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        <title>Frontiers in Nanotechnology | Nanodevices section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/nanotechnology/sections/nanodevices</link>
        <description>RSS Feed for Nanodevices section in the Frontiers in Nanotechnology journal | New and Recent Articles</description>
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        <pubDate>2026-05-14T20:14:17.856+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2026.1788527</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2026.1788527</link>
        <title><![CDATA[Symmetric pulse-enabled highly linear analog switching in ALD-grown HfO2/Ta2O5-based memristor for multi-level storage and synaptic applications]]></title>
        <pubdate>2026-03-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Parthasarathi Pal</author><author>Sanjay Kumar</author><author>Themis Prodromakis</author>
        <description><![CDATA[Analog memristors with multilevel cells are suitable for analog in-memory and neuromorphic applications. Herein, we report a 2-bit/cell complementary-metal-oxide-semiconductor (CMOS)-compatible HfO2/Ta2O5 bilayer memristor with both TiN electrodes fabricated via single thermal atomic layer deposition at 300 °C. The fabricated devices exhibit stable bipolar switching characteristics distinguished between both low resistance state and the high resistance state with a P/E endurance of 105WRITE cycles, as well as show better retention property beyond 104 s. The devices exhibited excellent uniformity in terms of low device-to-device (D2D) and low cycle-to-cycle (C2C) variation. Furthermore, analog switching responses are implemented with the pulse width from 2 ms to 500 µs, and the corresponding percentage change in the device resistance was measured. The results exhibit a significant change in the device resistance even at 500 µs, with an overall change in the device resistance in the range of 10%–17%. In addition, the performance of the devices has been verified for neuromorphic applications using the experimentally extracted data. The non-linearity of 0.07, including highly stable synaptic plasticity, has been achieved using symmetric pulses, making the devices compatible for designing an analog memristor-based neuromorphic computing system hardware.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2026.1729291</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2026.1729291</link>
        <title><![CDATA[Atomic layer deposited HfZrO4-based memristive devices: annealing effect and multilevel storage capability]]></title>
        <pubdate>2026-01-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rahul Ramesh</author><author>Spyros Stathopoulos</author><author>Sanjay Kumar</author><author>Hannah Levene</author><author>Deepika Yadav</author><author>Andreas Tsiamis</author><author>Themis Prodromakis</author>
        <description><![CDATA[In this work, an atomic layer deposited (ALD) Hf1Zr1O4 (HZO)-based switching layer is investigated in the device structure of a TiN/HZO/TiN. The thickness of the switching layer is ∼10 nm, which was grown by the thermal ALD at 250 °C by a super-cycle approach. Both pristine and annealed (400 °C for 60 s in N2) devices exhibit stable bipolar resistive switching responses after an essential electroforming process. However, the annealed devices require a relatively higher forming voltage but significantly improved ON/OFF ratio than pristine devices, which can be due to a certain modification at the TiN/HZO interface. The significant improvement in the ON/OFF ratio is attributed to the formation of nano-crystallinity in the film and an increment in sub-oxide content. The X-ray photoelectron spectroscopy (XPS) analysis also reveals the formation of a significant amount of sub-oxide (HfO2-x and ZrO2-x) after the annealing process. Additionally, the pristine devices exhibit comparatively poor switching stability and show a systematic decrement in the hysteresis loop, i.e., 73% after 100 switching cycles, whereas only a ∼22% drop is observed with annealed samples that significantly enhance the device stability. Lastly, the annealed device exhibits high volatility towards multiple programmable states, which can be useful in the development of multilevel memory storage, in-memory computation, and neuromorphic computation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2026.1783097</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2026.1783097</link>
        <title><![CDATA[Editorial: Thought leaders in nanotechnology research]]></title>
        <pubdate>2026-01-14T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Bingqing Wei</author><author>Themis Prodromakis</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1560733</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1560733</link>
        <title><![CDATA[Nanotechnology-enabled energy efficiency in semiconductors: plasmon-induced super-semiconductors and ballistic transport devices]]></title>
        <pubdate>2025-08-22T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Zhigang Li</author><author>Bingqing Wei</author>
