Current Distribution Research Articles

Modelling the current and future agro-ecological distribution potential of Mexican prickly poppy (Argemone mexicana L.) invasive alien plant species in South Wollo, Ethiopia

ABSTRACT Argemone mexicana L. is an invasive alien plant species (IAPS) that belongs to Papaveraceae family. This study aimed to identify and map its current and future (2050 and 2070) potential distribution in South Wollo, Ethiopia. Eight Kebeles were selected using a stratified random sampling method that covered two agro-ecologies ranging 1500–3200masl for species presence data collection and 204 presences data were used for modelling. Climate, topography, and land use land cover change (LUCC) variables were used to build the species distribution model (SDM). An ensemble SDM model was run consisting of five algorithms into one single model. The area under the curve (AUC) and true skill statics (TSS) of the ensemble SDM score values of 0.89 and 0.7, respectively. The predicted result on its agro-ecological distribution showed 76.75% was non-suitable and 23.26% was suitable in varied extents, currently. Suitability will be increased after LUCC and climate change except the SSP5–8.5 2070 emission scenario. It will be highest under SSP1–2.6, 2050, and SSP2–4.5, 2070 emission scenarios possessing 28.67% and 28% suitability class, respectively. A. mexicana distributed in the mid and highland agro-ecologies from 1500–3200masl both in current and future time period. It urges effective coordination among actors to minimize its distribution potential.

Projecting the impact of climate change on honey bee plant habitat distribution in Northern Ethiopia

Climate change significantly affects the diversity, growth, and survival of indigenous plant species thereby influencing the nutrition, health and productivity of honey bees (Apis mellifera). Hypoestes forskaolii (Vahl) is one of the major honey bee plant species in Ethiopia’s Tigray region. It is rich in pollen and nectar that typically provides white honey, which fetches a premium price in both local and inter-national markets. Despite its socio-economic and apicultural significance, the distribution of H. forskaolii has been declining, raising concerns regarding its conservation efforts. However, there is limited knowledge on how environmental and climatic factors affect its current distribution and response to future climate change. The study investigates the current and projected (the 2030s, 2050s, 2070s, and 2090s) habitat distributions of H. forskaolii under three future climate change scenarios (ssp126, ssp245, and ssp585) using the Maximum Entropy Model (MaxEnt). The results show that land use (50.1%), agro-ecology (28%), precipitation during the Driest Quarter (11.2%) and soil texture (6.1%) predominantly influence the distribution of H. forskaolii, collectively explaining 95.4% of the model's predictive power. Habitats rich in evergreen trees and mosaic herbaceous with good vegetation cover are identified as the most suitable for H. forskaolii. The spatial distribution of H. forskaolii is concentrated in the highlands and mid-highlands of the eastern and southern parts of Tigray, characterized by a colder temperature. Across the three climate change scenarios, the size of suitable habitat for H. forskaolii is projected to decrease over the four time periods studied. Predictions under the ssp585 scenario reveal alarming results, indicating a substantial decrease in the suitable habitat for H. forskaolii from 4.26% in the 2030s to 19.09% in the 2090s. Therefore, given the challenges posed by climate change, research efforts should focus on identifying and evaluating new technologies that can help the H. forskaolii species in adapting and mitigating the effects of climate change.

Projecting the impact of climate change on honey bee plant habitat distribution in Northern Ethiopia

Climate change significantly affects the diversity, growth, and survival of indigenous plant species thereby influencing the nutrition, health and productivity of honey bees (Apis mellifera). Hypoestes forskaolii (Vahl) is one of the major honey bee plant species in Ethiopia’s Tigray region. It is rich in pollen and nectar that typically provides white honey, which fetches a premium price in both local and inter-national markets. Despite its socio-economic and apicultural significance, the distribution of H. forskaolii has been declining, raising concerns regarding its conservation efforts. However, there is limited knowledge on how environmental and climatic factors affect its current distribution and response to future climate change. The study investigates the current and projected (the 2030s, 2050s, 2070s, and 2090s) habitat distributions of H. forskaolii under three future climate change scenarios (ssp126, ssp245, and ssp585) using the Maximum Entropy Model (MaxEnt). The results show that land use (50.1%), agro-ecology (28%), precipitation during the Driest Quarter (11.2%) and soil texture (6.1%) predominantly influence the distribution of H. forskaolii, collectively explaining 95.4% of the model's predictive power. Habitats rich in evergreen trees and mosaic herbaceous with good vegetation cover are identified as the most suitable for H. forskaolii. The spatial distribution of H. forskaolii is concentrated in the highlands and mid-highlands of the eastern and southern parts of Tigray, characterized by a colder temperature. Across the three climate change scenarios, the size of suitable habitat for H. forskaolii is projected to decrease over the four time periods studied. Predictions under the ssp585 scenario reveal alarming results, indicating a substantial decrease in the suitable habitat for H. forskaolii from 4.26% in the 2030s to 19.09% in the 2090s. Therefore, given the challenges posed by climate change, research efforts should focus on identifying and evaluating new technologies that can help the H. forskaolii species in adapting and mitigating the effects of climate change.

