Electronic Design Research Articles

Data Generation and Training of Surrogate Models for Friction Factor and Nusselt Number in Low Reynolds Number Flows Through Pin Fin Geometries

Abstract The design of various biomedical, electronics cooling, and microfluidic devices relies on geometry-specific models and empirical correlations for flow and heat transfer through microscale pin fin geometries. Machine learning (ML) techniques are being used across many branches of science to develop more generalized surrogate models that can predict such transport processes. To collapse the simulation of flow and thermal properties across many different pin fin surfaces into a single predictive tool, the present study develops machine-learning-based surrogate models for the friction factor and Nusselt number (for constant wall temperature conditions) for fully developed low Reynolds number flow across pin fin geometries of differing cross section shape (circular, square, triangular) in aligned or staggered arrangements, oriented at any angle to the incoming flow, and for a range of transverse and longitudinal pitches, with water as the working fluid. The model training data are generated using an automated workflow that allows thousands of numerical simulations to be carried out on across different geometric and flow configurations. A total of ∼14,800 distinct simulation cases, for both friction factor and Nusselt number, are generated while varying the Reynolds number and aforementioned geometric parameters to train and test the machine learning models. The machine learning model architecture takes inputs of both image and vector data, and then outputs a scalar friction factor or Nusselt number. The trained models yield a goodness of fit (R2) value of 0.98 on unseen data.

Electronic asymmetry of lattice oxygen sites in ZnO promotes the photocatalytic oxidative coupling of methane.

Photocatalytic oxidative coupling of methane with oxygen is promising to obtain valuable muti-carbon products, yet suffering low reactivity. Here, we apply cerium modifications on zinc oxide-supported gold catalysts based on the electronic asymmetry design of lattice oxygen to improve the coupling activity. The methane conversion rate exceeds 16000 μmol g-1 h-1 with muti-carbon selectivity of 94.9% and catalytic durability of 3 days, and it can increase to 34000 μmol g-1 h-1 under more thermal assistance, with a turnover frequency of 507 h-1 for ethane and an apparent quantum efficiency of 33.7% at 350 nm. According to systematic characterizations and theoretical analysis, cerium dopants not only can boost the formation of reactive oxygen species but also intervene in the vivacity of lattice oxygen by manipulating metal-oxygen bond strength, thereby leading to favorable methyl desorption to form ethane and quick water release. This work provides insight into the rational design of efficient photocatalysts for aerobic methane-to-ethane conversion.

Electronic properties of corundum-like Ir2O3 and Ir2O3-Ga2O3 alloys

In the hexagonal, corundum-like structure, α-Ga2O3 has a bandgap of ∼ 5.1 eV, which, combined with its relatively small electron effective mass, high Baliga's figure of merit, and high breakdown field, makes it a promising candidate for power electronics. Ga2O3 is easy to dope n-type, but impossible to dope p-type, impeding the realization of some electronic device designs. Developing a lattice-matched p-type material that forms a high-quality heterojunction with n-type Ga2O3 would open new opportunities in electronics and perhaps optoelectronic devices. In this work, we studied Ir2O3 as a candidate for that purpose. Using hybrid density functional theory calculations we predict the electronic band structure of α-Ir2O3 and compare that to α-Ga2O3, and study the stability and electronic properties of α-(IrxGa1−x)2O3 alloys. We discuss the band offset between the two materials and compare it with recently available experimental data. We find that the Ir d bands that compose the top of the valence band in α-Ir2O3 are much higher in energy than O p bands in α-Ga2O3, possibly enabling effective p-type doping. Our results provide an insight into using the Ir2O3 or Ir2O3-Ga2O3 alloys as p-type material lattice-matched to α-Ga2O3 for the realization of p–n heterojunctions.

Two-Level Electronic Switching in Individual Manganese-Phthalocyanine Molecules with Jahn-Teller Distortion.

