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Volume 39, Issue 7, Jul 2018
SPECIAL TOPIC ON SEMICONDUCTOR MATERIALS GENOME INITIATIVE: NEW CONCEPTS AND DISCOVERIES
Preface
Su-Huai Wei, Jun-Wei Luo, Bing Huang
Abstract PDF

Advanced semiconducting materials have many applications in information technology and clean energy, thus they are critical to sustained economic and environmental development. However, in the past, many important technology-enabling materials were discovered by trial and error, which tends to take long time and high cost to discover and move them from research laboratory to market. Therefore, accelerating the pace of discovery and deployment of advanced semiconducting materials are crucial to achieving rapid development in the 21st century.In recent years, great progresses have been made in theory and computational algorithms to discover and design new functional materials using materials genome techniques and high-throughput calculations. These recent advances in the ability of new material discoveries have transformed our understanding of the field and provided both opportunity and challenge in developing new semiconductor technology.

 

In this special topical issue, we invite leading scientists in this field to present their achievements and viewpoints as well as the state-of-the-art modelling methods on the material genome techniques, high-throughput calculations, machine learning, modeling and simulation of semiconducting materials.This special issue features four reviews ranging from data-driven material discovery for photocatalysis; approaches to design inorganic semiconductors while maintaining structural motifs; recent progress in Pb-free stable inorganic double halide perovskites; crystal structure prediction in the context of inverse materials design; and an article on first-principle high-throughput calculations of carrier effective masses of two-dimensional transition metal dichalcogenides.

 

We sincerely hope that this special issue could provide a valuable reference and perspective for the research community working in this exciting field and inspire many more to enter this field. We would like to thank all the authors who have contributed high-quality peer-reviewed articles to this special issue. We are also grateful to the editorial and production staff of Journal of Semiconductors for their superb assistance.

Advanced semiconducting materials have many applications in information technology and clean energy, thus they are critical to sustained economic and environmental development. However, in the past, many important technology-enabling materials were discovered by trial and error, which tends to take long time and high cost to discover and move them from research laboratory to market. Therefore, accelerating the pace of discovery and deployment of advanced semiconducting materials are crucial to achieving rapid development in the 21st century.In recent years, great progresses have been made in theory and computational algorithms to discover and design new functional materials using materials genome techniques and high-throughput calculations. These recent advances in the ability of new material discoveries have transformed our understanding of the field and provided both opportunity and challenge in developing new semiconductor technology.

 

In this special topical issue, we invite leading scientists in this field to present their achievements and viewpoints as well as the state-of-the-art modelling methods on the material genome techniques, high-throughput calculations, machine learning, modeling and simulation of semiconducting materials.This special issue features four reviews ranging from data-driven material discovery for photocatalysis; approaches to design inorganic semiconductors while maintaining structural motifs; recent progress in Pb-free stable inorganic double halide perovskites; crystal structure prediction in the context of inverse materials design; and an article on first-principle high-throughput calculations of carrier effective masses of two-dimensional transition metal dichalcogenides.

 

We sincerely hope that this special issue could provide a valuable reference and perspective for the research community working in this exciting field and inspire many more to enter this field. We would like to thank all the authors who have contributed high-quality peer-reviewed articles to this special issue. We are also grateful to the editorial and production staff of Journal of Semiconductors for their superb assistance.

Data-driven material discovery for photocatalysis: a short review
Jinbo Pan, Qimin Yan
J. Semicond.  2018, 39(7): 071001  doi: 10.1088/1674-4926/39/7/071001

In this short review, we introduce recent progress in the research field of data-driven material discovery and design for solar fuel generation. Construction of material databases under the materials genome initiative provides a great platform for material discovery and design by creating computational screening pipelines based on the materials’ descriptors. In the field of solar water splitting, data-driven computational discovery approach has been effective in making material predictions. When combined with synergistic and complimentary experimental efforts, high-throughput computations based on density functional theory showed great predictive power for accelerated discovery of inorganic compounds as functional materials for solar fuel generation. As an example, we introduce the theory–experiment joint discovery of a large set of metal oxide photoanode materials that have been theoretically predicted to be efficient candidates and soon verified by synergistic experimental fabrication and characterization processes. In the field of two-dimensional materials, the application of data-driven approach has realized the prediction of many promising candidates with suitable direct band gaps and optimal band edges for the generation of chemical fuels from sunlight, greatly expanding the number of theoretically predicted 2D photoelectrocatalysts that are awaiting experimental verification. We discuss the challenges for the continued discovery and design of novel bulk and 2D compounds for photocatalysis via a data-driven approach. At the end of this review, we provide a brief outlook for future material discoveries in the field of solar fuel generation.

