bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving vertical GaN p–n diode performance with room temperature defect mitigation
Authors: Sultan Al-Mamun Nahid , Gallagher James , Jacobs Alan G , Hobart Karl D , Anderson Travis J , Gunning Brendan P , Kaplar Robert J , Wolfe Douglas E , Haque Aman 
Published: November 2023

Abstract
Defect mitigation of electronic devices is conventionally achieved using thermal annealing. To mobilize the defects, very high temperatures are necessary. Since thermal diffusion is random in nature, the process may take a prolonged period of time. In contrast, we demonstrate a room temperature annealing technique that takes only a few seconds. The fundamental mechanism is defect mobilization by atomic scale mechanical force originating from very high current density but low duty cycle electrical pulses. The high-energy electrons lose their momentum upon collision with the defects, yet the low duty cycle suppresses any heat accumulation to keep the temperature ambient. For a 7 × 105 A cm−2 pulsed current, we report an approximately 26% reduction in specific on-resistance, a 50% increase of the rectification ratio with a lower ideality factor, and reverse leakage current for as-fabricated vertical geometry GaN p–n diodes. We characterize the microscopic defect density of the devices before and after the room temperature processing to explain the improvement in the electrical characteristics. Raman analysis reveals an improvement in the crystallinity of the GaN layer and an approximately 40% relaxation of any post-fabrication residual strain compared to the as-received sample. Cross-sectional transmission electron microscopy (TEM) images and geometric phase analysis results of high-resolution TEM images further confirm the effectiveness of the proposed room temperature annealing technique to mitigate defects in the device. No detrimental effect, such as diffusion and/or segregation of elements, is observed as a result of applying a high-density pulsed current, as confirmed by energy dispersive x-ray spectroscopy mapping.
Waveguide-integrated optical modulators with two-dimensional materials
Authors: Chen Haitao , Cao Hongyuan , Yu Zejie , Zhao Weike , Dai Daoxin 
Published: November 2023

Abstract
Waveguide-integrated optical modulators are indispensable for on-chip optical interconnects and optical computing. To cope with the ever-increasing amount of data being generated and consumed, ultrafast waveguide-integrated optical modulators with low energy consumption are highly demanded. In recent years, two-dimensional (2D) materials have attracted a lot of attention and have provided tremendous opportunities for the development of high-performance waveguide-integrated optical modulators because of their extraordinary optoelectronic properties and versatile compatibility. This paper reviews the state-of-the-art waveguide-integrated optical modulators with 2D materials, providing researchers with the developing trends in the field and allowing them to identify existing challenges and promising potential solutions. First, the concept and fundamental mechanisms of optical modulation with 2D materials are summarized. Second, a review of waveguide-integrated optical modulators employing electro-optic, all-optic, and thermo-optic effects is provided. Finally, the challenges and perspectives of waveguide-integrated modulators with 2D materials are discussed.
Performance optimization of tri-gate junctionless FinFET using channel stack engineering for digital and analog/RF design
Authors: Singh Devenderpal , Chaudhary Shalini , Dewan Basudha , Yadav Menka 
Published: November 2023

Abstract
This manuscript explores the behavior of a junctionless tri-gate FinFET at the nano-scale region using SiGe material for the channel. For the analysis, three different channel structures are used: (a) tri-layer stack channel (TLSC) (Si–SiGe–Si), (b) double layer stack channel (DLSC) (SiGe–Si), (c) single layer channel (SLC) (Si). The I−V characteristics, subthreshold swing (SS), drain-induced barrier lowering (DIBL), threshold voltage (V
t), drain current (I
ON), OFF current (I
OFF), and ON-OFF current ratio (I
ON/I
OFF) are observed for the structures at a 20 nm gate length. It is seen that TLSC provides 21.3% and 14.3% more ON current than DLSC and SLC, respectively. The paper also explores the analog and RF factors such as input transconductance (g
m), output transconductance (g
ds), gain (g
m/g
ds), transconductance generation factor (TGF), cut-off frequency (f
T), maximum oscillation frequency (f
max), gain frequency product (GFP) and linearity performance parameters such as second and third-order harmonics (g
m2, g
m3), voltage intercept points (VIP2, VIP3) and 1-dB compression points for the three structures. The results show that the TLSC has a high analog performance due to more g
m and provides 16.3%, 48.4% more gain than SLC and DLSC, respectively and it also provides better linearity. All the results are obtained using the VisualTCAD tool.
Design and simulation of modified 3D-trench electrode sensors
Authors: Ye Jixing , Loi Angelo , Lai Adriano , Dalla Betta Gian-Franco 
Published: November 2023