Understanding single molecular switches is a crucial step in designing and optimizing molecular electronic devices with highly nonlinear functionalities, e.g., gate voltage-dependent current switching. An atomically thin insulating template, in combination with scanning probe techniques, is an ideal platform to study such switches on the single-molecule level. In this study, we investigate manganese-phthalocyanine (MnPc) molecules on monolayer-thin epitaxial hexagonal boron nitride (h-BN) on Rh(111) by scanning tunneling microscopy (STM), spectroscopy (STS), and theoretical calculations. Several interesting phenomena are found: (1) high-resolution STM imaging of the molecular orbitals reveals symmetry breaking from D4h to D2h, observed in one type of MnPc. By comparison with simulations, this phenomenon can be attributed to the Jahn-Teller effect due to the negative charging of the molecule. (2) Ambipolar transitions at the molecule occur at fixed sample biases of about ±0.4 V, which manifest as negative differential conductance signatures in dI/dV spectroscopy. (3) The stochastic two-level switching, resulting in telegraphic noise in the tunneling current, manifests as a one-electron activated process. We present a two-level switching model to accurately describe a bias-dependent current-driven transition between the levels and reveal a first-order transition. The understanding and tailoring of molecular switches on the ultrathin insulating layer will be very helpful for future organic electronics design and application.

Perancangan E-Monitoring Laporan Polisi Menggunakan Metode Prototype pada Polsek Semendawai Suku III

The system for receiving police reports at the Semendawai Tribe III Police is currently still done manually by typing them in Microsoft Word which are then printed and stored in hard copy in the criminal investigation room. Storing files in hard copy form results in files piling up, being scattered, being tucked away, as well as the potential for losing files or having difficulty finding files when they are needed again. Apart from that, police report files in softcopy form are sometimes accidentally deleted, not copied, and immediately overwritten with a new police report, resulting in data loss that cannot be recovered. Therefore, this research aims to design electronic monitoring of police reports using a prototype method that allows gradual development of the system based on input from users. The electronic monitoring design was carried out in several stages, starting with the creation of a report recording module, followed by a combination of report status monitoring features, and ending with the implementation of automatic backup. Each stage is tested and evaluated separately to ensure optimal quality and usability. The research results show that this system is able to increase the efficiency of report management, can minimize the risk of data loss, and makes it easier for Sector Police personnel to monitor the progress of reports. With automatic backup, report data is stored safely and can be accessed at any time. It is hoped that this research can be an innovative solution for Sector Police in digitalizing administrative processes, as well as providing a basis for further development in the future.

A study of advances in machine learning-based electronic design automation

Abstract. The electronic design automation (EDA) is a convenient tool for designing integrated circuits (IC), which is employed extensively both in academic and engineering. The design of integrated circuits is conducted in accordance with a defined design flow, commonly referred to as the chip design flow, which can be divided into two distinct parts, the front-end design and the back-end design. Following a long period of evolution, the chip design flow of EDA has been gradually improved. Besides, it achieved some accomplishments during this period. However, with the growing demand of ICs, especially Very Large-Scale Integration Circuit (VLSI), the existing EDA is not adequate for the requirement. In addition, the EDA technology has been so developed that it is relatively less flexible. In this context, concerns about the future of EDA have recently emerged. In response to this challenge, research has mentioned that machine learning methods (ML methods) can improve the functionality of EDA. The ML method covers most of steps of EDAs design flow, especially back-end design. The machine learning-based electronic design automation is still in its infancy, which is presented with a multitude of challenges. Therefore, the paper explores the development of EDA by reviewing and organizing the related literature, and summarizes the application of ML methods in EDA, thereby providing the future development trend of ML-based EDA.

EnR: extend and reduce methodology to enable formal verification of truncated adders

Abstract Truncated adders are widely used in applications where using lower bit-width is enough to generate the desired outputs. Truncated adders give benefits in area, power, and delay as compared to their non-truncated counterparts. While prior works deal with the formal verification of n-bit adders, there is no prior work dealing with the formal verification of unverified m-bit truncated adders using verified n-bit adder designs, where m < ${< } $ n. In this work, we propose a methodology that enables the verification for any truncated adder designs, irrespective of the architecture, called Extend and Reduce (EnR). EnR uses a three-step methodology to formally verify the truncated adders, which are considered as Design Under Verification (DUV). Firstly, it extends the bit-width of the DUV (truncated adder) to match with the nearest higher 2 n -bit adder, called an Extended Truncated Adder (ETA). Secondly, it reduces off-the-shelf formally verified golden reference adder design by forcing 0’s at the input bits to match it to the extended DUV design and re-synthesizing it to generate a Reduced Golden Adder (RGA). Lastly, a combinational equivalence check is then performed between the ETA and the RGA for formal verification. If the truncated adder is correct, the ETA and RGA are equivalent and vice versa. We evaluate a number and variety of adder designs to show the efficacy of the EnR methodology. We performed the formal verification using Binary Decision Diagrams (BDDs) and And-Inverter Graphs (AIGs). Lastly, we show the scalability of EnR methodology using adders up to a bit-width of 512 bits. ACM CCS Hardware → Arithmetic and datapath circuits; Combinational circuits; Equivalence checking; Functional verification; Electronic design automation.