In this short review, we introduce recent progress in the research field of data-driven material discovery and design for solar fuel generation. Construction of material databases under the materials genome initiative provides a great platform for material discovery and design by creating computational screening pipelines based on the materials’ descriptors. In the field of solar water splitting, data-driven computational discovery approach has been effective in making material predictions. When combined with synergistic and complimentary experimental efforts, high-throughput computations based on density functional theory showed great predictive power for accelerated discovery of inorganic compounds as functional materials for solar fuel generation. As an example, we introduce the theory–experiment joint discovery of a large set of metal oxide photoanode materials that have been theoretically predicted to be efficient candidates and soon verified by synergistic experimental fabrication and characterization processes. In the field of two-dimensional materials, the application of data-driven approach has realized the prediction of many promising candidates with suitable direct band gaps and optimal band edges for the generation of chemical fuels from sunlight, greatly expanding the number of theoretically predicted 2D photoelectrocatalysts that are awaiting experimental verification. We discuss the challenges for the continued discovery and design of novel bulk and 2D compounds for photocatalysis via a data-driven approach. At the end of this review, we provide a brief outlook for future material discoveries in the field of solar fuel generation.
Approaches to design inorganic semiconductors while maintaining structural motifs
Xiuwen Zhang, Jianbai Xia
J. Semicond.  2018, 39(7): 071002  doi: 10.1088/1674-4926/39/7/071002

Inorganic semiconductors are the essential constituents of information society, having enabled most of the devices for microelectronics, optoelectronics, new energy technology, healthcare devices, artificial intelligence, etc. From the view of condensed matter physics and materials science, inorganic semiconductors are not intricate. However, this special class of materials are keeping inspiring new inventions and consequently new technologies, which in turn promote the design of new semiconductors. The kinds of semiconductors in nature are finite. On one hand, the new techniques need semiconductors with better properties than existing ones, on the other hand, the new computers’ software and hardware develop so rapid that it is possible to design new semiconductors according to people’s desire before manufacturing them. In this paper, we review the rational design of inorganic semiconductors by transformation of their elemental constituents, while maintaining their structure motifs.

Inorganic semiconductors are the essential constituents of information society, having enabled most of the devices for microelectronics, optoelectronics, new energy technology, healthcare devices, artificial intelligence, etc. From the view of condensed matter physics and materials science, inorganic semiconductors are not intricate. However, this special class of materials are keeping inspiring new inventions and consequently new technologies, which in turn promote the design of new semiconductors. The kinds of semiconductors in nature are finite. On one hand, the new techniques need semiconductors with better properties than existing ones, on the other hand, the new computers’ software and hardware develop so rapid that it is possible to design new semiconductors according to people’s desire before manufacturing them. In this paper, we review the rational design of inorganic semiconductors by transformation of their elemental constituents, while maintaining their structure motifs.
Recent progress in Pb-free stable inorganic double halide perovskites
Zhenzhu Li, Wanjian Yin
J. Semicond.  2018, 39(7): 071003  doi: 10.1088/1674-4926/39/7/071003

Although the power conversion efficiency (PCE) of CH3NH3PbI3-based solar cells has achieved 22.1%, which is comparable to commercialized thin-film CdTe and Cu(In,Ga)Se2 solar cells, the long-term stability is the main obstacle for the commercialization of perovskite solar cells. Recent efforts have been made to explore alternative inorganic perovskites, which were assumed to have better stability than organic-inorganic hybrid CH3NH3PbI3. In this short review, we will keep up with experiments and summarize recent progresses of inorganic double halide perovskite, in particular to Cs2AgBiBr6, Cs2AgInCl6, Cs2InBiBr6 and their family members. We will also share our opinions on the promise of such class of materials.

