Hasil untuk "Electric apparatus and materials. Electric circuits. Electric networks"

A. D. Molchanova, L. H. Yin, L. P. Gao et al.

Out-of-plane and in-plane electric polarization, which rarely coexist in a two-dimensional (2D) ferroelectric material, offer different advantages in ferroelectricity-based devices. Here, we report the coexistence of in-plane and out-of-plane electric dipoles, along with various phase transitions, in 2D van der Waals layered TlGaS2 single crystal. Quantum paraelectricity was observed along both in-plane and out-of-plane directions of the TlGaS2 crystal. Detailed investigation of the quantum paraelectric soft-mode behavior reveals a close correlation between the electric dipoles and the off-center displacement of Tl1+ ions with 6s2 lone pairs in TlGaS2. Anomalies near temperatures of about 120 K and 60-75 K in dielectric and/or infrared spectra indicate the existence of local or weak long-range structural transitions in TlGaS2. Our results provide important experimental evidence for elucidating the phase transitions and coexistence of in-plane and out-of-plane electric dipoles in 2D layered TlGaS2.

Feiran Wang, Charles E. D. Heaton, Nathan D. Cottam et al.

Abstract The exceptional electrical properties of graphene with high sensitivity to external stimuli make it an ideal candidate for advanced sensing technologies. Inkjet printing of graphene (iGr) can provide a versatile platform for multifunctional sensor manufacturing. Here the multifunctional sensor enabled by combining the design freedom of inkjet printing with the unique properties of graphene networks is reported on. A fully inkjet printed multimaterial device consists of two layers of iGr stripes separated by a dielectric polymeric layer of tripropylene glycol diacrylate (TPGDA). In these devices, the bottom iGr layer, capped with TPGDA, provides temperature sensing, the top uncapped iGr is sensitive to the external atmosphere, while the capacitance between the two iGr layers is sensitive to the applied pressure. The fast, sensitive, and reproducible performance of these sensors are demonstrated in response to environmental stimuli, such as pressure, temperature, humidity, and magnetic field. The devices are capable of simultaneous sensing of multiple factors and are successfully manufactured on a variety of substrates, including Si/SiO2, flexible Kapton films and textiles, demonstrating their potential impact in applications compatible with silicon technologies as well as wearable and healthcare devices.

Sarah Grützmacher, Max Heyl, Norbert Koch et al.

Abstract Silicon‐based technology is approaching scalability limits due to severe short‐channel effects arising from its intrinsic bulk properties. In contrast, two‐dimensional (2D) transition metal dichalcogenides (TMDCs) exhibit remarkable resilience to these effects because of their atomic‐scale thickness, positioning them as promising candidates for next‐generation optical and electronic devices. However, realizing 2D material‐based technology still requires the development of local p‐ and n‐type doping methods essential for complementary circuits. Self‐assembled monolayers (SAMs) have shown the ability to locally engineer electronic energy levels in 2D TMDCs to address this challenge. In this study, we demonstrate local engineering of electronic energy levels on micrometer scale in semiconducting single‐layer (1L) MoS2 by patterning the supporting substrate with functional SAMs via microcontact printing (µCP). Three SAMs were selected: two with large opposing dipole moments and one non‐dipolar reference. Their impact on surface properties particularly the work function and on optoelectronic properties of 1L‐MoS2 was investigated via Kelvin probe microscopy and photoluminescence (PL) mapping. Significant shifts in work function and PL were observed. FETs fabricated on locally patterned substrates enabled direct comparison, confirming that threshold voltage shifts up to 80 V and ON‐current increases by two orders of magnitude arise solely from SAM polarity. This work demonstrates that µCP and the electrostatic doping capabilities of dipolar SAMs offer a straight forward and scalable approach to locally engineering 1L‐MoS2 energy levels.

Forrest Mozer, Oleksiy Agapitov, Stuart Bale et al.

