A bifunctional superconducting cell as flux qubit and neuron

• Dmitrii S. Pashin,
• Pavel V. Pikunov,
• Marina V. Bastrakova,
• Andrey E. Schegolev,
• Nikolay V. Klenov and
• Igor I. Soloviev

Beilstein J. Nanotechnol. 2023, 14, 1116–1126, doi:10.3762/bjnano.14.92

• obtained confirm the possibility of practical use of a single-contact inductively shunted interferometer in a quantum mode in adjustment circuits for q-processors. Keywords: adiabatic logic cell; flux qubit; Josephson junctio; quantum neuron; quantum parametron; superconducting quantum computers

• -to-output transformation function (sigma-neuron). Preliminary calculations have shown that under certain conditions, such a neuron can operate successfully in both classical and quantum modes [24][26][28][30]. The energy of the system in the Hamiltonian formalism can be expressed as follows: where

• coupling circuits and tuning schemes in quantum computing systems. A Bifunctional Superconducting Cell as an Adiabatic Neuron The analysis conducted in section “A Bifunctional Superconducting Cell as a Controllable Flux Qubit” showed that Landau–Zener transitions significantly affect the dynamics of the

A superconducting adiabatic neuron in a quantum regime

• Marina V. Bastrakova,
• Dmitrii S. Pashin,
• Dmitriy A. Rybin,
• Andrey E. Schegolev,
• Nikolay V. Klenov,
• Igor I. Soloviev,
• Anastasiya A. Gorchavkina and
• Arkady M. Satanin

Beilstein J. Nanotechnol. 2022, 13, 653–665, doi:10.3762/bjnano.13.57

• obtained results indicate the conditions under which the neuron possesses the required sigmoid activation function. Keywords: Josephson junction; quantum neuron; quantum-classical neural networks; superconducting quantum interferometer; Introduction The implementation of machine learning algorithms is

• work, we account for this by considering the neuron cell operation in a quantum regime. We investigate the dynamics of this cell in search of conditions that provide the required sigmoid activation function (conversion of the input magnetic flux into the average output current), suitable for the

• operation of the ANN as a perceptron [4]. The studied cell is called a quantum neuron or SQ neuron. Its closest analogue is the flux qubit used by D-Wave Systems in quantum annealers [38][39][40][41]. An important incentive for this work are the previously obtained results on classical adiabatic neurons

Tunable superconducting neurons for networks based on radial basis functions

• Andrey E. Schegolev,
• Nikolay V. Klenov,
• Sergey V. Bakurskiy,
• Igor I. Soloviev,
• Mikhail Yu. Kupriyanov,
• Maxim V. Tereshonok and
• Anatoli S. Sidorenko

Beilstein J. Nanotechnol. 2022, 13, 444–454, doi:10.3762/bjnano.13.37

• relevant for a number of niche tasks where performance and energy efficiency are critically important. In this paper, we consider the basic elements for superconducting neural networks on radial basis functions. We examine the static and dynamic activation functions of the proposed neuron. Special

• responsible for its own area of the parameter space of incoming data. This is the probabilistic or Bayesian approach, where radial basis functions (for example, Gaussian-like functions) are used as neuron activation functions. The most common networks operating on this principle are radial basis function

• implementation of the key elements of the discussed neural networks is the focus of this work. Results and Discussion Model of tunable Gauss-neuron: numerical simulations A common architecture of the considered RBFNs [49] is presented in Figure 1a. These networks have only one hidden layer of neurons on which

Micro- and nanotechnology in biomedical engineering for cartilage tissue regeneration in osteoarthritis

• Zahra Nabizadeh,
• Mahmoud Nasrollahzadeh,
• Hamed Daemi,
• Mohamadreza Baghaban Eslaminejad,
• Ali Akbar Shabani,
• Mehdi Dadashpour,
• Majid Mirmohammadkhani and
• Davood Nasrabadi

Beilstein J. Nanotechnol. 2022, 13, 363–389, doi:10.3762/bjnano.13.31

Morphology-driven gas sensing by fabricated fractals: A review

• Vishal Kamathe and
• Rupali Nagar

Beilstein J. Nanotechnol. 2021, 12, 1187–1208, doi:10.3762/bjnano.12.88

• fractal [39][40]. Figure 1 shows various fractal geometries found in nature. Complex patterns seen in human lungs, lines on the surface of human brains, neuron distribution, molecular chains of proteins, and DNA structures with double helix are described by fractal geometries [41]. Ice crystals

