Device Simulation Research Articles

Experimental study on mine water purification mechanism for broken coal and rock masses in the underground reservoir of ecologically vulnerable mining area.

Water-rock interaction mechanism and water purification capacity of broken coal and rock masses are very important for the efficient operation of the underground reservoir. In this paper, a water purification simulation device for an underground mine reservoir was designed. The experimental study on the dynamic interaction between broken coal and rock masses and mine water was carried out. The water purification mechanism is analyzed from the changes in rock mineral composition and mine water quality before and after the test. The results show that after the broken coal and rock mass purification, the water turbidity and the concentration of chlorides and suspended solids decreased obviously. The water purification capacities of mudstone and sandstone are stronger than that of coal samples. After 60days of reaction between the working face sewage and the broken samples (mudstone, sandstone, and coal), the turbidity, chromaticity, and residual chlorine decreased by > 90%, 90%, and 60%, respectively; and COD decreased by 35.29%, 30.59%, and 28.99%, respectively. While the TDS and the total hardness increased by about 40%, 30%, and 10% for the mudstone, sandstone, and coal, respectively. It shows that coal also has the worst degradation performance. The water purification effect of broken coal and rock masses has a significant time effect. The early stage of water-rock interaction is dominated by mineral dissolution, and the middle stage is dominated by precipitation and adsorption. The pH value of the solution has a certain influence on the ion change. In the later stage, the water-rock interaction is weak in a dynamic equilibrium state, and the change in the mine water quality index is not obvious. Considering the influence of rock lithology on water quality and the law of water-rock interaction time, the construction site selection and water storage time optimization of underground reservoirs in Jinjie Coal Mine were carried out, respectively.

Mole Fraction and Device Reliability Analysis of Vertical-Tunneling-Attributed Dual-Material Double-Gate Heterojunction-TFET with Si0.7Ge0.3 Source Region at Device and Circuit Level

This paper puts forward a new vertical-tunneling-attributed dual-material double-gate heterojunction-TFET (VTDMDG-HTFET). The device structure of VTDMDG-HTFET includes Si[Formula: see text]Ge[Formula: see text] material for the designing of source region. The mechanism of vertical tunneling in VTDMDG-HTFET provides superior electric field at tunneling interface and leads to improved transfer characteristics. VTDMDG-HTFET also includes metal gate work-function engineering approach to facilitate high ON-current and small OFF-current. Application of high-[Formula: see text] dielectric material HfO2 in the form of gate oxide enhances the capacitive-coupling at channel-source interface. Moreover, the work includes the comparison of proposed VTDMDG-HTFET with the conventional vertical-tunneling based dual-material double-gate-TFET (VTDMDG-TFET). It has been observed from the simulation results that SiGe source-based VTDMDG-HTFET offers better DC characteristics in terms of superior ON-current, smaller OFF-current, steeper subthreshold-slope, lower threshold voltage, higher transconductance along with smaller drain-induced barrier-lowering (DIBL) effects as compared to its counterpart silicon-source-based VTDMDG-TFET. In this work, reliability of VTDMDG-HTFET has also been examined and compared with VTDMDG-TFET in terms of temperature sensitivity and effect of different interface trap charges. The device simulation and investigations have been carried out using technology computer aided design (TCAD) tool. Moreover, device circuit mixed-mode simulation analysis is carried out for conventional and proposed device based resistive load inverters. A comparison is performed between both the inverters in terms of prorogation delay and switching threshold voltages. Further, the mixed mode simulation analysis is also performed for the proposed device based inverter under the influence of different interface trap charges (ITCs). Study shows that reliability performance of the proposed device is better as compared to its counterpart conventional device. Hence, vertical tunneling and SiGe source-based VTDMDG-HTFET can be a better choice for various applications such as analog/RF, analog and digital electronic circuits, energy harvesting, gas-sensing and memory devices.