Although the power conversion efficiency (PCE) of CH3NH3PbI3-based solar cells has achieved 22.1%, which is comparable to commercialized thin-film CdTe and Cu(In,Ga)Se2 solar cells, the long-term stability is the main obstacle for the commercialization of perovskite solar cells. Recent efforts have been made to explore alternative inorganic perovskites, which were assumed to have better stability than organic-inorganic hybrid CH3NH3PbI3. In this short review, we will keep up with experiments and summarize recent progresses of inorganic double halide perovskite, in particular to Cs2AgBiBr6, Cs2AgInCl6, Cs2InBiBr6 and their family members. We will also share our opinions on the promise of such class of materials.
Crystal structure prediction in the context of inverse materials design
G. Trimarchi
J. Semicond.  2018, 39(7): 071004  doi: 10.1088/1674-4926/39/7/071004

Inverse materials design tackles the challenge of finding materials with desired properties, tailored to specific applications, by combining atomistic simulations and optimization methods. The search for optimal materials requires one to survey large spaces of candidate solids. These spaces of materials can encompass both known and hypothetical compounds. When hypothetical compounds are explored, it becomes crucial to determine which ones are stable (and can be synthesized) and which are not. Crystal structure prediction is a necessary step for assessing theoretically the stability of a hypothetical material and, therefore, is a crucial step in inverse materials design protocols. Here, we describe how biologically-inspired global optimization methods can efficiently predict the stable crystal structure of solids. Specifically, we discuss the application of genetic algorithms to search for optimal atom configurations in systems in which the underlying lattice is given, and of evolutionary algorithms to address the general lattice-type prediction problem.

Inverse materials design tackles the challenge of finding materials with desired properties, tailored to specific applications, by combining atomistic simulations and optimization methods. The search for optimal materials requires one to survey large spaces of candidate solids. These spaces of materials can encompass both known and hypothetical compounds. When hypothetical compounds are explored, it becomes crucial to determine which ones are stable (and can be synthesized) and which are not. Crystal structure prediction is a necessary step for assessing theoretically the stability of a hypothetical material and, therefore, is a crucial step in inverse materials design protocols. Here, we describe how biologically-inspired global optimization methods can efficiently predict the stable crystal structure of solids. Specifically, we discuss the application of genetic algorithms to search for optimal atom configurations in systems in which the underlying lattice is given, and of evolutionary algorithms to address the general lattice-type prediction problem.
First-principle high-throughput calculations of carrier effective masses of two-dimensional transition metal dichalcogenides
Yuanhui Sun, Xinjiang Wang, Xin-Gang Zhao, Zhiming Shi, Lijun Zhang
J. Semicond.  2018, 39(7): 072001  doi: 10.1088/1674-4926/39/7/072001

Two-dimensional group-VIB transition metal dichalcogenides (with the formula of MX2) emerge as a family of intensely investigated semiconductors that are promising for both electronic (because of their reasonable carrier mobility) and optoelectronic (because of their direct band gap at monolayer thickness) applications. Effective mass is a crucial physical quantity determining carriers transport, and thus the performance of these applications. Here we present based on first-principles high-throughput calculations a computational study of carrier effective masses of the two-dimensional MX2 materials. Both electron and hole effective masses of different MX2 (M = Mo, W and X = S, Se, Te), including in-layer/out-of-layer components, thickness dependence, and magnitude variation in heterostructures, are systemically calculated. The numerical results, chemical trends, and the insights gained provide useful guidance for understanding the key factors controlling carrier effective masses in the MX2 system and further engineering the mass values to improve device performance.