Negative impacts of future forest succession on three threatened butterfly species

AbstractThe dynamic interplay between anthropogenic activities and biodiversity conservation necessitates a nuanced understanding of habitat change, especially in contexts marked by transitions from grasslands to forested areas. This investigation utilised three threatened butterfly species—the Marsh Fritillary, Apollo, and Large Blue—as models to explore how grassland associated species respond to altered environmental conditions. The methodology encompassed extensive field surveys and statistical analyses with ecological niche modelling to determine their current and future distributions on the Island of Gotland. The species were surveyed under distinct years from 2017 to 2020 in a total of 3333 hectares in a 6000 hectare area—the Marsh Fritillary in 2017 (1232 hectares), Apollo in 2019 (2346 hectares), and Large Blue in 2020 (2256 hectares). Results revealed that the estimated current extents of suitable habitats were 49,104 hectares for the Marsh Fritillary (15.6% of the island), 45,646 hectares for Apollo (14.5%), and 33,089 hectares for Large Blue (10.5%). In general, increased forest and shrub cover and decreased heterogeneity negatively affected butterfly occupancy, but each species exhibited unique habitat preferences. The predictive modelling demonstrated that continued succession would reduce the amount of habitats predicted to be suitable and generated alarming forecasts—a twofold increase in forest and shrub cover suggests habitat declines of 41%, 47%, and 65% for the Marsh Fritillary, Apollo, and Large Blue, respectively. Given these findings, proactive measures are imperative for strategically managing these habitats to preserve landscape heterogeneity and accommodate diverse ecological needs. This study is important to conservation management providing, crucial insights amid anthropogenic and ecological changes.

Dual Synapses and Security Devices from Ternary C60‐Pentacene‐TiO2‐x Nanorods Heterostructures

AbstractIn the context of information explosion, neuromorphic and hardware‐based security devices have garnered significant attention for their capacity to facilitate parallel computing and not be vulnerable to hacking, respectively. A demonstration of a dual photosynaptic (DPS) and physically unclonable function (PUF) devices characterized by ternary TiO2‐x nanorods (NRs)/Pentacene/C60 heterostructure are simultaneously presented. For the DPS device, the ternary heterostructure leads to parallel‐operating DPS characteristics: i) wavelength‐dependent (WD) synapse and ii) stimulus‐moment‐dependent (SMD) synapse. Each synaptic characteristic demonstrates a remarkable degree of plasticity, which signifies a smooth transition from short‐term potentiation (STP) to long‐term potentiation (LTP). Moreover, The face recognition assessments have unveiled recognition rates of 83.3% for 2 operational modes. Notably, the DPS device maintains stable performance on the business card, even after a rigorous 49‐day testing period and undergoing 1 000 bending cycles. Regarding the PUF device, the security keys with unique patterns are created due to random current distribution induced by placement‐dependent doping effects of SnO2 quantum dots (QDs). Moreover, near‐ideal inter‐hamming distances (inter‐HDs), uniformities, and entropies are verified for all cryptographic keys. These findings introduce a pioneering concept of photonic synapses with their successful integration onto various substrates, including the hardware‐based security PUF device.

Local Permeability of a Metasurface in the MHz and GHz Ranges

The work is dedicated to the study of the magnetic response of a metasurface made of split ring resonators (meta-atoms) in the MHz and GHz ranges. A new method for calculating the local permeability of a metasurface in the MHz frequency range is proposed, taking into account the finite sizes of the elements, and for the first time, a result of high degree of accuracy matching with experimental values has been obtained. In the GHz range, additional factors such as the retardation effect, non-uniform current distribution in the meta-atom, and the complexity of the nature of meta-atoms’ interaction compared to the MHz range are also considered, in particular, the emergence of electrical interaction between them.