        <description><![CDATA[The semiconductor industry consumes staggering amounts of electricity annually, surpassing the energy usage of over 100 nations. This immense consumption not only underscores the environmental impact but also generates substantial heat within semiconductor devices, adversely affecting their performance, lifespan, and reliability, posing significant challenges to the advancement of nanodevices. To address these challenges, reducing energy consumption through the use of advanced, energy-efficient technologies has become a priority. Energy-efficient electronics (EEE), enabled by nanotechnology, have the potential to drastically reduce energy consumption in semiconductor devices while simultaneously enhancing their performance. From this perspective, this discussion focuses on two nano-semiconductor technologies poised to advance EEEs: plasmon-induced metal-based semiconductors and ballistic transport in nanostructured semiconductors. For example, p-n junction diodes constructed with the metal-based semiconductors can reduce power consumption by 3-4 orders of magnitude compared with silicon-based devices due to their low resistivity; similarly, the excellent ballistic transport property of InSe FETs enables an energy-delay product of ∼4.32*10−29 Js/μm of the devices, one order of magnitude lower than the Si counterparts. This perspective examines the offerings of each of these disciplines and explores how nanotechnology can be utilized to conserve energy and enhance performance. Differences from traditional technologies and limitations in existing research will also be assessed.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1650174</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1650174</link>
        <title><![CDATA[Correction: Performance and variability analysis of ALD-grown wafer scale HfO2/Ta2O5-based memristive devices for neuromorphic computing]]></title>
        <pubdate>2025-06-26T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Sanjay Kumar</author><author>Deepika Yadav</author><author>Spyros Stathopoulos</author><author>Themis Prodromakis</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1621554</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1621554</link>
        <title><![CDATA[Performance and variability analysis of ALD-grown wafer scale HfO2/Ta2O5-based memristive devices for neuromorphic computing]]></title>
        <pubdate>2025-06-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sanjay Kumar</author><author>Deepika Yadav</author><author>Spyros Stathopoulos</author><author>Themis Prodromakis</author>
        <description><![CDATA[Here, we report a large-scale wafer microfabrication process and in-depth electrical analysis of atomic layer deposition (ALD) grown bilayer (i.e., HfO2/Ta2O5) memristive devices. The fabricated bilayer devices initially require an electroforming event and show stable bipolar resistive switching responses with some variations in the device switching voltages. These variations are covered in the 15.7%–22.7% range corresponding to the maximum switching voltage of the tested devices. Moreover, time series analysis (TSA) is employed by considering the device switching voltages (VSET and VRESET) to predict the device performance and the obtained outcomes are well matched to the experimental data. Furthermore, the least values of coefficient of variability (CV) in the device switching voltages are 6.09% (VSET) and 3.22% (VRESET) in the case of device-to-device (D2D) while 1.76% (VSET) and 2.14% (VRESET) in the case of cycle-to-cycle (C2C). Furthermore, the fabricated devices efficiently perform the synaptic functionalities in terms of potentiation (P) and depression (D), paired-pulse facilitation (PPF), and paired-pulse depression (PPD), with a least value of nonlinearity (NL) factor of 0.43 in synaptic response, which is close to the ideal value of NL in biological synapses. Therefore, the present work shows that the single ALD system can be an efficient deposition method to deposit high-k oxide materials for memristive arrays over large-scale wafers.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1558743</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1558743</link>
        <title><![CDATA[Advanced memristive architectures based on nanomaterials for biomedical applications: a mini review]]></title>
        <pubdate>2025-04-23T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Manel Bouzouita</author><author>Shashikant Pathak</author><author>Fakhreddine Zayer</author><author>Hamdi Belgacem</author><author>Ioulia Tzouvadaki</author>
        <description><![CDATA[In recent years, the interest of science in big data sensing, storage and processing has been growing fast. Nano-materials have been widely used in resistive switching devices thanks to their distinguished properties. Furthermore, they provide nano-scale dimensions and compatibility with fabrication procedures and complementary metal oxide semiconductor (CMOS) technology. Nano-materials can also enhance the performance of memristive structures. The operation of a memristor, which enables efficient resistive switching characterized by fast response, increased storage density, and low power requirements, depends largely on nano-materials and deposition techniques. Herein, a comprehensive brief review of nano-material RRAM arrays and their application in biomedical is discussed. First, we introduce planar and array resistive switching structures. Second, we report the different nanomaterial categories that can be used in resistive random-access memories (RRAMs). Then, we focus on the integration of 3D nano-material-based memristive crossbars for in-memory computing and biosensing arrays and discuss representative applications. The exploration of nano-materials enables the development of enhanced resistive switching architectures with increased signal integrity, great speed, and ultra-high sensitivity towards thermally and electrically stable memristive biomedical platforms.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1583483</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1583483</link>
        <title><![CDATA[Application-driven innovations in nanodevices for next-generation transistors, neuromorphic computing, neural interface and quantum computing]]></title>
        <pubdate>2025-04-10T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Youfan Hu</author>