Two-dimensional group-VIB transition metal dichalcogenides (with the formula of MX2) emerge as a family of intensely investigated semiconductors that are promising for both electronic (because of their reasonable carrier mobility) and optoelectronic (because of their direct band gap at monolayer thickness) applications. Effective mass is a crucial physical quantity determining carriers transport, and thus the performance of these applications. Here we present based on first-principles high-throughput calculations a computational study of carrier effective masses of the two-dimensional MX2 materials. Both electron and hole effective masses of different MX2 (M = Mo, W and X = S, Se, Te), including in-layer/out-of-layer components, thickness dependence, and magnitude variation in heterostructures, are systemically calculated. The numerical results, chemical trends, and the insights gained provide useful guidance for understanding the key factors controlling carrier effective masses in the MX2 system and further engineering the mass values to improve device performance.
INVITED REVIEW PAPERS
A review: crystalline silicon membranes over sealed cavities for pressure sensors by using silicon migration technology
Jiale Su, Xinwei Zhang, Guoping Zhou, Changfeng Xia, Wuqing Zhou, Qing'an Huang
J. Semicond.  2018, 39(7): 071005  doi: 10.1088/1674-4926/39/7/071005

A silicon pressure sensor is one of the very first MEMS components appearing in the microsystem area. The market for the MEMS pressure sensor is rapidly growing due to consumer electronic applications in recent years. Requirements of the pressure sensors with low cost, low power consumption and high accuracy drive one to develop a novel technology. This paper first overviews the historical development of the absolute pressure sensor briefly. It then reviews the state of the art technology for fabricating crystalline silicon membranes over sealed cavities by using the silicon migration technology in detail. By using only one lithographic step, the membranes defined in lateral and vertical dimensions can be realized by the technology. Finally, applications of MEMS through using the silicon migration technology are summarized.

A silicon pressure sensor is one of the very first MEMS components appearing in the microsystem area. The market for the MEMS pressure sensor is rapidly growing due to consumer electronic applications in recent years. Requirements of the pressure sensors with low cost, low power consumption and high accuracy drive one to develop a novel technology. This paper first overviews the historical development of the absolute pressure sensor briefly. It then reviews the state of the art technology for fabricating crystalline silicon membranes over sealed cavities by using the silicon migration technology in detail. By using only one lithographic step, the membranes defined in lateral and vertical dimensions can be realized by the technology. Finally, applications of MEMS through using the silicon migration technology are summarized.
SEMICONDUCTOR PHYSICS
Hot electron transport in wurtzite-GaN: effects of temperature and doping concentration
Aritra Acharyya
J. Semicond.  2018, 39(7): 072002  doi: 10.1088/1674-4926/39/7/072002

The hot electron transport in wurtzite phase gallium nitride (Wz-GaN) has been studied in this paper. An analytical expression of electron drift velocity under the condition of impact ionization has been developed by considering all major scattering mechanisms such as deformation potential acoustic phonon scattering, piezoelectric acoustic phonon scattering, optical phonon scattering, electron-electron scattering and ionizing scattering. Numerical calculations show that electron drift velocity in Wz-GaN saturates at 1.44 × 105 m/s at room temperature for the electron concentration of 1022 m−3. The effects of temperature and doping concentration on the hot electron drift velocity in Wz-GaN have also been studied. Results show that the saturation electron drift velocity varies from 1.91 × 105–0.77 × 105 m/s for the change in temperature within the range of 10–1000 K, for the electron concentration of 1022 m−3; whereas the same varies from 1.44 × 105–0.91 × 105 m/s at 300 K for the variation in the electron concentration within the range of 1022–1025 m−3. The numerically calculated results have been compared with the Monte Carlo simulated results and experimental data reported earlier, and those are found to be in good agreement.