Climate change and Arctic charr (Salvelinus alpinus) in North America: modelling possible changes in range with different climate scenarios and interspecific interactions

AbstractOne of the greatest challenges for researchers today is understanding climate-change impacts on fish populations, particularly in vulnerable and understudied ecosystems such as the Canadian Arctic. Among other impacts, northern fishes will undergo thermal stress as atmospheric and sea surface temperatures are projected to rise globally. Models that consider how both environmental factors such as temperature and potential species interactions will impact population extirpation and species’ range contraction can help project the future distribution of a species in the face of a warming climate. Here, we investigate the climate-change impacts of rising temperatures and the potential northward distributional shift of brook charr (Salvelinus fontinalis) on Arctic charr (Salvelinus alpinus), Canada’s northernmost freshwater fish species. Specifically, we used a logistic regression model to establish baseline relationships between the current distribution of Arctic charr and the variables, degree-days (a key climate variable), geographical location, and brook charr occurrence. We developed the model applying the expected changes in degree-days to 2050 (25–50% increase from the average of 1976–2005) and 2080 (50–100% increase) while incorporating the historical distribution of Arctic charr to estimate the change in Arctic charr distribution over that time. We found that growing degree-days, longitude, latitude, and brook charr occurrences correctly classified 93% of Arctic charr historical occurrences in Canada. We estimate that in a high-carbon scenario, where degree-days are expected to increase by 50 to 100%, Arctic charr range is projected to decrease by 18% in Canada by 2051–2080 and decrease even further by 3% with the presence of brook charr. The Canadian high Arctic may provide refuge for Arctic charr, likely maintaining temperatures optimal for species persistence. Regardless, management that considers the climate stresses on Arctic charr populations will be important to preserve this highly valued resource that is pivotal for food security and traditional ways of life for northerners.

Bonded Interface Enabled Durable Solid‐state Lithium Metal Batteries with Ultra‐low Interfacial Resistance of 0.25 Ω cm2

AbstractThe solid‐state batteries (SSBs) with Li anode present one of the most promising energy storage systems due to their enhanced energy density and safety. However, interfacial problems between Li anode and solid‐state electrolyte hinder the advancement of SSBs. Among them, insufficient solid‐solid interfacial contact is the main issue, which causes large resistance and hinders Li+ diffusion, leading to current distribution unevenness and lithium dendrites growth. To meet these challenges, a silver/carbon interlayer composed of ultrafine Ag nanoparticles (≈5 nm) grown on COOH‐CNTs (nano‐Ag@COOH‐CNTs) is constructed. In which, nano‐Ag is designed to guide homogeneous Li deposition, while CNTs substrate bonds with Li6.5La3Zr1.5Ta0.5O12 (LLZTO) electrolyte by reactions between ─COOH groups and LLZTO alkaline surface, thus transforming loose physical solid‐solid contact to chemical bonding contact. In addition, nano‐Ag is immobilized by CNTs, avoiding the migration of Li+ implanted nano‐Ag during cycling. Therefore, nano‐Ag@COOH‐CNTs interlayer can boost Li+ transport at LLZTO/Li interface and inhibit Li dendrites, achieving an ultra‐low interfacial resistance of 0.25 Ω cm2, a high critical current density of 1.7 mA cm−2 and a long cycling over 2155 h at 0.5 mA cm−2. The modified SSBs with LiNi0.83Co0.12Mn0.05O2 cathode cycles stably over 500 cycles. Moreover, high‐loading SSBs operate stably for 85 cycles.