On November 6, 2024, the Parker Solar Probe flew past Venus to make the first accurate electric field measurement in the nightside Venusian magnetosphere. To achieve this result, the electric field antennas were current biased in a way never before experienced by an electric field detector. This biasing requirement, that the positive bias current in the Venus shadow be about equal to the electron thermal current, is discussed and illustrated. About one minute of useful electric f ield data in the eight-minute nightside magnetosphere crossing was obtained, during which the only feature observed was a few Hz signal. This result, along with the magnetic field measurements, showed that there were few if any electromagnetic waves, such as low-frequency electromagnetic turbulence or whistlers, in the nightside crossing. Instead, a few Hertz, purely electrostatic signal was found. This suggests that the interaction of the solar wind with an unmagnetized body having an ionosphere may be different from that of previously studied magnetized bodies. In the sunlit flanks, many electromagnetic wave modes were observed. These results describe the first step in the proper technique for future measurements of electric fields in shadow.

Yiyang Li, Maria Lukatskaya

Bhanu Priyanka Valluri, Nitin Sharma

Wireless Sensor Networks (WSNs) are networks of low-power, low-cost devices that may gather data for many applications. These networks rely heavily on Medium Access Control (MAC) features for administration due to the critical roles of energy and security. Due to the low resources of the nodes, traditional security methods are unsuitable for WSNs, hence lightweight cryptographic algorithms are required to ensure adequate security. Nodes, which are communication devices in WSNs, are used. Data trust, data availability, authentication, and data integrity are just some of the security concerns raised by the deployment of such nodes. To address these concerns and ensure secure data transmission, cryptographic methods should be utilized. Keeping information transmitted over a wireless sensor network secure is complicated by the technology's increasing popularity. The problem arises because of the constraints imposed by finite supplies of energy, data storage, and processing power. This research offers a method for node validations in WSN for secure data transmission, taking into account the characteristics of wireless sensor nodes where the energy consumption for transferring data is substantially larger than that for calculation. Cryptography keys will be used for node authentication and for secure data transmission. Messages sent between nodes in a WSN must be encrypted, and the network must keep a key for encryption and decryption. As a result, Key management plays a crucial role in ensuring WSN safety. Each node will be allocated with a key set which is used for node validation, encryption and decryption. Secure and efficient data transmission in WSN relies on obtaining such a key arrangement in a constrained resource setting. Plaintext assaults, attacks using brute force, attacks via side channels, and computational complexity are just a few of the security problems that plague today's algorithms. This research presents a scheme for protecting sensor data during transmission and after it has been received by nodes. This research proposes a Exceptional Key based Node Validation for Secure Data Transmission using Asymmetric Cryptography (EKbNV-SDT-AC) model. This research performs node validation, encryption and decryption of data in the WSN to securely transmit the data from source to destination. The proposed model when compared with the traditional model performs better in data node validation and secure data transmission.

Pallavi S. Bangare, Kishor P. Patil

The MQTT (Message Queuing Telemetry Transport) protocol used the pub-sub model for IoT communication. Bolstering security with two-way authentication becomes a critical necessity. This paper presents a novel algorithm that fortifies MQTT with enhanced security measures, utilizing a refined MQTT implementation that integrates with a Merkle tree. HBMQTT Broker increases security as it uses different plugins, like the authentication plugin and the authorization plugin. These plugins serve to add extra layers of protection, reinforcing security protocols and heightening resilience to potential threats. The Merkle tree integration enhances data security during data transmission, effectively distinguishing between authentic and inauthentic data streams. Merkle trees generate tokens, which are used for secure data transmission. The algorithm is tested with four different hacking adversarial attacks: man-in-The-Middle (MITM), malware attack, denial of service (DoS), and phishing attack. Space and time complexity are also calculated for these attacks.

Md Arif Iqbal, Srinivas Rahul Sapireddy, Sumanth Dasari et al.