Research on adaptive circuit structure optimization in electronic design based on Asynchronous Advantage Actor Critic (A3C) algorithm

The circuit structure optimizationed with the traditional method is often difficult to meet the complex and changeable design requirements. In this paper the A3C algorithm has been applied to integrate strategy learning and value learning for the circuit structure optimization. This integration can facilitate continuous interaction with the environment, enabling automatic adjustment of circuit structures to meet the complex design requirements. Gain, bandwidth, latency, and power consumption have been set as the optimization objectives, and the actions of the intelligent agent, which include adding, deleting, modifying connection lines, and adjusting component parameters have been introduced in detail. Once the Actor and Critic networks have been established, multiple agents can operate concurrently, translating optimization objectives into reward signals and providing direction and motivation for agent learning. Then with the proposed method, the circuit structure of one switch audio power amplifier has been designed in a simulation environment. The structure optimization results demonstrated that the gain can reach 78.4 dB at convergence of the A3C algorithm, while the bandwidth can reach 156.2 MHz at convergence, and both the circuit delay and power consumption have been reduced significantly. Obviously, the application of the A3C algorithm can effectively optimize the circuit structures through offering more flexible and efficient solutions.

Crack Development and Electrical Degradation in Chromium Thin Films Under Tensile Stress on PET Substrates

The mechanical and electrical deterioration of chromium (Cr) thin films sputtered onto polyethylene terephthalate (PET) substrates under tensile strain was studied. Understanding mechanical and electrical stability due to imposed strain is particularly important for device reliability, as the demand for flexible electronic devices increases. Cr thin films, widely spread across the field of electronic and sensor applications, face crack propagation with electrical degradation with tensile stress that can seriously compromise the performance. Accordingly, this study offers new findings on how Cr film thickness might influence crack formation and electrical resistance differently and also the general guidelines for flexible electronic component design with respect to long-term durability. Electrical resistances were measured while mechanically stretching 100- and 200 nm thin sheets. The study focused on crack development and propagation mechanisms in both film thicknesses and their effects on percentage change in electrical resistance (PCER). Scanning electronic microscopy (SEM) was used to characterize surface morphology and observe cracks as the strain rose. Early crack formation in 100 nm Cr films led to rapid PCER increases due to quick crack propagation and fast electrical degradation. Thicker 200 nm films, however, showed a more gradual PCER rise with fewer but deeper cracks, indicating a regulated strain response. Unlike the sharp PCER spike in 100 nm films, 200 nm samples were more variable, with three out of four showing a slight PCER decrease at the end, hinting at partial crack repair or conductive realignment before full failure. These results underscore the role of layer thickness in managing crack propagation and electrical stability, relevant for flexible electronics and strain sensors. This paper is aligned with the ninth goal of the United Nations Sustainable Development Goals, specifically Target 9.5: Enhance Research and Upgrade Industrial Technologies.

Double-eigenvalue bifurcation and multistability in serpentine strips with tunable buckling behaviors

Serpentine structures, composed of straight and circular strips, have garnered significant attention as potential designs for flexible electronics due to their remarkable stretchability. When subjected to stretching, these serpentine strips buckle out of plane, and previous studies have identified two distinct buckling modes whose order of appearance may interchange in serpentine structures with a single cell. In this study, we employ anisotropic rod theory to model serpentine strips as a multi-segment boundary value problem (BVP), with continuity conditions enforced at the interface between the straight and curved strips. We solve the BVP using methods of continuation, and our results reveal that: (1) the exchange of the two buckling modes in a single-cell serpentine strip is induced by a double-eigenvalue and associated secondary bifurcations, which also alter the stability of the two buckling modes; (2) a variety of stable states with reversible symmetry can be manually obtained in tabletop models and are found to be disconnected from the planar branch in numerical continuation. Furthermore, we demonstrate that modulating the strip thickness across different cells leads to the initiation of buckling in the thinnest section, thereby allowing for the tuning of buckling modes in serpentine strips. In structures with two cells, the sequence of the two buckling modes can also be controlled by designing serpentine strips with nonuniform height. This work could enhance the mechanical design of serpentine-interconnect-based flexible structures and could have applications in multistable actuators and mechanical memory devices.