Climate change and Arctic charr (Salvelinus alpinus) in North America: modelling possible changes in range with different climate scenarios and interspecific interactions

AbstractOne of the greatest challenges for researchers today is understanding climate-change impacts on fish populations, particularly in vulnerable and understudied ecosystems such as the Canadian Arctic. Among other impacts, northern fishes will undergo thermal stress as atmospheric and sea surface temperatures are projected to rise globally. Models that consider how both environmental factors such as temperature and potential species interactions will impact population extirpation and species’ range contraction can help project the future distribution of a species in the face of a warming climate. Here, we investigate the climate-change impacts of rising temperatures and the potential northward distributional shift of brook charr (Salvelinus fontinalis) on Arctic charr (Salvelinus alpinus), Canada’s northernmost freshwater fish species. Specifically, we used a logistic regression model to establish baseline relationships between the current distribution of Arctic charr and the variables, degree-days (a key climate variable), geographical location, and brook charr occurrence. We developed the model applying the expected changes in degree-days to 2050 (25–50% increase from the average of 1976–2005) and 2080 (50–100% increase) while incorporating the historical distribution of Arctic charr to estimate the change in Arctic charr distribution over that time. We found that growing degree-days, longitude, latitude, and brook charr occurrences correctly classified 93% of Arctic charr historical occurrences in Canada. We estimate that in a high-carbon scenario, where degree-days are expected to increase by 50 to 100%, Arctic charr range is projected to decrease by 18% in Canada by 2051–2080 and decrease even further by 3% with the presence of brook charr. The Canadian high Arctic may provide refuge for Arctic charr, likely maintaining temperatures optimal for species persistence. Regardless, management that considers the climate stresses on Arctic charr populations will be important to preserve this highly valued resource that is pivotal for food security and traditional ways of life for northerners.

The current knowledge about the distribution of Portulaca species (Portulacaceae) within the Balkan Peninsula

AbstractThis study addresses the complex taxonomy and distribution of the genus Portulaca L. (Portulacaceae) within the Balkans, focusing on the often-debated species composition and distribution patterns in the P. oleracea aggregate. Our research aims to resolve this ambiguity by addressing two key questions: 1) Which Portulaca taxa are present in the Balkans, and 2) What is the current distribution of these taxa here? To achieve this, we conducted literature reviews, seed collection, species identification using micromorphological characteristics, and distribution analysis. Our findings reveal the presence of four distinct species in the Balkans: P. oleracea agg., P. grandiflora, P. pilosa and P. umbraticola. Additionally, within the P. oleracea complex, twelve microspecies have been identified, primarily differentiated based on seed micromorphology. Besides, five species (P. daninii, P. granulato-stellulata, P. rausii, P. sardoa, and P. trituberculata) have been documented in Montenegro, and one species (P. nitida) – in Slovenia for the first time. This study provides a valuable contribution to the botanical knowledge of the Balkan Peninsula, offering the recommendations for future studies of the P. oleracea complex for the solution of the taxonomic puzzle in this aggregate.

Polymer bead size revealed via neural network analysis of single-entity electrochemical data.

Single-entity electrochemistry methods for detecting polymer microbeads offer a promising approach to analyzing microplastics. However, conventional methods for determining microparticle size face challenges due to non-uniform current distribution across the surface of a sensing disk microelectrode. In this study, we demonstrate the utility of neural network (NN) analysis for extracting the size information from single-entity electrochemical data (current steps). We developed fully connected regression NN models capable of predicting microparticle radii based on experimental parameters and current-time data. Once trained, the models provide near-real-time predictions with good accuracy for microparticles of the same size, as well as the average size of two different-sized microparticles in solution. Potential future applications include analyzing various bioparticles, such as viruses and bacteria of different sizes and shapes.

The current knowledge about the distribution of Portulaca species (Portulacaceae) within the Balkan Peninsula

AbstractThis study addresses the complex taxonomy and distribution of the genus Portulaca L. (Portulacaceae) within the Balkans, focusing on the often-debated species composition and distribution patterns in the P. oleracea aggregate. Our research aims to resolve this ambiguity by addressing two key questions: 1) Which Portulaca taxa are present in the Balkans, and 2) What is the current distribution of these taxa here? To achieve this, we conducted literature reviews, seed collection, species identification using micromorphological characteristics, and distribution analysis. Our findings reveal the presence of four distinct species in the Balkans: P. oleracea agg., P. grandiflora, P. pilosa and P. umbraticola. Additionally, within the P. oleracea complex, twelve microspecies have been identified, primarily differentiated based on seed micromorphology. Besides, five species (P. daninii, P. granulato-stellulata, P. rausii, P. sardoa, and P. trituberculata) have been documented in Montenegro, and one species (P. nitida) – in Slovenia for the first time. This study provides a valuable contribution to the botanical knowledge of the Balkan Peninsula, offering the recommendations for future studies of the P. oleracea complex for the solution of the taxonomic puzzle in this aggregate.