        <description><![CDATA[The demand for aggressive scaling in integrated circuits technology has been a primary driving force behind the rapid advancement of nanotechnology, leading to groundbreaking innovations in nanoscience, engineering, and technology. Initially, the unique phenomena observed at nanoscale enable innovative applications in nanodevices. Now, as our understanding has greatly developed, nanodevices are increasingly being leveraged to provide solutions for a growing range of applications. In this perspective, several key areas are featured that are proposed to benefit significantly from advancements in nanodevices.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1545792</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1545792</link>
        <title><![CDATA[Nano-enabled biosensors in early detection of plant diseases]]></title>
        <pubdate>2025-04-04T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Ambika Chaturvedi</author><author>Deepti Tripathi</author><author>Rajiv Ranjan</author>
        <description><![CDATA[Plant disease outbreaks are raising concerns about global food security. Pathogenic evolution and continuous climate changes increase the threat to agriculture and necessitate disease surveillance. To prevent future outbreaks and maintain agricultural sustainability advanced tools are required. Nowadays various types of nanobiosensors such as electrochemical, piezoelectric, thermal, optical, and Fluorescence resonance energy transfer (FRET)-based biosensors are used to predict disease-associated pathogens, toxins, and abiotic stress. Nanobiosensors, provide quick detection of diseases and may protect from future pandemics as they overcome the time dependency of traditional methods and provide real-time monitoring. The incorporation of various nanoparticles with biosensors such as chitosan nanoparticles, silver nanoparticles (AgNPs), gold nanoparticles (AuNPs), multiwalled carbon nanotubes (MWCNTs), and graphene oxide, etc., facilitates the precise detection of various toxins, pesticides, and disease-causing pathogens in plants. Furthermore, the integration of portable devices and artificial intelligence (AI) increases their practical application in agricultural monitoring. Despite their promising aspect, issues with sensor stability, large-scale development, and cost-effectiveness also need to be addressed. Future studies are more concerned with improving durability, multiplex detection ability, and user-friendly field application. To enhance agricultural output, it is necessary to develop an early disease diagnosis approach that is heavily dependent on the ongoing development of cost-effective nanobiosensors. This review focuses on the recent studies of various nanobiosensors development and their operation mechanism for pathogen detection. Additionally, challenges associated with the worldwide acceptance of nano biosensors are also addressed. Overall, nanobiosensors are new-edge technology that enhances plant disease management strategies and risk mitigation in food security.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2025.1549547</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2025.1549547</link>
        <title><![CDATA[Rethinking 1T1R architecture and OxRAM stack for memristive neural network inference in-memory]]></title>
        <pubdate>2025-03-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Joel Minguet Lopez</author><author>Sylvain Barraud</author><author>David Cooper</author><author>Audrey Jannaud</author><author>Adeline Grenier</author><author>Aurelie Souhaité</author><author>Jean-Michel Pedini</author><author>Corinne Comboroure</author><author>Ahmed Gharbi</author><author>François Boulard</author><author>Clément Castan</author><author>Amélie Lambert</author><author>François Andrieu</author>
        <description><![CDATA[Neural Network hardware in-memory implementations based on memristive synapses are a promising path towards energy efficient Edge computing. Among others, Oxide-based Resistive Random Access Memory (OxRAMs) devices utilization for synaptic weight hardware implementation has shown promising performance on various types of Neural Networks, notably when coupled with bit-error correcting codes or adaptive programming schemes for the device intrinsic variability management. In this context, memristive footprint reduction coupling with Multi-Level-Cell (MLC) operation remains essential to hardware implement highly accurate state-of-art Neural Networks, whose number of parameters is exponentially increasing over time. In this work, a compact OxRAM-based 1 Transistor – 1 Resistor (1T1R) architecture, where the memory is integrated inside the 40 nm × 40 nm drain contact of thin-gate oxide FDSOI transistors, is demonstrated in 28 nm technology. The memory structure is optimized from the OxRAM active material level to the cell architecture. This results in 106 endurance and 11-level MLC encoding resilient to 109 inference cycles compatible with 0.0357 μm2 bitcell footprint potential in 28 nm technology. Altogether, the proposed 1T1R cell density is competitive with respect to ultra-dense 1S1R-based Crossbar arrays, while being compatible with in-memory Neural Network inference implementations on-chip.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2024.1443473</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2024.1443473</link>
        <title><![CDATA[Editorial: Women in nanotechnology: Vol. I]]></title>
        <pubdate>2024-07-01T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Neha Kaushik</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2024.1431198</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2024.1431198</link>
        <title><![CDATA[Editorial: Nanofluidics: computational methods and applications]]></title>
