1146852","DOIUrl":"https://doi.org/10.3389/fnano.2023.1146852","url":null,"abstract":"Neuromorphic computing, commonly understood as a computing approach built upon neurons, synapses, and their dynamics, as opposed to Boolean gates, is gaining large mindshare due to its direct application in solving current and future computing technological problems, such as smart sensing, smart devices, self-hosted and self-contained devices, artificial intelligence (AI) applications, etc. In a largely software-defined implementation of neuromorphic computing, it is possible to throw enormous computational power or optimize models and networks depending on the specific nature of the computational tasks. However, a hardware-based approach needs the identification of well-suited neuronal and synaptic models to obtain high functional and energy efficiency, which is a prime concern in size, weight, and power (SWaP) constrained environments. In this work, we perform a study on the characteristics of hardware neuron models (namely, inference errors, generalizability and robustness, practical implementability, and memory capacity) that have been proposed and demonstrated using a plethora of emerging nano-materials technology-based physical devices, to quantify the performance of such neurons on certain classes of problems that are of great importance in real-time signal processing like tasks in the context of reservoir computing. We find that the answer on which neuron to use for what applications depends on the particulars of the application requirements and constraints themselves, i.e., we need not only a hammer but all sorts of tools in our tool chest for high efficiency and quality neuromorphic computing.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42126762","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 : 2023-02-08DOI: 10.3389/fnano.2023.1112346
Xiuyu Wang, Xiaoman Wang, Q. Ren, Haocheng Cai, J. Xin, Yuxin Lang, Xiaofei Xiao, Z. Lan, J. You, W. E. Sha
Terahertz functional devices with high-Q factor play an important role in spectral sensing, security imaging, and wireless communication. The reported terahertz devices based on the electromagnetic induction transparency (EIT) effect cannot meet the needs of high-Q in practical applications due to the low-Q factor. Therefore, to increase the Q-factor of resonance, researchers introduced the concept of bound state in the continuum (BIC). In the quasi-BIC state, the metasurface can be excited by the incident wave and provide resonance with a high-Q factor because the condition that the resonant state of the BIC state is orthogonal is not satisfied. The split ring resonator (SRR) is one of the most representative artificial microstructures in the metasurface field, and it shows great potential in BIC. In this paper, based on the classical single-SRR array structure, we combine the large and small SRR and change the resonance mode of the inner and outer SRR by changing the outer radius of the inner SRR. The metasurface based on parameter-tuned BIC verified that the continuous modulation of parameters in a system could make a pair of resonant states strongly coupled, and the coherent cancellation of the resonant states will cause the linewidth of one of the resonant states to disappear, thus forming BIC. Compared with the single-SRR array metasurface based on symmetry-protected BIC, the dual-SRR array metasurface designed in this paper has multiple accidental BICs and realizes multichannel multiplexing of X-polarization and Y-polarization. It provides a brilliant platform for high-sensitivity optical sensor array, low threshold laser and efficient optical harmonic generation.
{"title":"Polarization multiplexing multichannel high-Q terahertz sensing system","authors":"Xiuyu Wang, Xiaoman Wang, Q. Ren, Haocheng Cai, J. Xin, Yuxin Lang, Xiaofei Xiao, Z. Lan, J. You, W. E. Sha","doi":"10.3389/fnano.2023.1112346","DOIUrl":"https://doi.org/10.3389/fnano.2023.1112346","url":null,"abstract":"Terahertz functional devices with high-Q factor play an important role in spectral sensing, security imaging, and wireless communication. The reported terahertz devices based on the electromagnetic induction transparency (EIT) effect cannot meet the needs of high-Q in practical applications due to the low-Q factor. Therefore, to increase the Q-factor of resonance, researchers introduced the concept of bound state in the continuum (BIC). In the quasi-BIC state, the metasurface can be excited by the incident wave and provide resonance with a high-Q factor because the condition that the resonant state of the BIC state is orthogonal is not satisfied. The split ring resonator (SRR) is one of the most representative artificial microstructures in the metasurface field, and it shows great potential in BIC. In this paper, based on the classical single-SRR array structure, we combine the large and small SRR and change the resonance mode of the inner and outer SRR by changing the outer radius of the inner SRR. The metasurface based on parameter-tuned BIC verified that the continuous modulation of parameters in a system could make a pair of resonant states strongly coupled, and the coherent cancellation of the resonant states will cause the linewidth of one of the resonant states to disappear, thus forming BIC. Compared with the single-SRR array metasurface based on symmetry-protected BIC, the dual-SRR array metasurface designed in this paper has multiple accidental BICs and realizes multichannel multiplexing of X-polarization and Y-polarization. It provides a brilliant platform for high-sensitivity optical sensor array, low threshold laser and efficient optical harmonic generation.","PeriodicalId":34432,"journal":{"name":"Frontiers in Nanotechnology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46752313","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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