Polymer bead size revealed via neural network analysis of single-entity electrochemical data.

Single-entity electrochemistry methods for detecting polymer microbeads offer a promising approach to analyzing microplastics. However, conventional methods for determining microparticle size face challenges due to non-uniform current distribution across the surface of a sensing disk microelectrode. In this study, we demonstrate the utility of neural network (NN) analysis for extracting the size information from single-entity electrochemical data (current steps). We developed fully connected regression NN models capable of predicting microparticle radii based on experimental parameters and current-time data. Once trained, the models provide near-real-time predictions with good accuracy for microparticles of the same size, as well as the average size of two different-sized microparticles in solution. Potential future applications include analyzing various bioparticles, such as viruses and bacteria of different sizes and shapes.

A Wideband Polarization Diversified MIMO Antenna with Improved Isolation using Machine Learning Optimized Metasurface Absorber

Abstract This communication presents a model and optimization of a dual-sense circularly polarized (RHCP/LHCP) 2-port MIMO antenna with increased isolation. The antenna operates in a broad frequency range of 1.76 – 4.0 GHz and is loaded with a metasurface. It has dimensions of 98.5 × 39 mm2 and an edge-to-edge distance of 55.5 mm. The MIMO antenna is created by replicating a single unit and placing it in a mirrored configuration around the y-axis. The dimensions of the unit antenna are 40 × 39 × 0.8 mm3 and it is printed on a substrate made of FR4 with a thickness of 0.8 mm. The substrate has a relative permittivity (εr) of 4.4 and a loss tangent (tanδ) of 0.02. The isolation between the ports may be enhanced by including a metasurface absorber, increasing from 12 dB to 23 dB. To verify the wideband and CP properties, we examine the MIMO antenna unit element for its reflection coefficient, peak gain (4.2 dB), radiation efficiency (about 90%), axial ratio, and surface current distribution. Machine learning is used to improve the design of metasurface unit cells to achieve optimum absorption. The Envelope correlation coefficient (ECC), Diversity gain (DG), and Channel capacity loss (CCL) of the proposed metasurface absorber-enabled antenna are simulated and calculated to prove its MIMO identity. The HFSS simulations are consistent with the experimental results obtained from the developed model.

A mixed finite element spatial discretization scheme and a higher‐order accurate temporal discretization scheme for a strongly discontinuous electromagnetic interface condition in ideal sliding electrical contact problems

AbstractSliding electrical contact involves multiple conductors sliding in contact at different speeds, with current flowing through the contact surfaces. The Lagrangian method is commonly used to describe the electromagnetic field in order to overcome the trouble of convective dominance, especially in high‐speed sliding electrical contact problems. However, to maintain correct field continuity, magnetic vector potential and scalar potential taken as variables cannot be continuous simultaneously at the ideal sliding electrical contact interface. This involves a strongly discontinuous condition for variables. Further, commonly used spatial–temporal discretization algorithms are invalid, for example, the classic finite element (CFEM) framework does not allow discontinuous variables, and the backward Euler method in time domain introduces a significant interface error source associated with the velocity of relative motion. To accurately handle strongly discontinuous conditions in numerical calculations, a mixed nodal finite element scheme and a higher‐order accurate temporal discretization scheme are introduced. In this scheme, classical finite element method is performed in each subdomain, and the derivative terms at the boundary are added as new variables. The effectiveness and accuracy of the above methods are verified by comparing them with a standard solution in a two‐dimensional railgun model and analyzing the current density distribution in a three‐dimensional railgun model.