        <pubdate>2024-06-13T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Filippos Sofos</author><author>Konstantinos Ritos</author><author>Aggelos Avramopoulos</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2024.1364985</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2024.1364985</link>
        <title><![CDATA[A kinetic Monte Carlo approach for Boolean logic functionality in gold nanoparticle networks]]></title>
        <pubdate>2024-05-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jonas Mensing</author><author>Wilfred G. van der Wiel</author><author>Andreas Heuer</author>
        <description><![CDATA[Nanoparticles interconnected by insulating organic molecules exhibit nonlinear switching behavior at low temperatures. By assembling these switches into a network and manipulating charge transport dynamics through surrounding electrodes, the network can be reconfigurably functionalized to act as any Boolean logic gate. This work introduces a kinetic Monte Carlo-based simulation tool, applying established principles of single electronics to model charge transport dynamics in nanoparticle networks. We functionalize nanoparticle networks as Boolean logic gates and assess their quality using a fitness function. Based on the definition of fitness, we derive new metrics to quantify essential nonlinear properties of the network, including negative differential resistance and nonlinear separability. These nonlinear properties are crucial not only for functionalizing the network as Boolean logic gates but also when our networks are functionalized for brain-inspired computing applications in the future. We address fundamental questions about the dependence of fitness and nonlinear properties on system size, number of surrounding electrodes, and electrode positioning. We assert the overall benefit of having more electrodes, with proximity to the network’s output being pivotal for functionality and nonlinearity. Additionally, we demonstrate an optimal system size and argue for breaking symmetry in electrode positioning to favor nonlinear properties.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2024.1301320</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2024.1301320</link>
        <title><![CDATA[Theoretico-experimental analysis of bistability in the oscillatory response of a TaOx ReRAM to pulse train stimuli]]></title>
        <pubdate>2024-05-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>N. Schmitt</author><author>A. Ascoli</author><author>I. Messaris</author><author>A. S. Demirkol</author><author>S. Menzel</author><author>V. Rana</author><author>R. Tetzlaff</author><author>L. O. Chua</author>
        <description><![CDATA[Fading memory is the capability of a physical system to approach a unique asymptotic behaviour, irrespective of the initial conditions, when stimulated by an input from a certain class. Standard stimuli from the AC periodic class typically induce fading memory effects in non-volatile memristors, as uncovered for the first time back in 2016. Very recently, a deep investigation of resistance switching phenomena in a TaOx resistive random access memory cell revealed the capability of the nano-device to exhibit one of two possible oscillatory behaviours, depending upon the initial condition, when subject to a particular periodic excitation. This interesting finding was, however, left unexplained. Bistability is the simplest form of local fading memory. In a system, endowed with local fading memory under a given stimulus, the initial condition does not affect the long-term behaviour of the state as long as it is drawn from the basin of attraction of either of the distinct coexisting state-space attractors (two limit cycles for the periodically forced memristor acting as a bistable oscillator). Here, the history of the system, encoded in the initial condition, is, thus, erasable only locally through ad hoc stimulation. Motivated by the discovery of local history erase effects in our resistive random access memory cell, this study applies a powerful system-theoretic tool, enabling the analysis of the response of first-order systems to square pulse train-based periodic stimuli, known as the time-average state dynamic route, to an accurate physics-based mathematical model, earlier fitted to the nano-device, to determine a strategy for specifying the parameters of an excitation signal, consisting of the sequence of two square pulses of opposite polarity per period so as to induce various forms of monostability or multistability in the non-volatile memristor. In particular, as an absolute novelty in the literature, experimental measurements validate the theoretical prediction on the capability of the device to operate as one of two distinct oscillators, depending upon the initial condition, under a specific pulse train excitation signal. The coexistence of multiple oscillatory operating modes in the periodically forced resistive random access memory cell, an example par excellence of their unique non-linear dynamics, may inspire the development and circuit implementation of novel sensing and mem-computing paradigms.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2023.1296454</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2023.1296454</link>
        <title><![CDATA[Single-layer MoS2 solid-state nanopores for coarse-grained sequencing of proteins]]></title>
        <pubdate>2023-11-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Andreina Urquiola Hernández</author><author>Patrice Delarue</author><author>Christophe Guyeux</author><author>Adrien Nicolaï</author><author>Patrick Senet</author>
