Device Simulation Research Articles

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

Finding optimal pathways in chemical reaction networks using Ising machines

Finding optimal pathways in chemical reaction networks is essential for elucidating and designing chemical processes, with significant applications such as synthesis planning and metabolic pathway analysis. Such a chemical pathway-finding problem can be formulated as a constrained combinatorial optimization problem, aiming to find an optimal combination of chemical reactions connecting starting materials to target materials in a given network. Due to combinatorial explosion, the computation time required to find an optimal pathway increases exponentially with the network size. Ising machines, including quantum and simulated annealing devices, are promising novel computers dedicated to such hard combinatorial optimization. However, to the best of our knowledge, there has yet to be an attempt to apply Ising machines to chemical pathway-finding problems. In this article, we present the Ising/quantum computing application for chemical pathway-finding problems. The Ising model, translated from a chemical pathway-finding problem, involves several types of penalty terms for violating constraints. It is not obvious how to set appropriate penalty strengths of different types. To address this challenge, we employ Bayesian optimization for parameter tuning. Furthermore, we introduce a technique that enhances tuning performance by grouping penalty terms according to the underlying problem structure. The performance evaluation and analysis of the proposed algorithm were conducted using a D-Wave Advantage system and simulated annealing. The benchmark results reveal challenges in finding exact optimal pathways. Concurrently, the results indicate the feasibility of finding approximate optimal pathways, provided that a certain degree of relative error in cost value is acceptable. Published by the American Physical Society 2024

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.

An Optimized Device Structure with Improved Erase Operation within the Indium Gallium Zinc Oxide Channel in Three-Dimensional NAND Flash Applications

In this paper, we propose an optimized device structure to address issues in 3D NAND flash memory devices, which encounter difficulties when using the hole erase method due to the unfavorable hole characteristics of indium gallium zinc oxide (IGZO). The proposed structure mitigated the erase operation problem caused by the low hole mobility of IGZO by introducing a filler inside the IGZO channel. It facilitated the injection of holes into the IGZO channel through the filler, while the existing P-type doped polysilicon filler material was replaced by a P-type oxide semiconductor. In contrast to polysilicon (band gap: 1.1 eV), this P-type oxide semiconductor has a band gap similar to that of the IGZO channel (2.5 to 3.0 eV). Consequently, it was confirmed through device simulation that there was no barrier due to the difference in band gaps, enabling the seamless supply of holes to the IGZO channel. Based on these results, we conducted a simulation to determine the optimal parameters for the P-type oxide semiconductor to be used as a filler, demonstrating improved erase operation when the P-type carrier density was 1019 cm−3 or higher and the band gap was 3.0 eV or higher.

Gate-controlled near-surface Josephson junctions

Gate-tunable Josephson junctions are interesting for quantum technology applications, such as gatemon qubits and topological Majorana-based qubits. Furthermore, high-frequency compatible geometries can be utilized for implementing electrically pumped parametric amplifiers. In this paper, we combine processing, measurements, and modeling of near-surface InGaAs Josephson field-effect transistors in order to facilitate circuit simulations of actual non-ideal devices. We developed a compact model using Verilog-A and confirmed the validity of our model by accurately reproducing our measured data by circuit simulations in Advanced Design System. From the circuit simulations, an effective gate-dependent transmission coefficient, with a peak value of ∼ 3.5%, was extracted, mainly limited by contact transparency.

All oxide lead-free bismuth ferrite perovskite absorber based FTO/ZnO/BiFeO3/Au solar cell with efficiency ∼ 12%: First principle material and macroscopic device simulation studies

We report the photovoltaic response of bismuth ferrite (BiFeO3) multiferroic absorber based all oxide FTO/ZnO/BiFeO3/Au solar cell using density functional theory for materials optoelectronic properties and macroscopic device simulation-based hybrid approach. The structural, electronic, and optical properties of BiFeO3 are investigated using density functional theory (DFT). The band structure and density of states of R3c-BiFeO3 are computed considering the Hubbard parameter Ueff∼4.2eV for both Fe-3d and O-2p orbitals for matching the experimental bandgap of ∼2.5eV. The computed optical properties, such as absorption for rhombohedral R3c-BiFeO3, are used to investigate FTO/ZnO/BiFeO3/Au solar cell performance using a macroscopic device simulation approach. The thickness, acceptor concentration, defect concentration of the absorber layer, interface defect density, electron affinity of the electron transport layer, and the impact of series, shunt resistance, and metal back contact are investigated to optimize the photovoltaic response under realistic conditions. The optimum photoconversion efficiency (PCE) is ∼11.92% with open circuit voltage (Voc) of 1.033V, short circuit current density (Jsc) of 15.27mA/cm2, and fill factor (FF) of 75.59%. This study on BiFeO3-based absorber materials opens a way to realize lead-free perovskite absorber material with a potential for realizing all oxide solar cells.

Fault Diagnosis of PV Array Based on Time Series and Support Vector Machine

This paper proposes a diagnosis method based on time series and support vector machine (SVM) to improve the timeliness, accuracy, and feasibility of fault diagnosis for photovoltaic (PV) arrays. It obtains the nominal output power of the PV array based on real-time collected data such as voltage, current, radiation, and temperature and normalizes the power values at different time points throughout the day to form a time series. Using the time series values as input data for a “one-to-one” multiclass classifier, we can identify and classify typical operational faults such as random shading, fixed shading, and aging degradation of PV arrays. The developed algorithmic model is trained and tested for different fault conditions using the data sets generated by the PV array simulation device. The experimental results show that our model has fairly good reliability and accuracy, and to some extent, it solves the problem of classifying shading and aging faults, two of which exhibit rather similar degradation characteristics.

Read Operation Mechanism of Feedback Field-Effect Transistors with Quasi-Nonvolatile Memory States.

In this study, the read operation of feedback field-effect transistors (FBFETs) with quasi-nonvolatile memory states was analyzed using a device simulator. For FBFETs, write pulses of 40 ns formed potential barriers in their channels, and charge carriers were accumulated (depleted) in these channels, generating the memory state "State 1 (State 0)". Read pulses of 40 ns read these states with a retention time of 3 s, and the potential barrier formation and carrier accumulation were influenced by these read pulses. The potential barriers were analyzed, using junction voltage and current density to explore the memory states. Moreover, FBFETs exhibited nondestructive readout characteristics during the read operation, which depended on the read voltage and pulse width.

Response mechanism of soil leachate and disinfection by-product formation to extreme precipitation events under continuous drought scenario

In this study, a rainfall simulation device was employed to investigate the response mechanism of soil leachate and disinfection by-products formation potential (DBPsFP) to extreme precipitation events. The results revealed that the aromaticity of dissolved organic matter (DOM) and the concentration of hydrophobic DOM containing aromatic carbon groups in leachate decreased with rising temperature. The humification degree of DOM decreased at 25 °C (99 mm/h), while the humification degree and protein-like level of DOM increased under high temperatures droughts (45 °C and 65 °C). Higher temperatures resulted in the leach of more microbial-derived humus and low molecular phenolic compounds from soil and broadened the range of molecular weight distribution. Increasing temperature increased DBPsFP and DBPs species and caused the precursors of haloacetic acids (HAAs) in leachate to become more hydrophobic, while the precursors of trihalomethanes (THMs) became more hydrophilic. Most importantly, the increased temperature attenuated the rainfall-mediated dilution of organic pollutant concentration, and temperature has a more significant effect than extreme rainfall in DOM abundance and the formation potential (or species) of DBPs. The results help to better understand the impact of climate change on the physicochemical processes of water quality.