Abstract
Future experiments at high-luminosity hadron colliders will involve unprecedent levels of
pile up, calling for ultrafast detectors in order to add time information to distinguish between
particle tracks. The unique geometry of 3D sensors enables to achieve very good timing
performance, with the additional benefit of high radiation hardness. Remarkable results in terms
of temporal resolution have been reported for 3D sensors with columnar electrodes (∼30 ps)
and even better with trenched electrodes (∼10 ps), because of a more uniform distribution of
the electric field and weighting field. However, 3D-trench technology is more complex, and has
still to be optimized in terms of both fabrication process and pixel layout. To this purpose, as
an alternative to the existing design which features continuous (p+) ohmic trenches, we propose
a new variant by introducing a gap (∼10 μm) in the p+ trenches and placed offset
with respect to the readout (n+) trenches, so as to reduce the risk of lithographical defects
that were observed in mm's long ohmic trenches, thus improving the fabrication yield.

TCAD simulations confirmed that the impact of the gap on the uniformity of the electric and weighting field is minimum, and good charge collection efficiency performance is preserved up to large fluences. Further Monte Carlo time-resolved simulations are performed on both the standard and modified geometries showing comparable temporal resolutions.
The link between intertropical convergence zone stagnation and bias in local shortwave cloud radiative forcing over tropical Africa in climate models
Authors: Dombo Tomviezibe C , AchutaRao Krishna M , Sandeep S 
Published: November 2023

Abstract
The northward migration of the intertropical convergence zone (ITCZ) is a significant feature of the West African (WA) monsoon. An accurate simulation of ITCZ migration is essential for the realistic representation of WA precipitation in global coupled models. In this study, we employ the energetics and dynamics framework with a subset of CMIP6 models to investigate the bias in the simulated WA precipitation. Models were found to simulate more local positive (negative) shortwave cloud radiative forcing (SWCRF) in the Southeastern Atlantic Ocean (over the African continent). The effect of the excess local SWCRF is linked to the stagnation of the ITCZ latitudinal migration and the associated biases in the asymmetry index of precipitation. In the models, there is more (less) moist static energy in the lower (mid and upper) troposphere than in the reanalysis. The worst models have a stronger bias, especially over land. The vertical transport of moisture is confined to the boundary layer in the worst model ensemble. In most cases, the high-resolution coupled models show substantial northward migration of the ITCZ compared to the low-resolution models. Furthermore, the best-performing models capture local circulation and energetic processes more accurately than the worst-performing models.
The role of solvent interfacial structural ordering in maintaining stable graphene dispersions
Authors: Patil Urvesh , Caffrey Nuala M 
Published: November 2023

Abstract
Liquid phase exfoliation is the most promising method for the low-cost, scalable production of two-dimensional nanosheets from their bulk counterparts. Extensive exfoliation occurs in most solvents due to the huge amount of energy introduced by sonication or shear mixing. However, the subsequent dispersion is not always stable, with extensive reaggregation occurring in some solvents. Identifying the optimal solvent for a particular layered material is difficult and requires a fundamental understanding of the mechanism involved in maintaining a stable dispersion. Here, we use molecular dynamics calculations to show that when graphene is immersed in a solvent, distinct solvation layers are formed irrespective of the choice of solvent and their formation is energetically favourable for all considered solvents. However, energetic considerations such as these do not explain the experimental solvent-dependence of the dispersion concentration. Instead, we find that solvents with high diffusion coefficients parallel to the graphene layer result in the lowest experimental concentration of graphene in solution. This can be explained by the enhanced ease of reaggregation in these solvents. Solvents with smaller diffusion coefficients result in higher experimental graphene concentrations as reaggregation is prevented. In the low diffusion limit, however, this relationship breaks down. We suggest that here the concentration of graphene in solution depends primarily on the separation efficiency of the initial exfoliation step. Based on this, we predict that the concentration of exfoliated graphene in solvents such as benzaldehyde and quinoline, which have low diffusion constants, can be increased dramatically by careful tuning of the experimental sonication parameters.
Controllable superconducting to semiconducting phase transition in topological superconductor 2M-WS2
Authors: Gautam Sabin , McBride Joseph , Scougale William R , Samarawickrama Piumi I , De Camargo Branco Danilo , Yang Peilin , Fu ZhuangEn , Wang Wenyong , Tang Jinke , Cheng Gary J , Ackerman John , Chien TeYu , Leonard Brian M , Tian Jifa 
Published: November 2023