Skin marker-based versus bone morphology-based coordinate systems of the hindfoot and forefoot

Segment coordinate systems (CSs) of marker-based multi-segment foot models are used to measure foot kinematics, however their relationship to the underlying bony anatomy is barely studied. The aim of this study was to compare marker-based CSs (MCSs) with bone morphology-based CSs (BCSs) for the hindfoot and forefoot. Markers were placed on the right foot of fifteen healthy adults according to the Oxford, Rizzoli and Amsterdam Foot Model (OFM, RFM and AFM, respectively). A CT scan was made while the foot was loaded in a simulated weight-bearing device. BCSs were based on axes of inertia. The orientation difference between BCSs and MCSs was quantified in helical and 3D Euler angles. To determine whether the marker models were able to capture inter-subject variability in bone poses, linear regressions were performed. Compared to the hindfoot BCS, all MCSs were more toward plantar flexion and internal rotation, and RFM was also oriented toward more inversion. Compared to the forefoot BCS, OFM and RFM were oriented more toward dorsal and plantar flexion, respectively, and internal rotation, while AFM was not statistically different in the sagittal and transverse plane. In the frontal plane, OFM was more toward eversion and RFM and AFM more toward inversion compared to BCS. Inter-subject bone pose variability was captured with RFM and AFM in most planes of the hindfoot and forefoot, while this variability was not captured by OFM. When interpreting multi-segment foot model data it is important to realize that MCSs and BCSs do not always align.

Deep photonic network platform enabling arbitrary and broadband optical functionality

Expanding applications in optical communications, computing, and sensing continue to drive the need for high-performance integrated photonic components. Designing these on-chip systems with arbitrary functionality requires beyond what is possible with physical intuition, for which machine learning-based methods have recently become popular. However, computational demands for physically accurate device simulations present critical challenges, significantly limiting scalability and design flexibility of these methods. Here, we present a highly-scalable, physics-informed design platform for on-chip optical systems with arbitrary functionality, based on deep photonic networks of custom-designed Mach-Zehnder interferometers. Leveraging this platform, we demonstrate ultra-broadband power splitters and a spectral duplexer, each designed within two minutes. The devices exhibit state-of-the-art experimental performance with insertion losses below 0.66 dB, and 1-dB bandwidths exceeding 120 nm. This platform provides a tractable path towards systematic, large-scale photonic system design, enabling custom power, phase, and dispersion profiles for high-throughput communications, quantum information processing, and medical/biological sensing applications.

Thermal Compact Modeling and Resistive Switching Analysis in Titanium Oxide-Based Memristors.

Resistive switching devices based on the Au/Ti/TiO2/Au stack were developed. In addition to standard electrical characterization by means of I-V curves, scanning thermal microscopy was employed to localize the hot spots on the top device surface (linked to conductive nanofilaments, CNFs) and perform in-operando tracking of temperature in such spots. In this way, electrical and thermal responses can be simultaneously recorded and related to each other. In a complementary way, a model for device simulation (based on COMSOL Multiphysics) was implemented in order to link the measured temperature to simulated device temperature maps. The data obtained were employed to calculate the thermal resistance to be used in compact models, such as the Stanford model, for circuit simulation. The thermal resistance extraction technique presented in this work is based on electrical and thermal measurements instead of being indirectly supported by a single fitting of the electrical response (using just I-V curves), as usual. Besides, the set and reset voltages were calculated from the complete I-V curve resistive switching series through different automatic numerical methods to assess the device variability. The series resistance was also obtained from experimental measurements, whose value is also incorporated into a compact model enhanced version.

Identifying Performance Limiting Parameters in Perovskite Solar Cells Using Machine Learning

Herein, it is shown that machine learning (ML) methods can be used to predict the parameter that limits the solar‐cell performance most significantly, solely based on the current density–voltage (J–V) curve under illumination. The data (11’150 J–V curves) to train the model is based on device simulation, where 20 different physical parameters related to charge transport and recombination are varied individually. This approach allows to cover a wide range of effects that could occur when varying fabrication conditions or during degradation of a device. Using ML, the simulated J–V curves are classified for the changed parameter with accuracies above 80%, where Random Forests perform best. It turns out that the key parameters, short‐circuit current density, open‐circuit voltage, maximum power conversion efficiency, and fill factor are sufficient for accurate predictions. To show the practical relevance, the ML algorithms are then applied to reported devices, and the results are discussed from a physics perspective. It is demonstrated that if some specified conditions are met, satisfying results can be reached. The proposed workflow can be used to better understand a device's behavior, e.g., during degradation, or as a guideline to improve its performance without costly and time‐consuming lab‐based trial‐and‐error methods.