Molecular dynamics study of the effect of composition on elastic properties of silicon oxynitride films

Understanding the mechanical properties of silicon oxynitride (a-SiON), a key insulating material, is vital for electronic device design and reliability. Though the effects of fabrication conditions on a-SiON have been studied, the underlying relationship between its atomic-scale structure and mechanical properties remains unclear. This study investigates the relationship between elasticity and atomic-scale structures in a-SiON by molecular dynamics simulations with a universal graph neural network interatomic potential. The bulk modulus increases from 49 to 150 GPa with higher N content. N atoms form N2 molecules under O-rich conditions, hindering bulk modulus increase, and form an Si3N4-like network under O-poor conditions, enhancing bulk modulus. Formation energy calculations indicate N2 formation is preferable under O-rich conditions. Meanwhile, under O-poor conditions, Si–N bond formation is preferable, which reinforces a-SiON by increasing bond density. The findings suggest realizing O-poor conditions is crucial for highly elastic insulating films.

A cosmic ray muons telescope based on bar plastic scintillator detectors

A cosmic ray muons telescope (CORMT) was designed to monitor the distribution of cosmic ray muons in the environment. CORMT is made of three main components: the mechanical structure, the detector, and the readout electronics. The mechanical structure consists of a support structure and a rotating moving platform that ensures the stability and accuracy of the test. The detector consists of four bar-shaped plastic scintillators each coupled with a silicon photomultiplier (SiPM). The readout electronics design uses Xilinx Artix 7 series field-programmable gate array (FPGA), combined with peripheral circuit design, to complete the readout of detector cosmic ray muons hit information. CORMT has the advantage of adjustable thresholds, real-time output, and the use of Coordinated Universal Time (UTC) to record events. The CORMT test results show that the detection efficiency can reach over 90%, the accidental compliance count rate is around 0.02, and the muon flux conforms to the distribution law. This article will discuss the design and performance of the CORMT.

An active two-stage class-J power amplifier design for smart grid’s 5G wireless networks

<span>The wireless communication networks in the smart grid’s advanced metering infrastructure (AMI) applications need 5G technology to support large data transmission efficiently. As the 5G wireless communication network’s overall bandwidth (BW) and efficiency depend on its power amplifier (PA), in this work, a two-stage class-J power amplifier’s design methodology that operates at 3.5 GHz centre frequency by utilizing the CGH40010F model gallium nitride (GaN) transistor is presented. The proposed design methodology involves proper designing of input, output, and interstage matching networks to achieve class-J operation with improved power gain over desired BW using the advanced design system (ADS) electronic design automation (EDA) tool and estimating its integration feasibility through active element-based design approach using the Mentor Graphics EDA tool. The proposed PA provides 54% drain efficiency (D.E), 53% power added efficiency (PAE) with a small signal gain of 27 dB at 3.5 GHz and 41 dBm power output with 21 dB of improved power gain across a BW of around 400 MHz using 28 V power supply into 50 Ω load. By replacing the two-stage PA's passive elements with active elements, its layout size is estimated to be (15.5×29.2) μm2 . The results of the proposed PA exhibit its integration feasibility and suitability for the smart grid’s 5G wireless networks.</span>

Multifunctional Smart Fabrics with Integration of Self-Cleaning, Energy Harvesting, and Thermal Management Properties.