The hot electron transport in wurtzite phase gallium nitride (Wz-GaN) has been studied in this paper. An analytical expression of electron drift velocity under the condition of impact ionization has been developed by considering all major scattering mechanisms such as deformation potential acoustic phonon scattering, piezoelectric acoustic phonon scattering, optical phonon scattering, electron-electron scattering and ionizing scattering. Numerical calculations show that electron drift velocity in Wz-GaN saturates at 1.44 × 105 m/s at room temperature for the electron concentration of 1022 m−3. The effects of temperature and doping concentration on the hot electron drift velocity in Wz-GaN have also been studied. Results show that the saturation electron drift velocity varies from 1.91 × 105–0.77 × 105 m/s for the change in temperature within the range of 10–1000 K, for the electron concentration of 1022 m−3; whereas the same varies from 1.44 × 105–0.91 × 105 m/s at 300 K for the variation in the electron concentration within the range of 1022–1025 m−3. The numerically calculated results have been compared with the Monte Carlo simulated results and experimental data reported earlier, and those are found to be in good agreement.
SEMICONDUCTOR MATERIALS
Controlling morphology evolution of AlN nanostructures: influence of growth conditions in physical vapor transport
Lei Jin, Hongjuan Cheng, Jianli Chen, Song Zhang, Yongkuan Xu, Zhanping Lai
J. Semicond.  2018, 39(7): 073001  doi: 10.1088/1674-4926/39/7/073001

A series of AlN nanostructures were synthesized by an ultrahigh-temperature, catalyst-free, physical vapor transport (PVT) process. Energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), X-Ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (HRTEM) detection show that high quality AlN nanowires were prepared. Nanostructures including nanorings, nanosprings, nanohelices, chain-like nanowires, six-fold symmetric nanostructure and rod-like structure were successfully obtained by controlling the growth duration and temperature. The morphology evolution was attributed to electrostatic polar charge model and the crystalline lattice structure of AlN.

A series of AlN nanostructures were synthesized by an ultrahigh-temperature, catalyst-free, physical vapor transport (PVT) process. Energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), X-Ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (HRTEM) detection show that high quality AlN nanowires were prepared. Nanostructures including nanorings, nanosprings, nanohelices, chain-like nanowires, six-fold symmetric nanostructure and rod-like structure were successfully obtained by controlling the growth duration and temperature. The morphology evolution was attributed to electrostatic polar charge model and the crystalline lattice structure of AlN.
SEMICONDUCTOR DEVICES
Small-signal model parameter extraction of E-mode N-polar GaN MOS-HEMT using optimization algorithms and its comparison
D. K. Panda, G. Amarnath, T. R. Lenka
J. Semicond.  2018, 39(7): 074001  doi: 10.1088/1674-4926/39/7/074001

An improved small-signal parameter extraction technique for short channel enhancement-mode N-polar GaN MOS-HEMT is proposed, which is a combination of a conventional analytical method and optimization techniques. The extrinsic parameters such as parasitic capacitance, inductance and resistance are extracted under the pinch-off condition. The intrinsic parameters of the small-signal equivalent circuit (SSEC) have been extracted including gate forward and backward conductance. Different optimization algorithms such as PSO, Quasi Newton and Firefly optimization algorithm is applied to the extracted parameters to minimize the error between modeled and measured S-parameters. The different optimized SSEC models have been validated by comparing the S-parameters and unity current-gain with TCAD simulations and available experimental data from the literature. It is observed that the Firefly algorithm based optimization approach accurately extracts the small-signal model parameters as compared to other optimization algorithm techniques with a minimum error percentage of 1.3%.

An improved small-signal parameter extraction technique for short channel enhancement-mode N-polar GaN MOS-HEMT is proposed, which is a combination of a conventional analytical method and optimization techniques. The extrinsic parameters such as parasitic capacitance, inductance and resistance are extracted under the pinch-off condition. The intrinsic parameters of the small-signal equivalent circuit (SSEC) have been extracted including gate forward and backward conductance. Different optimization algorithms such as PSO, Quasi Newton and Firefly optimization algorithm is applied to the extracted parameters to minimize the error between modeled and measured S-parameters. The different optimized SSEC models have been validated by comparing the S-parameters and unity current-gain with TCAD simulations and available experimental data from the literature. It is observed that the Firefly algorithm based optimization approach accurately extracts the small-signal model parameters as compared to other optimization algorithm techniques with a minimum error percentage of 1.3%.
Impact of crystal orientation and surface scattering on DG-MOSFETs in quasi-ballistic region
Lei Shen, Shaoyan Di, Longxiang Yin, Yun Li, Xiaoyan Liu, Gang Du
J. Semicond.  2018, 39(7): 074002  doi: 10.1088/1674-4926/39/7/074002

The characteristics of nano scale n-type double gate MOSFETs with (100) and (110) surfaces are studied using 3D full band ensemble Monte Carlo simulator. The anisotropic surface scattering mechanism is investigated. The (100) case is sensitive to the gate voltage more than the (110) case. The impact of crystal orientation and surface scattering on transport features mainly reflects in the carrier velocity distribution. The electron transport features with (100) direction are greater than that with (110) direction, but are more likely to be affected by the surface scattering.