Device simulations of perovskite transistors containing mobile ions and their relevance to experimental data

We present a device simulation of lead-halide perovskite-based thin film transistors (TFTs) containing mobile charged species to provide physical reasoning for the various experimental reports. We study the output characteristics for a range of scan duration (1/speed), average mobile ion densities, and N- and P-channel TFTs. We then directly compare our results to published data by Zeidell et al. [Adv. Electron. Mater. 4(12), 1800316 (2018)] and show that if the transistor’s measurement procedure is such that the ions’ effects are apparent, and then, our model can resolve the sign of the mobile ions in their MAPbI3−xClx TFTs (cations) and provide a good estimate of their density (∼1017 cm−3 at 200 k). Interestingly, we find that effects previously associated with channel screening are due to the ion-blocking of the charge extraction and that the incomplete saturation often reported is due to ion-induced channel shortening. Utilizing the same perovskite materials as in solar cells would allow researchers to improve their understanding of the mechanisms governing solar photovoltaics and improve their performance.

Development and Fabrication of MOSFET-Based Radiation Dosimeter (RadFET) for Enhanced Performance in Space Missions

This work presents the development and fabrication process of a radiation dosimeter based on Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) technology, known as RadFET. The aim of this study is to determine the specifications of the RadFET sensor for use in space missions by the Egyptian Space Agency in SPNeX mission. We have successfully determined the sensor specifications, specified the required electronic components for readout circuits, and confirmed the correct operation of the RadFET device through device simulations and radiation-induced damage models. The fabrication process was conducted at Zewail City of Science, Technology and Innovation cleanroom facility, utilizing Sentaurus TCAD for device and process simulations. We have conducted fabrication experiments for phosphorus spin-on dopant application, dry oxide growth, and wet oxidation using water vapor bubblers. The dosimeter readout PCB fabrication and assembly phases have been successfully completed. The developed RadFET dosimeter holds great promise for radiation monitoring in space missions, ensuring enhanced safety and reliability of electronic systems.

Unveiling the Impact of the Electrolyte's Counter Ions on Organic Electrochemical Transistor Performance

AbstractThe effect of the electrolyte's counter‐ion in organic electrochemical transistors is often neglected. the influence of anions (i.e., counter ions) is investigated on organic electrochemical transistors (OECTs) with a PEDOT:PSS‐like semiconductor through device simulations. The study examined the effects of mobile anions on OECT performance under two scenarios: when anions are blocked by the semiconductor and when they can penetrate it. In each case, the OECT's ON and OFF states are analyzed. The findings show that when anions can penetrate the semiconductor, the ON/OFF ratio of the OECT remains unchanged while the transconductance significantly increases. In the ON state, the case of blocked anions is observed that the current is predominantly surface‐current, whereas it becomes volumetric only when anions can penetrate the semiconductor. Furthermore, the extreme case is explored in which anions remain stationary within the electrolyte. In this scenario, achieving a reasonable ON/OFF ratio necessitates an ion density within the electrolyte that is two orders of magnitude higher than the dopant density of the semiconductor. This work underscores the substantial influence of counter anions on OECT performance, highlighting their critical role in shaping device behavior.

Influence of Imbibition Fracturing Fluid on the Original Water and Methane Occurrence in Actual Coalbed Methane Reservoirs Using the Integrated Device of Displacement and Low-Field Nuclear Magnetic Resonance.