Self-assembly of amino acids toward functional biomaterials

• Huan Ren,
• Lifang Wu,
• Lina Tan,
• Yanni Bao,
• Yuchen Ma,
• Yong Jin and
• Qianli Zou

Beilstein J. Nanotechnol. 2021, 12, 1140–1150, doi:10.3762/bjnano.12.85

• combinations suggest that all assembled ultrastructures formed from various metabolites exhibit amyloidosis. These metabolites not only self-assemble into supramolecular amyloid fiber structures, but also have significant apoptotic effects on neuron model cells. Singh et al. [36] showed that the hydrophobic

The role of convolutional neural networks in scanning probe microscopy: a review

• Ido Azuri,
• Irit Rosenhek-Goldian,
• Neta Regev-Rudzki,
• Georg Fantner and
• Sidney R. Cohen

Beilstein J. Nanotechnol. 2021, 12, 878–901, doi:10.3762/bjnano.12.66

• most appropriate for the given task. Notwithstanding the terminology, an ANN does not work the same way a biological neuron works, but the fundamental idea of response to input being selectively passed forward in a network is similar [26]. Following the initial work of McCulloch and Pitts [25], the

• classification task. The hidden layer contains the “neurons” that connect the input layer (features) to the output layer (categories) and learns the relationship between them. This is done by processing their input to decide if, and how the information will be passed forward. The features are fed to each neuron

• boundary line in Figure 1). Then, a non-linear function is applied for each neuron. Without this step, termed “activation” (see below), multiple layers add no new knowledge to the problem. This non-linear function enables the neural network to learn complex non-linear decision boundaries instead of the

Intracranial recording in patients with aphasia using nanomaterial-based flexible electronics: promises and challenges

• Qingchun Wang and
• Wai Ting Siok

Beilstein J. Nanotechnol. 2021, 12, 330–342, doi:10.3762/bjnano.12.27

• known. Theodor Meynert pioneered the histological examination of the human brain in 1867 by using a blue dye to observe neuron cells in distinct portions of the cerebral cortex [13]. He observed that different parts of the cerebral cortex had different cell structures and found that sensory input was

Nitrogen-vacancy centers in diamond for nanoscale magnetic resonance imaging applications

• Alberto Boretti,
• Lorenzo Rosa,
• Jonathan Blackledge and
• Stefania Castelletto

Beilstein J. Nanotechnol. 2019, 10, 2128–2151, doi:10.3762/bjnano.10.207

• ) magnetic fields have been measured at the macroscale with coarse spatial and/or temporal resolution, using MRI methods and magnetoencephalography for example. This does not supply single-neuron spatial resolution without scalability to functional networks or intact organisms. In [34], AP magnetic sensing

• has been realized with single-neuron sensitivity and intact organism applicability with an NV quantum diamond microscope under ambient conditions. The method was applied for excised single neurons from marine worm and squid and then to marine worms for extended periods. The key element to making the

• distance does not allow for single-neuron action potential sensitivity. A key point of NV magnetometry is to set up a correlation with MRI-contrast methods based on conventional MRI. The comparison is typically achieved only in subcellular imaging due to the scale associated with NV magnetometry. A method

Flexible freestanding MoS₂-based composite paper for energy conversion and storage

• Florian Zoller,
• Jan Luxa,
• Thomas Bein,
• Dina Fattakhova-Rohlfing,
• Daniel Bouša and
• Zdeněk Sofer

Beilstein J. Nanotechnol. 2019, 10, 1488–1496, doi:10.3762/bjnano.10.147

• -11456S) and with the financial support of the Neuron Foundation for science support.