The characteristics of nano scale n-type double gate MOSFETs with (100) and (110) surfaces are studied using 3D full band ensemble Monte Carlo simulator. The anisotropic surface scattering mechanism is investigated. The (100) case is sensitive to the gate voltage more than the (110) case. The impact of crystal orientation and surface scattering on transport features mainly reflects in the carrier velocity distribution. The electron transport features with (100) direction are greater than that with (110) direction, but are more likely to be affected by the surface scattering.
Research on the hydrogen terminated single crystal diamond MOSFET with MoO3 dielectric and gold gate metal
Zeyang Ren, Jinfeng Zhang, Jincheng Zhang, Chunfu Zhang, Pengzhi Yang, Dazheng Chen, Yao Li, Yue Hao
J. Semicond.  2018, 39(7): 074003  doi: 10.1088/1674-4926/39/7/074003

The single crystal diamond with maximum width about 10 mm has been grown by using microwave plasma chemical vapor deposition equipment. The quality of the grown diamond was characterized using an X-ray diffractometer. The FWHM of the (004) rocking curve is 37.91 arcsec, which is comparable to the result of the electronic grade single crystal diamond commercially obtained from Element Six Ltd. The hydrogen terminated diamond field effect transistors with Au/MoO3 gates were fabricated based on our CVD diamond and the characteristics of the device were compared with the prototype Al/MoO3 gate. The device with the Au/MoO3 gate shows lower on-resistance and higher gate leakage current. The detailed analysis indicates the presence of aluminum oxide at the Al/MoO3 interface, which has been directly demonstrated by characterizing the interface between Al and MoO3 by X-ray photoelectron spectroscopy. In addition, there should be a surface transfer doping effect of the MoO3 layer on H-diamond even with the atmospheric-adsorbate induced 2DHG preserved after MoO3 deposition.

The single crystal diamond with maximum width about 10 mm has been grown by using microwave plasma chemical vapor deposition equipment. The quality of the grown diamond was characterized using an X-ray diffractometer. The FWHM of the (004) rocking curve is 37.91 arcsec, which is comparable to the result of the electronic grade single crystal diamond commercially obtained from Element Six Ltd. The hydrogen terminated diamond field effect transistors with Au/MoO3 gates were fabricated based on our CVD diamond and the characteristics of the device were compared with the prototype Al/MoO3 gate. The device with the Au/MoO3 gate shows lower on-resistance and higher gate leakage current. The detailed analysis indicates the presence of aluminum oxide at the Al/MoO3 interface, which has been directly demonstrated by characterizing the interface between Al and MoO3 by X-ray photoelectron spectroscopy. In addition, there should be a surface transfer doping effect of the MoO3 layer on H-diamond even with the atmospheric-adsorbate induced 2DHG preserved after MoO3 deposition.
A GaN/InGaN/AlGaN MQW RTD for versatile MVL applications with improved logic stability
Haipeng Zhang, Qiang Zhang, Mi Lin, Weifeng Lü, Zhonghai Zhang, Jianling Bai, Jian He, Bin Wang, Dejun Wang
J. Semicond.  2018, 39(7): 074004  doi: 10.1088/1674-4926/39/7/074004