The original water in the coal rock pores plays a controlling role in the occurrence of gas. Furthermore, during the hydraulic fracturing process, pressurized fracturing fluid with a higher pressure than the original pore pressure in the fractures drives the fracturing fluid to infiltrate into the coal rock pores, thereby altering the occurrence pattern of gas and water in the original pores. However, due to the limitations of the indoor simulation device, a systematic conclusion on the impact of the original pore water and imbibition fracturing fluid on coalbed methane reservoirs has not yet been formed. In this paper, an integrated device combining displacement and low-field nuclear magnetic resonance was employed using underground cylindrical coal rock samples as experimental subjects. Experimental conditions were maintained at a temperature of 30 °C, a confining pressure of 23 MPa, and an approximate reservoir pressure of 15 MPa. The initial water saturation levels were altered to 0, 27.88, and 42.18% to replicate the conditions of a coalbed methane reservoir at a depth of approximately 1200 m. Fracturing fluid with a pressure of 18 MPa was injected into the experimental samples to simulate the impact of the fracturing fluid on the original reservoir during hydraulic fracturing. This allowed for a realistic assessment of the influence of initial water saturation and fracturing fluid absorption on the coalbed methane recovery rate in the reservoir. The experimental results indicate that the imbibition process promotes the desorption of adsorbed gas, and the desorption amount of adsorbed gas increases with the increase in the original water saturation. This will result in an increase in the gas pressure within the pore system. The conditions of this experiment, in comparison to the previous ones, more closely resemble real reservoir conditions. This enables a realistic assessment of how the presence of the original water content and the absorption of the fracturing fluid affect gas occurrence within the reservoir.

A design TCADAS tool for semiconductor devices and case study of 65 nm conventional floating-gate MOS transistor

An automatic programming tool has become an essential component in virtual fabrication in recent years. This paper aims to propose a methodology of virtual fabrication for semiconductor devices and design a tool called Technology Computer-Aided Design Automatic Simulation (TCADAS) which can perform a completely virtual fabrication, device simulation, process variation, and output extraction. Especially, the TCADAS tool eliminates drudgery when studying semiconductor devices such as complexity in setting inputs, substantial manual work, and long run time of simulations. This work investigates the completed flow for a 65 nm conventional Floating-gate MOS transistor as a case study, which is widely considered a vital determinant of the non-volatile memory field. A detailed automatic process from the entry to a completed three-dimension structure, device characterization, extract important output parameters such as memory window, ION/IOFF, Gate Coupling Ratio (GCR), and speed operations are presented. The TCADAS tool was designed by Python language and the utilities of TCAD Silvaco tools including Athena, Atlas, and DevEdit3D.

Implementasi Akuntansi Dalam Rangka Meningkatkan Kualitas Laporan Keuangan UMKM

Micro, small, and medium enterprises (MSMEs) have an important position and function that, together with state-owned or private enterprises, carry out various businesses to achieve prosperity for the community. The function of MSMEs is to unite, direct, and develop the creative power and business power of the people, especially those with limited economic capacity so that they can participate in economic activities. Accounting information is used to assess management activities in managing assets entrusted to them (the stewardship function) and is also used as a decision-making tool by those who use it. MSMEs experience problems understanding the application of accounting in their business operations. The efforts they make are to improve the ability of their accounting personnel through training that is carried out incidentally both by related agencies and through activities carried out by universities. However, their efforts have not produced optimal results, coupled with a fairly high level of employee mutation, where employees who have been trained sometimes change workplaces. This problem is latent and occurs repeatedly, so it greatly disrupts the daily operations of MSMEs. To be able to achieve the objectives of the activity, the method used was in the form of assistance to 20 MSMEs. This assistance is carried out by providing a multimedia-based accounting simulation device to MSMEs and then explaining how to use it. This mentoring activity begins with a briefing on the use of the device. After that, monitoring the simulation device's utilization was carried out. The final activity carried out was an evaluation of the usefulness of the device in improving the ability of MSMEs to prepare financial reports.