        <description><![CDATA[Proteins are essential biological molecules to use as biomarkers for early disease diagnosis. Therefore, their detection is crucial. In recent years, protein sequencing has become one of the most promising techniques. In particular, solid-state nanopores (SSNs) are powerful platforms for single biological molecule sensing without any labeling and with high sensitivity. Atomically thin two-dimensional (2D) materials with nanometer-sized pores, such as single-layer MoS2, represent the ideal SSN because of their ultimate thinness. Despite the benefits they offer, their use for protein sequencing applications remains very challenging since the fast translocation speed provides a short observation time per single molecule. In this work, we performed extensive molecular dynamics simulations of the translocation of the 20 proteinogenic amino acids through single-layer MoS2 nanopores. From ionic current traces, we characterized peptide-induced blockade levels of current and duration for each of the 20 natural amino acids. Using clustering techniques, we demonstrate that positively and negatively charged amino acids present singular fingerprints and can be visually distinguished from neutral amino acids. Furthermore, we demonstrate that this information would be sufficient to identify proteins using the coarse-grained sequencing technique made of only three amino acid categories depending on their charge. Therefore, single-layer MoS2 nanopores have great potential as sensors for the identification of biomarkers.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2023.1146852</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2023.1146852</link>
        <title><![CDATA[Choose your tools carefully: a comparative evaluation of deterministic vs. stochastic and binary vs. analog neuron models for implementing emerging computing paradigms]]></title>
        <pubdate>2023-05-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Md Golam Morshed</author><author>Samiran Ganguly</author><author>Avik W. Ghosh</author>
        <description><![CDATA[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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2023.1127363</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2023.1127363</link>
        <title><![CDATA[Large-scale nano-biosensing technologies]]></title>
        <pubdate>2023-02-15T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Ioulia Tzouvadaki</author><author>Themis Prodromakis</author>
        <description><![CDATA[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.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2022.1095291</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2022.1095291</link>
        <title><![CDATA[Layered GeI2: A wide-bandgap semiconductor for thermoelectric applications–A perspective]]></title>
        <pubdate>2022-12-12T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Archit Dhingra</author>
        <description><![CDATA[Layered GeI2 is a two-dimensional wide-bandgap van der Waals semiconductor, which is theorized to be a promising material for thermoelectric applications. While the value of the experimentally extrapolated indirect optical bandgap of GeI2 is found to be consistent with the existing theoretical calculations, its potential as a thermoelectric material still lacks experimental validation. In this Perspective, recent experimental efforts aimed towards investigating its dynamical properties and tuning its bandgap further, via intercalation, are discussed. A thorough understanding of its dynamical properties elucidates the extent of electron-phonon scattering in this system, knowledge of which is crucial in order to open pathways for future studies aiming to realize GeI2-based thermoelectric devices.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2022.1073863</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2022.1073863</link>
        <title><![CDATA[Editorial: In-memory sensing and computing: New materials and devices meet new challenges]]></title>
        <pubdate>2022-11-21T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Changjin Wan</author><author>Zhongrui Wang</author><author>Rohit Abraham John</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fnano.2022.998656</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fnano.2022.998656</link>
        <title><![CDATA[Improved two-photon photopolymerisation and optical trapping with aberration-corrected structured light]]></title>
        <pubdate>2022-10-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>D. J. Armstrong</author><author>A. B Stilgoe</author><author>T. A. Nieminen</author><author>H. Rubinsztein-Dunlop</author>
        <description><![CDATA[We demonstrate the effectiveness of phase only aberration corrections of structured light and their application to versatile optical trapping setups. We calculate phase corrections before (ex-situ) and after (in-situ) a high numerical aperture microscope objective using a spatial light modulator (SLM), and investigate how these corrections can be used to improve the efficiency and resolution of micro-structures fabricated through two-photon-photopolymerisation (2PP). We apply a phase retrieval algorithm to correct for distortions in a femtosecond laser that enables the fabrication of 3D structures using as many as 50 simultaneous foci. The inclusion of aberration correction in the fabrication process shows improved confinement of optically trapped particles and more efficient polymerisation while minimising intensity variations at individual foci, which potentially damage the structure during fabrication. We find that phase corrections allow for consistent voxel sizes, increased sharpness, and an expanded effective printing range when using an SLM, while also allowing for closer proximity of individual trap foci, minimising interference effects that hinder fabrication resolution.]]></description>
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