To improve the logic stability of conventional multi-valued logic (MVL) circuits designed with a GaN-based resonate tunneling diode (RTD), we proposed a GaN/InGaN/AlGaN multi-quantum well (MQW) RTD. The proposed RTD was simulated through solving the coupled Schrodinger and Poisson equations in the numerical non-equilibrium Green’s function (NEGF) method on the TCAD platform. The proposed RTD was grown layer by layer in epitaxial technologies. Simulated results indicate that its current-voltage characteristic appears to have a wider total negative differential resistance region than those of conventional ones and an obvious hysteresis loop at room temperature. To increase the Al composite of AlGaN barrier layers properly results in increasing of both the total negative differential resistance region width and the hysteresis loop width, which is helpful to improve the logic stability of MVL circuits. Moreover, the complement resonate tunneling transistor pair consisted of the proposed RTDs or the proposed RTD and enhanced mode HEMT controlled RTD is capable of generating versatile MVL modes at different supply voltages less than 3.3 V, which is very attractive for implementing more complex MVL function digital integrated circuits and systems with less devices, super high speed linear or nonlinear ADC and voltage sensors with a built-in super high speed ADC function.

To improve the logic stability of conventional multi-valued logic (MVL) circuits designed with a GaN-based resonate tunneling diode (RTD), we proposed a GaN/InGaN/AlGaN multi-quantum well (MQW) RTD. The proposed RTD was simulated through solving the coupled Schrodinger and Poisson equations in the numerical non-equilibrium Green’s function (NEGF) method on the TCAD platform. The proposed RTD was grown layer by layer in epitaxial technologies. Simulated results indicate that its current-voltage characteristic appears to have a wider total negative differential resistance region than those of conventional ones and an obvious hysteresis loop at room temperature. To increase the Al composite of AlGaN barrier layers properly results in increasing of both the total negative differential resistance region width and the hysteresis loop width, which is helpful to improve the logic stability of MVL circuits. Moreover, the complement resonate tunneling transistor pair consisted of the proposed RTDs or the proposed RTD and enhanced mode HEMT controlled RTD is capable of generating versatile MVL modes at different supply voltages less than 3.3 V, which is very attractive for implementing more complex MVL function digital integrated circuits and systems with less devices, super high speed linear or nonlinear ADC and voltage sensors with a built-in super high speed ADC function.
Micro-plasma noise of 30 krad gamma irradiation broken-down GaN-based LED
Yu’an Liu, Wenlang Luo
J. Semicond.  2018, 39(7): 074005  doi: 10.1088/1674-4926/39/7/074005

A correlation model between micro plasma noise and gamma irradiation of GaN-based LED is built. The reverse bias I–V characteristics and micro-plasma noise were measured in it, before and after Gamma irradiation. It is found that even after 30 krad Gamma irradiation, the GaN-based LED has soft breakdown failure. The reverse soft breakdown region current local instability of this device before irradiation is analyzed by the micro-plasma noise method. The results were obtained that if the GaN-based LED contained micro-plasma defects, it will fail after low doses (30 krad) of gamma irradiation. The results clearly reflect the micro-plasma defects induced carriers fluctuation noise and the local instability of GaN-based LED reverse bias current.

A correlation model between micro plasma noise and gamma irradiation of GaN-based LED is built. The reverse bias I–V characteristics and micro-plasma noise were measured in it, before and after Gamma irradiation. It is found that even after 30 krad Gamma irradiation, the GaN-based LED has soft breakdown failure. The reverse soft breakdown region current local instability of this device before irradiation is analyzed by the micro-plasma noise method. The results were obtained that if the GaN-based LED contained micro-plasma defects, it will fail after low doses (30 krad) of gamma irradiation. The results clearly reflect the micro-plasma defects induced carriers fluctuation noise and the local instability of GaN-based LED reverse bias current.
Comparative analysis of memristor models and memories design
Jeetendra Singh, Balwinder Raj
J. Semicond.  2018, 39(7): 074006  doi: 10.1088/1674-4926/39/7/074006