Due to their good wearability, smart fabrics have gradually developed into one of the important components of multifunctional flexible electronics. Nevertheless, function integration is typically accomplished through the intricate stacking of diverse modules, which inevitably compromises comfort and elevates processing complexities. The integration of these discrete functional modules into a unified design for smart fabrics represents a superior solution. Here, we put forward a rational approach to functional integration for the typical challenges of thermal management, energy supply, and surface contamination in smart fabrics. This sandwich-structured multilayer fabric (MLF) is obtained by continuous electrospinning of two layer P(VDF-HFP) fabric and one layer P(VDF-HFP) fabric functionalized with core-shell SiO2/ZnO/ZIF-8 (SZZ) nanoparticles. Specifically, MLFs achieve effective and stable energy harvesting in triboelectric nanogenerators (TENGs) with hydrophobicity and antibacterial properties. Meanwhile, MLFs also have high mid-infrared emissivity and sunlight reflectivity, successfully realizing radiative cooling under different climates, and have been applied in wearing clothing, roof shading, and car covers. This work may contribute to the design and manufacturing of next-generation thermal comfort smart fabrics and wearable electronics, particularly in terms of the rational design of multifunctional devices.

Social Work Education Leadership

Social work education-specific leadership models are necessary to maximize the effectiveness of the profession’s role in addressing societal issues that impact individuals, families, and communities and promote feminist leadership within the profession and academy. A cross-sectional electronic survey design gathered information from faculty and staff members at accredited social work programs within the United States. Study participants included 88 full- and part-time faculty and staff. 50 of the 88 participants (57%) answered the open-ended question from which data for this study were analyzed and triangulated with responses to other questions. The data analysis process resulted in identification of three main themes: conceptualization of leadership, support for leadership, and barriers to leadership. Participants expressed the need for more thoughtful succession planning, leadership specific training, and support in removing barriers to leadership. Many of the problems raised could be addressed through systemic change in higher education, including the proposed model of social work education leadership praxis.

Understanding the consumer purchase behaviour towards green electronic products: using insight from the theory of planned behaviour

PurposeThis research investigation aims to explore the factors that affect purchasing behaviour among consumers in India in the context of green electronic products with the aid of the extended theory of planned behaviour (TPB) by incorporating two additional constructs, namely environmental concern and ethical obligation.Design/methodology/approachThe current research adopted a quantitative methodology, utilising a survey (questionnaire) to gather data from respondents residing in Delhi-NCR, India. A convenience sampling technique was used to select these respondents. Both online and offline modes were used to collect the data. Moreover, to evaluate the theoretical foundation of the investigation, the researchers employed PLS-SEM (partial least square structural equation modelling) on 346 useable samples.FindingsThe outcome reveals that attitude, subjective norm and perceived behaviour control (PBC) are significant predictors, supplementary constructs such as environmental concern are not significant predictors, whereas ethical obligation is a substantial predictor of purchase intention. Consumer purchase behaviour, in turn, is influenced by consumer purchase intention.Practical implicationsThe outcome of this research could help the country’s legislators formulate policies and programs related to current environmental problems faced by our planet. Marketers could understand the factors that drive consumers' purchasing behaviour towards green electronic products and design effective marketing strategies accordingly. Thus, by enhancing the company’s green image, marketers of green products may potentially increase future purchases, all of which contribute to solving worldwide environmental problems.Originality/valueThis research confirms the usefulness of TPB in understanding Indian consumers' purchasing intention and behaviour towards green electronic products. It further extends the TPB by showing that new components, environmental concerns and ethical obligations influence Indian consumers' purchasing intentions and behaviour. Moreover, prior studies mostly used both additional constructs for green products. Current research used specific types of green products, i.e. green electronic products, as very few studies are available on these products that apply TPB, which makes this study novel. In contrast to previous research that primarily examined purchase intention, this study takes a further step by investigating the connection between intentions and consumers' purchase behaviour. It establishes intention as a precursor to behaviour, specifically towards green electronic products. Additionally, this study introduces new constructs and explores the Indian context, significantly contributing to the existing literature.

Design and Implementation of Small Modular Amphibious Robot System

Various marine engineering facilities have been eroded by marine organisms and wind waves for a long time, resulting in different types of damage to the surface of marine engineering facilities, such as the pile legs of offshore platforms. Therefore, in order to carry out safety inspections and other work on marine engineering facilities, a small amphibious robot structure system and a set of control systems adapted to it are independently developed. Various problems such as the modular design of the structure, composite motion mode, adsorption stability, wall adaptability of the crawling mode, and flaw localization have been solved by means of three-dimensional modeling, mechanical analysis, simulation, and electronic design. At the same time, a set of control systems including hardware and software is developed for the amphibious robot. In order to improve the stability and efficiency of the amphibious robot working underwater, a sliding mode control algorithm based on the exponential reaching law and saturation function is designed. For the fixed depth and fixed heading control functions, the sliding mode control algorithm and the PID control algorithm are simulated and compared. Finally, several types of experiments are carried out for the amphibious robot. The simulation and experimental results show that all the functions of the amphibious robot meet work requirements, such as the motion performance of the composite motion mode. Compared with the PID control algorithm, the sliding mode control algorithm has a faster response speed and better stability, which is conducive to the efficient and stable work of the amphibious robot underwater.