Abstract
The investigation of exotic properties in two-dimensional (2D) topological superconductors has garnered increasing attention in condensed matter physics, particularly for applications in topological qubits. Despite this interest, a reliable way of fabricating topological Josephson junctions (JJs) utilizing topological superconductors has yet to be demonstrated. Controllable structural phase transition presents a unique approach to achieving topological JJs in atomically thin 2D topological superconductors. In this work, we report the pioneering demonstration of a structural phase transition from the superconducting to the semiconducting phase in the 2D topological superconductor 2M-WS2. We reveal that the metastable 2M phase of WS2 remains stable in ambient conditions but transitions to the 2H phase when subjected to temperatures above 150 °C. We further locally induced the 2H phase within 2M-WS2 nanolayers using laser irradiation. Notably, the 2H phase region exhibits a hexagonal shape, and scanning tunneling microscopy uncovers an atomically sharp crystal structural transition between the 2H and 2M phase regions. Moreover, the 2M to 2H phase transition can be induced at the nanometer scale by a 200 kV electron beam. The electrical transport measurements further confirmed the superconductivity of the pristine 2M-WS2 and the semiconducting behavior of the laser-irradiated 2M-WS2. Our results establish a novel approach for controllable topological phase change in 2D topological superconductors, significantly impacting the development of atomically scaled planar topological JJs.
Examining the adsorption efficiency of iron oxide-decorated magnetic halloysite nanotubes for tetracycline elimination from solutions
Authors: Wang Na , Ma Wei , Hou Yanmin , Gao Hang 
Published: November 2023

Abstract
In our research, we investigated the potential of HNT-Fe3O4, a magnetic adsorbent composed of halloysite nanotubes(HNTs) and iron oxide nanoparticles, for removing tetracyclines(TCs) from water. We utilized a range of analytical techniques such as FT-IR, VSM, XRD, BET, TEM, TGA, and SEM to characterize the materials. Furthermore, we evaluated HNT-Fe3O4’s capability to remove TCs from water, particularly noting the influence of solution pH on its adsorption properties. Results indicated that the adsorption process adhered to the pseudo-second-order kinetics, with the Langmuir model best describing the adsorption isotherms. The reusability study revealed that after six repeated uses, HNT-Fe3O4 maintained most of its adsorption efficiency. An adsorption–desorption experiment further confirmed its potential as a valuable adsorbent for wastewater treatment. In summary, our study underscores the potential of HNT-Fe3O4 as a durable and effective medium for TCs removal in water treatment.
Carbothermal reduction assisted by hydrogenation treatment for preparing single-phase CeC2 nanoscale powders
Authors: Liu Guoqin , Lian Lixian , Liu Ying 
Published: November 2023

Abstract
Single-phase CeC2 powders can be successfully prepared through the carbothermal reduction assisted by hydrogenation treatment (CRHT) using 20–50 nm CeO2 as cerium source and 100–200 nm carbon black as carbon source. During the hydrogenation process, the interaction of CeO2 with H2 leads to a partial valence reduction of Ce ions, yielding a partially anoxic phase (CeO1.675) and a hydrogenated phase (CeH2). CeO1.675 can increase the oxygen vacancies required in the reaction process, while CeH2 can produce gas-phase reductant H2 at the reaction temperature, which together promotes the reduction reaction. The results show that the CRHT can obtain single-phase CeC2 powders at a temperature of 1550 °C, which is 100 °C lower than its theoretical temperature. For the preparation of CeC2 powders, the CRHT is a low-temperature and efficient method.
Risk and self-optimization analysis of the carbon tax policy based on scenario simulation
Authors: Zhang Kanghui , Lu Long 
Published: November 2023

Abstract
The double dividend of the carbon tax policy has been a controversial topic. To comprehensively evaluate the benefits and risks brought by the carbon tax policy and contribute to China’s emission reduction goals, this paper establishes a carbon tax policy cycle simulation model based on China’s economic and energy data from 2010 to 2020 to explore the winner-curse phenomenons of the policy. To alleviate the winner’s curse of the carbon tax policy, this paper introduces a consumer behavior model to explore the optimization degree of loss aversion effect on the carbon tax policy. The research results show that the carbon tax policy has three kinds of winner’s curse phenomenons, namely, the improvement of environmental quality and the reduction of market capital, the decline of national carbon intensity and the increase of carbon intensity of three major industries, and the reuse of the tax revenue and the increase of economic loss. The loss aversion of consumers can alleviate the negative effect of the carbon tax policy and strengthen the positive effect. In addition, during the implementation of the carbon tax policy, the loss aversion effect can also reduce the polluted population by about 2%. Finally, based on the research results, the paper puts forward some feasible policy suggestions.
A comparative analysis of US state-level policies and programs to advance energy justice
Authors: Sandoval Noah , Morgenstein Jonathan , Geiger Jesse , Gibbs Patrick , Bazilian Morgan , Warren Adam 
Published: November 2023