The advent of the memristor breaks the scaling limitations of MOS technology and prevails over emerging semiconductor devices. In this paper, various memristor models including behaviour, spice, and experimental are investigated and compared with the memristor’s characteristic equations and fingerprints. It has brought to light that most memristor models need a window function to resolve boundary conditions. Various challenges of availed window functions are discussed with matlab’s simulated results. Biolek’s window is a most acceptable window function for the memristor, since it limits boundaries growth as well as sticking of states at boundaries. Simmons tunnel model of a memristor is the most accepted model of a memristor till now. The memristor is exploited very frequently in memory designing and became a prominent candidate for futuristic memories. Here, several memory structures utilizing the memristor are discussed. It is seen that a memristor-transistor hybrid memory cell has fast read/write and low power operations. Whereas, a 1T1R structure provides very simple, nanoscale, and non-volatile memory that has capabilities to replace conventional Flash memories. Moreover, the memristor is frequently used in SRAM cell structures to make them have non-volatile memory. This paper contributes various aspects and recent developments in memristor based circuits, which can enhance the ongoing requirements of modern designing criterion.

The advent of the memristor breaks the scaling limitations of MOS technology and prevails over emerging semiconductor devices. In this paper, various memristor models including behaviour, spice, and experimental are investigated and compared with the memristor’s characteristic equations and fingerprints. It has brought to light that most memristor models need a window function to resolve boundary conditions. Various challenges of availed window functions are discussed with matlab’s simulated results. Biolek’s window is a most acceptable window function for the memristor, since it limits boundaries growth as well as sticking of states at boundaries. Simmons tunnel model of a memristor is the most accepted model of a memristor till now. The memristor is exploited very frequently in memory designing and became a prominent candidate for futuristic memories. Here, several memory structures utilizing the memristor are discussed. It is seen that a memristor-transistor hybrid memory cell has fast read/write and low power operations. Whereas, a 1T1R structure provides very simple, nanoscale, and non-volatile memory that has capabilities to replace conventional Flash memories. Moreover, the memristor is frequently used in SRAM cell structures to make them have non-volatile memory. This paper contributes various aspects and recent developments in memristor based circuits, which can enhance the ongoing requirements of modern designing criterion.
SEMICONDUCTOR INTEGRATED CIRCUITS
A BFSK and OOK IF demodulation circuit with 2.8 μs settling time and re-configurable image rejection functions for MICS/BCC applications
Tongqiang Gao, Zhenxiong Chen, Siqi Zhao, Haigang Yang, Xinxia Cai
J. Semicond.  2018, 39(7): 075001  doi: 10.1088/1674-4926/39/7/075001

A BFSK and OOK IF base-band circuit is provided to implement the low-IF RF receivers for a dual-band MICS/BCC network controller. In order to transfer the massive vital data immediately, the IF circuit is comprised of the fast-settling feed-forward programmable gain amplifier (PGA), a GmC complex filter, the fixed gain amplifier (FGA) and a 4-input " quadratic sum” demodulator. A novel auto-switched coarse gain-setting method is adopted in the PGA to enhance the reaction speed and narrow the output signal range. Also the PGA does not suffer the same stability constraint as open-loop topologies. The complex filter fulfills the function of image rejection, in which the center frequency and bandwidth can be adjusted individually. The FGA is used to ameliorate the linearity and the ‘quadratic sum’ demodulator can reduce the overall power consumption. The designed IF circuit is fabricated with SMIC 0.18 μm CMOS process. The chip area is about 5.36 mm2. Measurement results are given to verify the design goals.

A BFSK and OOK IF base-band circuit is provided to implement the low-IF RF receivers for a dual-band MICS/BCC network controller. In order to transfer the massive vital data immediately, the IF circuit is comprised of the fast-settling feed-forward programmable gain amplifier (PGA), a GmC complex filter, the fixed gain amplifier (FGA) and a 4-input " quadratic sum” demodulator. A novel auto-switched coarse gain-setting method is adopted in the PGA to enhance the reaction speed and narrow the output signal range. Also the PGA does not suffer the same stability constraint as open-loop topologies. The complex filter fulfills the function of image rejection, in which the center frequency and bandwidth can be adjusted individually. The FGA is used to ameliorate the linearity and the ‘quadratic sum’ demodulator can reduce the overall power consumption. The designed IF circuit is fabricated with SMIC 0.18 μm CMOS process. The chip area is about 5.36 mm2. Measurement results are given to verify the design goals.