Effects of gold and PCL- or PLLA-coated silica nanoparticles on brain endothelial cells and the blood–brain barrier

• Aniela Bittner,
• Angélique D. Ducray,
• Hans Rudolf Widmer,
• Michael H. Stoffel and
• Meike Mevissen

Beilstein J. Nanotechnol. 2019, 10, 941–954, doi:10.3762/bjnano.10.95

• -lactide) (PLLA), and Au-NPs used in LTS on cells of the brain, namely microglial and neuron-like cells. Si-NPs were further characterized regarding their interactions with cells by using organotypic hippocampal tissue slices and primary cultures. All types of NPs were found in microglial cells and neuron

• , oxidative stress and an increase in inflammatory cytokines in dopaminergic neuron-like cells. In vivo intranasal administration of these NPs corroborated these findings and showed localization of Si-NPs mainly in the striatum and hippocampus [13]. As LTS finds its application in vessels of the brain, the

Bioinspired self-healing materials: lessons from nature

• Joseph C. Cremaldi and
• Bharat Bhushan

Beilstein J. Nanotechnol. 2018, 9, 907–935, doi:10.3762/bjnano.9.85

• cellular response. The cells meant to maintain homeostasis around the PNS, Schwann cells, and clear away material to help neuron regrowth (rather than scarring as is seen in the CNS) and restore function. Vertebrate hard tissue: Hard tissue in vertebrates refers to bone. Bones are the porous and

Recombinant DNA technology and click chemistry: a powerful combination for generating a hybrid elastin-like-statherin hydrogel to control calcium phosphate mineralization

• Mohamed Hamed Misbah,
• Mercedes Santos,
• Luis Quintanilla,
• Christina Günter,
• Matilde Alonso,
• Andreas Taubert and
• José Carlos Rodríguez-Cabello

Beilstein J. Nanotechnol. 2017, 8, 772–783, doi:10.3762/bjnano.8.80

• size and morphologies of CP under mild reaction conditions, it is difficult to control the crystallinity and phase purity of the synthesized CP nanostructures with narrow size distribution [9][12]. Furthermore, the generation of delicate nanostructures, for example neuron-like morphology of amorphous

• , the self-assembly properties of ELRs have a marked influence on the mineralization activity of SNA15. These complementary functionalities give rise to the formation of fibre- or petal-like HA, in addition to amorphous CP with a neuron-like morphology. In the ELRs used in this current work (IK24 and

• building block H3 [(IK)2-SNA15-(IK)2] inhibits the transformation of ACP into the crystalline phase in solution, thus giving rise to the formation of a neuron-like morphology. In the confined state (IK24 and H3AH3 hydrogels in the current work) this effect seems to be observed after incubation for 4 days

Adiabatic superconducting cells for ultra-low-power artificial neural networks

• Andrey E. Schegolev,
• Nikolay V. Klenov,
• Igor I. Soloviev and
• Maxim V. Tereshonok

Beilstein J. Nanotechnol. 2016, 7, 1397–1403, doi:10.3762/bjnano.7.130

• ], those for signal classification and recognition are less developed. A solution for the recognition problem by employing perceptron ANNs was sought in earlier works with SQUID-based neuron switching [14][15] in the resistive state. In subsequent variations [16][17], this feature was found to drastically

• reduce the energy efficiency of the superconducting circuit. In another recent approach to multilayer perceptron, SQUIDs were utilized as nonlinear magnetic flux transducers, allowing the ANN to persist in the superconducting state [18]. The implemented neuron scheme is quite analogous to the quantum

• orders of magnitude (including the power required for superconducting circuit cooling) [21][22][23][24]. While the activation function of the QFP neuron was not analyzed in [18], our assay shows that it is not well suited for the chosen type of network. The activation function commonly has a highly

Unraveling the neurotoxicity of titanium dioxide nanoparticles: focusing on molecular mechanisms

• Bin Song,
• Yanli Zhang,
• Jia Liu,
• Xiaoli Feng,
• Ting Zhou and
• Longquan Shao

Beilstein J. Nanotechnol. 2016, 7, 645–654, doi:10.3762/bjnano.7.57

• contributed to neurotoxicity. Ze et al. [57] found that after mice were treated with TiO2 NPs by oral exposure, histopathological changes in the hippocampus were occurred. Meanwhile, affected neuron ultrastructures, such as swollen mitochondria and impaired nuclear membrane were detected. Long-term