Abstract
The US energy system is undergoing massive changes that have environmental, technological, and societal implications. Decisions and actions taken now will dramatically alter the trajectory of our future energy system. Though new technologies can lessen the dangers of anthropogenic climate change, an effective and sustainable transition requires addressing social justice issues as a priority. To this end, many states have implemented policies and programs that address energy justice. A formal survey of state-level energy justice policies and programs is needed to better understand the methods used to assist communities targeted and the impacts of these efforts. Such an analysis should include an analysis of the metrics used to judge the effectiveness of the enacted policies and programs. In this paper, we analyze the energy justice policies and programs of seven different US states. From this analysis, we identify three important aspects of state energy policies. First, most policies and programs do not articulate their goals, nor cite metrics to judge their successes. This lack of transparency and accountability is a major roadblock to truly just solutions. Second, states focus on a very narrow range of solutions for energy justice issues. The most prevalent being utility bill assistance, which does not address the systemic and enduring challenges faced by many low-income or historically marginalized communities. Lastly, comprehensive energy policy does not acknowledge and address housing, employment, education, and healthcare inequities that exacerbate energy system inequities. The work presented in this paper sheds light on the progress of state-level energy justice policies and programs across the United States, and we argue more work needs to be done to understand best practices in energy justice policymaking.
Deep learning for enhanced free-space optical communications
Authors: Bart M P , Savino N J , Regmi P , Cohen L , Safavi H , Shaw H C , Lohani S , Searles T A , Kirby B T , Lee H , Glasser R T 
Published: November 2023

Abstract
Atmospheric effects, such as turbulence and background thermal noise, inhibit the propagation of light used in ON–OFF keying (OOK) free-space optical (FSO) communication. Here we present and experimentally validate a convolutional neural network (CNN) to reduce the bit error rate of FSO communication in post-processing that is significantly simpler and cheaper than existing solutions based on advanced optics. Our approach consists of two neural networks, the first determining the presence of bit sequences in thermal noise and turbulence and the second demodulating the bit sequences. All data used for training and testing our network is obtained experimentally by generating OOK bit streams, combining these with thermal light, and passing the resultant light through a turbulent water tank which we have verified mimics turbulence in the air to a high degree of accuracy. Our CNN improves detection accuracy over threshold classification schemes and has the capability to be integrated with current demodulation and error correction schemes.
GA-based weighted ensemble learning for multi-label aerial image classification using convolutional neural networks and vision transformers
Authors: Tseng Ming-Hseng 
Published: November 2023

Abstract
Multi-label classification (MLC) of aerial images is a crucial task in remote sensing image analysis. Traditional image classification methods have limitations in image feature extraction, leading to an increasing use of deep learning models, such as convolutional neural networks (CNN) and vision transformers (ViT). However, the standalone use of these models may have limitations when dealing with MLC. To enhance the generalization performance of MLC of aerial images, this paper combines two CNN and two ViT models, comparing four single deep learning models, a manually weighted ensemble learning method, and a GA-based weighted ensemble method. The experimental results using two public multi-label aerial image datasets show that the classification performance of ViT models is better than CNN models, the traditional weighted ensemble learning model performs better than a single deep learning model, and the GA-based weighted ensemble method performs better than the manually weighted ensemble learning method. The GA-based weighted ensemble method proposed in this study can achieve better MLC performance of aerial images than previous results.
Bimetallic nanoparticles green synthesis from litchi leaf extract: a promising approach for breast cancer treatment
Authors: Kaur Ramanjeet , Singh Jitender , Avti Pramod K , Kumar Vivek , Kumar Rajesh 
Published: November 2023

AbstractNoble metal nanoparticles have demonstrated promising biomedical and nanomedicine applications, and their bimetallic equivalents from the green synthesis approach are expected to be more promising. This study concerns bimetallic nanoparticle’s synthesis, characterization, and structure-function analysis for their potential application in breast cancer. Silver core (SCNPs) and Gold core (GCNPs) bimetallic nanoparticles were synthesized usingLitchi Chinesisleaf extract (LCLE) and characterized using various physio-chemical techniques. The results revealed the successful synthesis of SCNPs and GCNPs with distinct surface plasmon resonance peaks at 551 nm and 531 nm, hydrodynamic sizes of 66 nm and 53 nm, and Zeta potential values of −26.0 mV and −20.6 mV. XRD analysis confirmed the presence of silver and gold phases, while HR-TEM images revealed spherical shapes for SCNPs and heterogenous shapes for GCNPs. Both nanoparticles demonstrated dose and time-dependent inhibition of breast cancer cell growth, with GCNPs requiring a higher concentration than SCNPs at 48 h compared to 24 h. Cell cycle evaluation indicated a cell cycle arrest in the G2M phase for both nanoparticles, an impact on the S phase distribution, and reactive oxygen species (ROS) generation, further contributing to their antiproliferative effects.