Using a control variable, the functionality of Polymorphic circuits can be modified, making them adaptable and useful for reconfiguring circuit behavior — all the way from gate level to system level. State-of-the art polymorphic circuits are based on custom non-linear circuit design or emerging devices such as ambipolar FET, configurable magnetic devices etc. While some of these approaches are inefficient in performance, others involve exotic devices. The Crosstalk computing based polymorphic circuits offer a fresh perspective. In Crosstalk, the interconnect interference between nanoscale metal lines is intentionally engineered to exhibit the programmable Boolean logic behavior. This approach relies on the coupling between metal lines and not on the transistors for computing, resulting in better scalability, security by obscurity, and fault tolerance by reconfiguration. Our novel approach is backed by the mathematical formulation that conveys the rationale to generalize and achieve a wide variety of polymorphic circuits. Our experiments, including design, simulation, and Power Performance Area (PPA) characterization results indicate that crosstalk circuits provide significant improvement in transistor count (about 3x), switching energy (2x), and speed (1.5x) for polymorphic logic circuits. In the best-case scenario, the transistor count reduction is 5x. This paper presents Crosstalk computing’s fundamentals, polymorphism and the scalability aspects to compete/co-exist with CMOS for digital logic implementations below 10 nm. Our scalability study uses Open Source 7 nm PDK, considers all process variation aspects and accommodates worst-case scenarios. The study results for various benchmark circuits show that the Crosstalk technology is a viable alternative to CMOS for digital logic implementations below 10 nm, having 48% density, 57% power, and 10% performance gains over equivalent CMOS counterparts. Finally, we compare Crosstalk Polymorphic Circuit design technique with similar approaches described in related works and discuss its features and constraints.

Kent Edrian Lozada, Dong-Jin Chang, Dong-Ryeol Oh et al.

The distinct advantages of low power consumption and hardware compactness make SAR ADCs especially appealing in scaled CMOS technologies, garnering significant attention. The residue left on the capacitor digital-to-analog converter (CDAC) after conversion in the SAR ADC negates the need for complex residue extraction circuits. This crucial feature has inspired numerous SAR-assisted architectural variations, employed in a range of applications from high resolution to high speed. This article introduces several energy-efficient hybrid ADC architectures that incorporate SAR ADCs as their sub blocks, including the following: SAR-assisted subranging SAR, which saves DAC switching power and can detect skew errors for time-interleaved ADCs; SAR-flash hybrid for energy-efficient high-speed conversion; SAR-assisted dual-residue pipelined ADC, which eliminates the stringent requirement for residue gain accuracy; and SAR-assisted delta–sigma modulator (DSM) with digital-domain noise coupling, which reduces the number of required analog integrators.

Rabindra Basnet, Taksh Patel, Jian Wang et al.

Abstract Recent developments in 2D magnetic materials have motivated the search for new van der Waals magnetic materials, especially Ising‐type magnets with strong magnetic anisotropy. Fe‐based MPX3 (M = transition metal, X = chalcogen) compounds such as FePS3 and FePSe3 both exhibit an Ising‐type magnetic order, but FePSe3 receives much less attention compared to FePS3. This work focuses on establishing the strategy to engineer magnetic anisotropy and exchange interactions in this less‐explored compound. Through chalcogen and metal substitutions, the magnetic anisotropy is found to be immune against S substitution for Se whereas tunable only with heavy Mn substitution for Fe. In particular, Mn substitution leads to a continuous rotation of magnetic moments from the out‐of‐plane direction toward the in‐plane. Furthermore, the magnetic ordering temperature displays non‐monotonic doping dependence for both chalcogen and metal substitutions but due to different mechanisms. These findings provide deeper insight into the Ising‐type magnetism in this important van der Waals material, shedding light on the study of other Ising‐type magnetic systems as well as discovering novel 2D magnets for potential applications in spintronics.

Hsin‐Yuan Chiu, Tzu‐Ang Chao, Nathaniel S. Safron et al.

Abstract Carbon nanotube (CNT) field effect transistors (CNFETs) show promise for the next generation VLSI systems due to their excellent scalability, energy efficiency, and speed. However, high leakage current is a drawback of large diameter CNTs (diameter (DCNT) ≥ 1.4 nm) due to the small electronic band gap (EG) ≤ 0.6 eV and effective mass. This work investigates the on‐current and off‐current tradeoff for two populations of semiconducting‐enriched CNT with DCNT ≈ 1.0 nm displaying a simultaneous 50x improvement in minimun current (IMIN) with 2.5x degradation in contact resistance compared to DCNT ≈ 1.4 nm using a Pd side‐bonded contact. A method to enhance the performance of low‐leakage CNFETs is demonstrated using sub‐monolayer self‐aligned contact doping with 0.8 nm of MoOX, which delivers a 57% reduction in contact resistance to DCNT ≈ 1.0 nm. Robustness is verified after annealing at 200 °C for 30 min and monitoring stability across 6 months post‐fabrication with no change in electrical behaviors.