Tattoo ink nanoparticles in skin tissue and fibroblasts

• Colin A. Grant,
• Peter C. Twigg,
• Richard Baker and
• Desmond J. Tobin

Beilstein J. Nanotechnol. 2015, 6, 1183–1191, doi:10.3762/bjnano.6.120

• toxicity or biocompatibility of nanoparticles is an extremely important consideration for many of the aforementioned proposed applications. In particular carbon nanotubes, commonly used in applications such as drug delivery [10] and directed growth of neuron cells [11], have been shown to exhibit

Carbon-based smart nanomaterials in biomedicine and neuroengineering

• Antonina M. Monaco and
• Michele Giugliano

Beilstein J. Nanotechnol. 2014, 5, 1849–1863, doi:10.3762/bjnano.5.196

• or nanoscale roughness (Figure 3c). Moreover, in the same work, mathematical modelling and electrophysiology were used to probe a contingent connection between the effects observed at single-neuron level and those detected at the level of neuronal networks, leading to the speculation that the tight

• positively charged surface showed a greater number of neurites per neuron, a longer length of neurites and a greater number of branches per neurite. However, the lack of a direct comparison with the conventional control conditions (i.e., glass or plastic, polymeric, culture substrates) makes it difficult to

• and of (E) action potentials. Reproduced and modified from [118] with permission. Copyright 2005 American Chemical Society. CNTs affect single-neuron excitability, inducing depolarising after-potentials (a). This behaviour is specifically attributable to CNTs, as it has been observed neither for cells

Growth and structural discrimination of cortical neurons on randomly oriented and vertically aligned dense carbon nanotube networks

• Christoph Nick,
• Sandeep Yadav,
• Ravi Joshi,
• Christiane Thielemann and
• Jörg J. Schneider

Beilstein J. Nanotechnol. 2014, 5, 1575–1579, doi:10.3762/bjnano.5.169

• . These neuron cells attach preferentially on the CNT sidewalls of the vertically aligned CNT architecture instead than onto the tips of the individual CNT pillars. Keywords: carbon nanotube; chemical vapour deposition; interface; neuron; scaffold; Findings Biochemically functionalised carbon nanotubes

• interest in the biomedical community since they have outstanding potential as a substrate for growing different cell type materials [6][7][8]. Due to their very good electrical conductivity they are a promising substrate for neuron growth as well as for biocompatible electrode materials to record and/or

• chemistry viewpoint in future work. In conclusion, pristine randomly and vertically aligned CNTs architectures were studied with respect their use as substrates for neuron cell growth. Both CNT architectures are unique hierarchical structures to direct and control neural cell growth. To the best of our

Fabrication of multi-parametric platforms based on nanocone arrays for determination of cellular response

• Lindarti Purwaningsih,
• Tobias Schoen,
• Tobias Wolfram,
• Claudia Pacholski and
• Joachim P. Spatz

Beilstein J. Nanotechnol. 2011, 2, 545–551, doi:10.3762/bjnano.2.58

• finding for research dealing with the reactions of neuron-like tissue in the immediate moments after direct contact with an implanted surface. Keywords: block copolymer nanolithography; cell adhesion; nanostructures; surface chemistry; surface topography; Introduction Nanostructured materials for

Infrared receptors in pyrophilous (“fire loving”) insects as model for new un-cooled infrared sensors

• David Klocke,
• Anke Schmitz,
• Helmut Soltner,
• Herbert Bousack and
• Helmut Schmitz

Beilstein J. Nanotechnol. 2011, 2, 186–197, doi:10.3762/bjnano.2.22

• enclosure of the dendritic tip of the mechanosensitive neuron inside the core in a liquid-filled chamber. Most probably a photomechanic IR sensillum acts as a microfluidic converter of infrared radiation which leads to an increase in internal pressure inside the sphere, which is measured by a

• mechanosensitive neuron. A simple model for this biological IR sensor is a modified Golay sensor in which the gas has been replaced by a liquid. Here, the absorbed IR radiation results in a pressure increase of the liquid and the deflection of a thin membrane. For the evaluation of this model analytical formulas

• of the mechanosensitive neuron inside the inner core in a liquid-filled chamber. Most probably, IR radiation absorbed by the proteins, the chitin fibres, and the water of the sensillum heats up the sphere, which immediately causes thermal expansion especially of the liquid inside the microfluidic