Direct numerical simulations of a novel device to fight airborne virus transmission

The SARS-CoV-2 (COVID-19) pandemic has highlighted the crucial role of preventive measures in avoiding the spread of disease and understanding the transmission of airborne viruses in indoor spaces. This study focuses on a novel personal protective equipment consisting of a fan-peaked cap that creates a jet flow of air in front of the individual's face to reduce the concentration of airborne viruses and decrease the risk of infection transmission. Direct numerical simulation is used to analyze the effectiveness of the device under certain conditions, such as the velocity of the airflow, flow orientation, ambient conditions, and geometrical factors.

Numerical simulation and experiment of a blade management device in microgravity

Currently, most satellite propulsion systems are mainly chemical propulsion, and liquid propellant is the necessary power fuel for the propulsion system. The working environment of microgravity occurs when the satellite is in orbit. According to the working characteristics of the satellite, a propellant management device of vane type is designed. The PMD is composed of a vertical guide plate and a liquid accumulator, which is applied to the propellant tank to store and manage the propellant. In this paper, the microgravity gas-liquid management and control mechanism of a propellant management device of vane type is studied by numerical simulation and tower drop test. The results of numerical simulation and tower drop test are consistent, which verifies the good fluid management characteristics of this type of propellant management device, and provides references for its engineering application and the design of this type of structure.

Accuracy of the explicit energy-conserving particle-in-cell method for under-resolved simulations of capacitively coupled plasma discharges

The traditional explicit electrostatic momentum-conserving particle-in-cell algorithm requires strict resolution of the electron Debye length to deliver numerical stability and accuracy. The explicit electrostatic energy-conserving particle-in-cell algorithm alleviates this constraint with minimal modification to the traditional algorithm, retaining its simplicity, ease of parallelization, and acceleration on modern supercomputing architectures. In this article, we apply the algorithm to model a one-dimensional radio frequency capacitively coupled plasma discharge relevant to industrial applications. The energy-conserving approach closely matches the results from the momentum-conserving algorithm and retains accuracy even for cell sizes up to 8 times the electron Debye length. For even larger cells, the algorithm loses accuracy due to poor resolution of steep gradients within the radio frequency sheath. Accuracy can be recovered by adopting a non-uniform grid, which resolves the sheath and allows for cell sizes up to 32 times the electron Debye length in the quasi-neutral bulk of the discharge. The effect is an up to 8 times reduction in the number of required simulation cells, an improvement that can compound in higher-dimensional simulations. We therefore consider the explicit energy-conserving algorithm as a promising approach to significantly reduce the computational cost of full-scale device simulations and a pathway to delivering kinetic simulation capabilities of use to industry.

Application of bioinspired geomagnetic sensor measurements and geomagnetic map modeling based on neural networks in simulated navigation

A geomagnetic field is a vector field in which the strength and direction are related to geographical location. Geomagnetic navigation technology, which uses collected geomagnetic field information to achieve positioning and navigation, has the advantages of reliability, stability, accuracy, and concealment. With the deepening research on geomagnetic navigation, bioinspired geomagnetic navigation technology has also been developed, which mainly studies and imitates the magnetic sensing mechanism and navigation behavior of animals, providing new research ideas for geomagnetic navigation technology. The magnetic particle hypothesis and free radical pair hypothesis are two mainstream mechanisms of biological sensing using the geomagnetic field, and studies have shown that these two mechanisms may be coupled within organisms. In this study, we propose a bioinspired weak magnetic vector (BWMV) sensor based on the joint sensing mechanism of magnetic particles and free radicals. It consists of a magnetic rod made of soft magnetic material and a tunnel magnetoresistance (TMR) sensor array. A magnetic rod was used to simulate magnetic particles to convert magnetic field angle information into magnetic field intensity distribution information, and the TMR sensor array was used to simulate the perception of the magnetic field distribution by free radicals. In addition, artificial neural networks (ANNs) were used for BWMV sensors to obtain the mapping relationship between the magnetic field distribution and parameters, which can be used for geomagnetic navigation. To verify the navigation effect of the BWMV sensor in the laboratory, a simulated geomagnetic navigation device was built, and the high-precision mapping relationship from geomagnetic parameters to latitude and longitude information of the selected navigation area was obtained through another ANN. Finally, the effectiveness of the BWMV sensor based on ANNs for geomagnetic navigation is verified using simulated navigation experiments.