Transferable Percolated Particle Monolayers Derived from Marangoni Flows for Thermally Conductive Dielectric Coatings.

Thermal management is becoming one of the most significant design and size limitations for high power density electronics, including motherboards, power converters, and phased array antennas for 5G communications. There are few options for conducting heat away with dielectric materials that avoid shortening or distorting the performance of these electronics. Certain highly thermally conductive 2D and 3D materials, including hexagonal boron nitride and diamond, offer ideal material properties to address these issues but are extremely challenging to process. This work studies highly oriented single-particle thick films of hexagonal boron nitride, manufactured through a modified Langmuir-Blodgett process and densified further using the Marangoni effect to attain remarkable thermal conductivity enhancement with minimal coating thickness. High loadings of hexagonal boron nitride (∼60 vol %) in dense, castable films are also produced to compare thermal spreading ability in a comparatively simpler but less-coordinated percolated system to the highly percolated particle monolayers. These procedures were applied to glass fiber reinforced polymers used in aerospace and radome applications as well as to a single-board computer to demonstrate enhanced thermal management.

Effect of Anions on Deformation of Gallium-Based Liquid Metal in Solution.

In this study, deformation behaviors of gallium-based liquid metals in acidified cupric sulfate or cupric chloride solutions with varying concentrations of chloride anion or sulfate anion were investigated to explore their potential applications in soft machines and electronics. Gallium-based liquid metals are known for their unique deformability, making them promising materials for various fields. Previous research has shown that deformation of the liquid metal can be achieved in the presence of acidified cupric or ferric salts. However, the specific influence of different anions on the deformation process remains unclear. Our findings indicate that the deformation rate of the liquid metal increases with higher concentrations of chloride ions and decreases with higher concentrations of sulfate ions in the solution. UV-vis absorbance spectra of the solutions were analyzed to identify the formation of hydrated cupric cations. It was observed that increasing the concentration of Cl- ions promotes the formation of cupric-chloro complexes, thereby reducing the concentration of hydrated cupric ions in the solution. Furthermore, the addition of sulfate ions to the solution enhances the ionic strength of the medium, leading to the dissociation of cupric-chloro complexes. Additionally, sulfate ions can form insoluble layers with gallium ions, which impede the deformation of the liquid metal. The deformation rate of the liquid metal was found to be inversely correlated with the concentration of cupric ions in the solution. These results provide valuable insights into the deformable behavior of gallium-based liquid metals and their potential applications in liquid metal-based soft robots. This study highlights the importance of understanding the role of different anions in the deformation process of liquid metals, shedding light on the design and optimization of soft machines and electronics utilizing these materials.

Degradable Multilayer Fabric Sensor with Wide Detection Range and High Linearity.

Integration of multiple superior features into a single flexible pressure sensor would result in devices with greater versatility and utility. To apply the device to a variety of scenarios and solve the problem of accumulation of e-waste in the environment, it is highly desirable to combine degradability and wide-range linearity characteristics in a single device. Herein, we reported a degradable multilayer fabric (DMF) consisting of an ellipsoidal carbon nanotube (ECNT) and polyvinylpyrrolidone/cellulose acetate electrospun fibers (PEF). The alternative layer-by-layer stacking of the ECNT and PEF notably accelerates the sensitivity toward pressure. The optimized device demonstrated a sensitivity of 3.38 kPa-1 over a wide measurement range from 0.1 to 500 kPa, as well as great mechanical stability over 2000 cycles. A good degradation performance was confirmed by both Fourier transform infrared (FTIR) characterization and decomposition experiments in sodium hydroxide solution. The fabricated sensor is capable of precepting a variety of physiological scenarios including subtle arterial pulse, dancing training, walking postures, and accidental falls. This work throws light onto the fundamental understanding of the mechanical interfacial coupling in piezoresistive materials and provides possibilities for the design and development of on-demand wearable electronics.