Ryota Yambe, Satoru Hayami

A skyrmion crystal (SkX) has attracted much attention in condensed matter physics, since topologically nontrivial structures induce fascinating physical phenomena. The SkXs have been experimentally observed in a variety of materials, where the Zeeman coupling to the static magnetic field plays an important role in the formation of the SkXs. In this study, we theoretically propose another route to generate the SkXs by using a circularly polarized electric field. We investigate a non-equilibrium steady state in a classical frustrated Heisenberg magnet under the circularly polarized electric field, where the electric field is coupled to the electric polarization via the spin-current mechanism. By numerically solving the Landau-Lifshitz-Gilbert equation at zero temperature, we show that the electric field radiation generates a SkX with a high topological number in the high-frequency regime, where the sign of the skyrmion number is fixed to be negative (positive) under the left (right) circularly polarized field. The intense electric field melts these SkXs and generates isolated skyrmions. We clarify that the microscopic origin is effective electric-field-induced three-spin interactions by adopting the high-frequency expansion in the Floquet formalism. Furthermore, we find that the electric field radiation generates another type of SkXs, a bimeron crystal, in the low-frequency regime. Our results provide a way to generate the SkXs and control the topology by the circularly polarized electric field.

Roman Ya. Kezerashvili, Shalva M. Tsiklauri, Anastasia Spiridonova

We predict the formation of intravalley controllable trions in buckled two-dimensional (2D) materials such as silicene, germanene, and stanene monolayers in an external electric field. Performing a study within the framework of a nonrelativistic potential model using the method of hyperspherical harmonics (HH), the three-body Schrödinger equation is solved with the Rytova-Keldysh potential by expanding the wave functions of a trion in terms of the HH. Then, we numerically solve a resultant system of coupled differential equations. The ground state energies of intravalley trions controlled by the external electric field are presented. The dependencies of the binding energy (BE) of trions in silicene, germanene, and stanene as a function of the electric field are shown to be qualitatively similar. BEs of trions formed by $A$ and $B$ excitons have a non-negligible difference that increases slightly as the electric field increases. We demonstrate that trion BEs can be controlled by the external electric field.

Mehmet Yilmaz, Ramadan ElShatshat

Arif Ahmed, Evangelos Pompodakis

Dazhi Wang, Pengfei Xu, Yichang Cui et al.

Abstract Nanomechanical resonators are expected to be exceptional sensors for high‐performance mass detection, mechanical sensing, and signal processing. In this paper, zinc oxide nanobeam resonators are produced based on single‐crystal ZnO nanowire, which has a typical diameter down to a few nanometers and the length of hundreds of micrometers. This resonator has the characteristics of high aspect ratio nanobeam structure and reliable material. It is observed that the resonance frequency of ZnO nanobeam resonator is up to 1.47 MHz with a high quality factor of 2300 at room temperature, which will play a key role in high‐sensitivity mass detection. The mass detection of ZnO nanobeam resonator is demonstrated by depositing platinum atoms on the middle of the beam, which shows a sensitivity of 11.13 Hz fg−1 indicating its ultrasensitive mass detection capability. In addition, according to the experiment, the molecular dynamics simulations for the resonator is established, which shows that the detection resolution down to 0.2 yg at room temperature can be realized based on this resonator. The results show that the ZnO nanobeam resonator has enormous potential in ultrasensitive detection for biosensing and gas sensing.

Jinwoo Choi, Kyuho Lee, Minhwan Lee et al.