Spatial dynamic image planning based on wearable optoelectronic devices for tactical simulation of table tennis tournaments

Spatial dynamic image planning based on wearable optoelectronic devices for tactical simulation of table tennis tournaments

Light Effect on Amorphous Tin Oxide Thin‐Film Transistors

Amorphous tin oxide (a‐SnOx) is a potential transparent oxide semiconductor candidate for future large‐area electronic applications. The thin‐film transistor (TFT) mobilities reach ≈100 cm2 Vs−1, a mobility higher than other multiple cation‐based oxide semiconductor TFTs. Few optical properties have been reported so far and therefore both the effect of visible light and negative bias illumination stress (NBIS) on a‐SnOx TFT performances, known to dramatically impact oxide semiconductor‐based TFTs, have been investigated. The variation of density of states (DOS) due to NBIS by device simulation is analyzed, and a fourfold increase of the donor‐like states and a decrease in the band edge DOS from 2.3 to 2.0 × 1019 cm−3 eV−1 are showed. The evaluation of the effect of neutral, singly, and doubly ionized oxygen vacancies by density functional theory using 95 atoms reveals not only states in the gap of SnO2, but also variations in the electron density, and modifications in the crystal parameters compared to a structure without an oxygen vacancy. Material and device simulation analysis reveal that the oxygen vacancies have a dramatical impact on the DOS in the gap of SnO2 and can explain the NBIS phenomenon observed in a‐SnOx TFT.

An integrated mechanical degradation model to explore the mechanical response of a bioresorbable polymeric scaffold

Simulation of bioresorbable medical devices is hindered by the limitations of current material models. Useful simulations require that both the short- and long-term response must be considered; existing models are not physically-based and provide limited insight to guide performance improvements. This study presents an integrated degradation framework which couples a physically-based degradation model, which predicts changes in both crystallinity (Xc) and molecular weight (Mn), with the results of a micromechanical model, which predicts the effective properties of the semicrystalline polymer. This degradation framework is used to simulate the deployment of a bioresorbable PLLA (Poly (L-lactide) stent into a mock vessel and the subsequent mechanical response during degradation under different diffusion boundary conditions representing neointimal growth. A workflow is established in a commercial finite element code that couples both the immediate and long-term responses. Clinically relevant lumen loss is reported and used to compare different responses and the effect of neo-intimal tissue regrowth post-implantation on degradation and on the mechanical response is assessed. In addition, the effects of possible changes in Xc, which could occur during processing and stent deployment, are explored.

A collaborative framework for unifying typical multidimensional solar cell simulations – Part I. Ten common simulation steps and representing variables

AbstractMultidimensional simulations for diverse solar cells often encounter distinctive configurations, even when employing the same simulation software. The complexity and inefficiency of this process are further exacerbated when employing different simulators. From our extensive decade‐long experience in numerical simulations of diverse solar cells, we have identified ten common simulation steps intrinsic to typical electrical and optical simulations. Subsequently, we propose ten sets of variables that encompass all the relevant details required for these steps. To address the challenge of varying information requirements for each variable across different simulations, we assign a list, a versatile data type, to each variable. This approach, by design, enables concise, coherent, and flexible input, accommodating the unique demands of each simulation. However, to ensure unambiguous simulations, precise specifications for these variables are essential. Computer code has been successfully implemented to ensure adherence to specifications and expedite variable synchronization with Sentaurus, the de facto standard for device simulation. Within this framework, users are only tasked with editing variables in a plain text file, obviating the need for in‐depth knowledge of Sentaurus. This streamlines the prerequisites for engaging in numerical simulation significantly. Through thoughtful design considerations, we preserve the simulation capacity while simultaneously enhancing productivity considerably. This open‐source framework welcomes global collaboration within the photovoltaic community and has the potential to generate an extensive dataset for cost‐effective artificial intelligence training.