Abstract An additive, 1,4‐butadiene sulfone (BDS), which generates H2SO3 by in situ thermal retro‐Diels‐Alder decompositions, is used for preparing high β‐phase polyvinylidene fluoride (PVDF) films. Because of preferential multiple non‐covalent interactions of H2SO3 with all‐trans configuration of PVDF, β‐phase PVDF is spontaneously induced without mechanical drawing and/or extensive thermal annealing process. PVDF films cast from PVDF/BDS/water solutions exhibit high β‐phase content (fβ = 95%) when the BDS concentration is only cBDS = 1.0 wt%, which is confirmed by polarized optical microscopy (POM), SEM, Fourier transform infrared spectroscopy (FT‐IR), differential scan calorimetry (DSC), and 2D grazing incidence wide‐angle X‐ray scattering (GIWAXS). Because of the high β‐phase content, PVDF films prepared by using BDS exhibit excellent ferroelectric and piezoelectric properties (Ec = 50 MV/m, Pr = 5 µC/cm2, and d33 = ≈‐25 pm/V). Furthermore, a triboelectric nanogenerator (TENG) developed with high β‐phase PVDF film exhibits enhanced performance as 2.5 times higher than neat PVDF film in output charge density, allowing reliable operation of conventional electronic devices.

Yousef Methkal Abd Algani, Mahyudin Ritonga, B. Kiran Bala et al.

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal).This article has been removed at the request of the Authors, due to incomplete authorisation for the publication of the article from one of the author's institutions. The authors sincerely apologize for the inconvenience.

K. Samunnisa, G. Sunil Vijaya Kumar, K. Madhavi

Cloud Computing is popular nowadays due to its storage and data access services. Security and privacy are prime concerns when network threats increase. Cloud computing offers organizations and enterprises a scalable, flexible, and cost-effective infrastructure to store data on the Web. An anomaly-based IDS implementation protects the integrity of the data in a database by identifying and quarantining records when something appears to have changed unexpectedly. Machine learning based clustering and classification methods are used for anomaly based IDS attack classification and scalability in advanced networking environments. Machine learning is a fast, efficient, and adaptable approach to develop intrusion detection models that can deal with emerging threats, i.e., known and unknown attacks (including zero-day attacks). This paper proposes an efficient Hybrid clustering and classification models for implementing an anomaly-based IDS for malicious attack type classifications such as normal (no intrusion), DoS, Probe, U2R, and R2L using threshold-based functions, and the results are tested with two different threshold values (e), 0.01 & 0.5. The experiments have been performed on two tested datasets, namely, NSL-KDD and KDDcup99. Detection rate, False alarm ratio, and accuracy have been used to study the performance of the proposed methodology. After applying the proposed approach, the K-means with random forest has been shown at two different threshold values to have a better classification accuracy, detection rate, and false alarm rate of 99.85%, 99.78% and 0.09% on the NSL-KDD dataset and 98.27%, 98.12% and 2.08% respectively on the KDDcup99 dataset.

Pawan, Rohtash Dhiman

Decryption of Motor Imagery (MI) activity from an Electroencephalogram (EEG) data is a significant part of the Brain-Computer Interface (BCI) technology that allows motor-disabled persons to connect with external devices. Channel selection, feature extraction, and classification are essential requirements for an effective BCI system. Non-stationary EEG data confuses designing EEG-based BCIs. In this study, the Pearson correlation coefficient (PCC) technique is employed for channel selection for EEG signals in the BCI system. It selects the most associated fourteen channels for the sensorimotor area of subject's brain. The popular signal processing technique wavelet packet decomposition (WPD) is employed for feature extraction. After that approximate entropy (ApEn) feature is calculated for selected channels. The proposed study is a novel scheme combining Pearson correlation coefficient-based channel selection technique and wavelet packet decomposition for classifying MI signals. Finally, extracted features are classified with the help of two benchmark techniques, Support Vector Machine (SVM) and K-Nearest Neighbors (K-NN) and achieve maximum accuracy of 91.66% and 90.33%, respectively. The proposed technique is examined on freely available EEG datasets BCI competition-IV-Dataset I to prove its superiority over previously reported approaches. Obtained experimental findings demonstrated advantages over previous methods in terms of classification accuracy.