Assessment of the influence of levees along Yangtze River on Oncomelania hupensis, the intermediate host of Schistosoma japonicum

BackgroundOncomelania hupensis is the exclusive intermediate host of Schistosoma japonicum in China. Snail control is an essential component of schistosomiasis elimination programme. With 70 years of continuous efforts, the range of O. hupensis had reduced significantly, but slowed down in last decades. A large number of levees against flooding were constructed along Yangtze River and its affiliated lakes in the middle and lower reaches, which influenced the hydrology and ecology in the alluvial plains. The purpose of this study was to assess the impact of levees on the distribution of O. hupensis in the middle and lower reaches of the Yangtze River.MethodsThe snail habitats were digitalised by hand-held GPS system. The years for discovery and elimination of snail habitats were extracted from historical records. The accumulated snail-infested range for each habitat was calculated on the basis of annual reports. The current distribution of O. hupensis was determined by systematic and environmental sampling. The geographical distribution of levees was obtained from satellite imagery. To assess the impact of levees, the data pertaining to O. hupensis were divided into two parts: inside and outside the Yangtze River. Joinpoint regression was utilised to divide the study time span and further characterise the regression in each period. The 5-year-period moving averages of eliminated area infested by snails were calculated for the habitats inside and outside Yangtze River. The moving routes of corresponding geographical median centres were simulated in ArcGIS. Hotspot analysis was used to determine the areas with statistical significance clustering of O. hupensis density.ResultsThree periods were identified according to Joinpoint regression both inside and outside Yangtze River. The area infested by O. hupensis increased in the first two periods. It decreased rapidly outside Yangtze River year over year after 1970, while that inside the Yangtze River did not change significantly. Furthermore, the latter was significantly higher than the former. It was observed that the present density of O. hupensis inside Yangtze River was lower than outside the Yangtze River. The median centre for eliminated ranges inside Yangtze River wavered between the east (lower reach) and the west (middle reach). In contrast, the median centre for eliminated ranges continuously moved from the east to the west.ConclusionsOur findings indicated that the levees had a considerable negative impact on the distribution of O. hupensis outside Yangtze River. Some hotspots observed in the irrigation areas need a sluice system at the inlet of branch for snail control. The major distribution of O. hupensis located in Hubei might be caused by severe waterlogging. The intensive surveillance should be implemented there. The biggest two freshwater lakes, the major endemic regions historically, were identified as cold spots. The long-term impact of Three Gorges Dam on the distribution of O. hupensis in the lakes should be monitored and evaluated.Graphical

High performance and compact antenna with new scheme for broadband circular polarisation applications

ABSTRACT In this research paper, the authors propose a unique broad-band circularly polarised antenna design with a sequentially rotated feed network intended for applications in the WiMAX IEEE 802.16, C-band, and ITU-R F386.9 bands. A sequential feeding approach utilising transmission lines with varying impedance properties and lengths has been utilised to properly stimulate the amplitude and phase distribution of each radiation element. To facilitate the rotation of the surface current distribution on the ground plane and further improve impedance matching, four L-shaped slits have been inserted into each corner of the ground plane along with a pair of mirrored slits of identical geometry within the antenna ground plane. The individual antenna element achieves an impedance bandwidth between 5–6.8 GHz and a 3 dB axial ratio bandwidth from 5.1–6.6 GHz. To additionally advance the radiation performance, the elements are configured into a 2 × 2 antenna and are interconnected utilising a sequentially rotated feeding network to attain broader axial ratio and impedance bandwidths. A key benefit of the implemented feed network is the minimisation of coupling effects between elements. To significantly increase the performance metrics of the antenna with limited increase to its physical size, electromagnetic band gap structures were incorporated as a one-dimensional lattice between the radiating elements. For the resulting antenna, an axial ratio bandwidth from 4.19 to 6.8 GHz (48%) and an impedance bandwidth spanning 2.9 to 9.8 GHz (102%) are achieved. The peak gain of the antenna is 11.2 dBic.

Evaluation of the backflashover performance of 150 kV and 400 kV double-circuit overhead transmission lines as affected by lightning attachment models and peak current distributions

The evaluation of the backflashover performance of overhead transmission lines requires the adoption of a lightning attachment model and a peak current distribution. These affect the estimated backflashover rate, BFR, of the lines. The present study aims to quantify the influence of lightning attachment model and peak current distribution on the BFR of double-circuit overhead lines. This is achieved by evaluating typical 150 kV and 400 kV lines. ATP-EMTP simulations are conducted to obtain the critical currents causing backflashover of line insulation. Then, the critical currents are used in lightning incidence computations to obtain BFR. The influencing parameters taken into account in this work are the low current and low frequency tower ground resistance, the location of lightning strike to the shield wire along the span, and the AC voltage phase angle, all affecting the critical backflashover current. Several lightning attachment models and peak current distributions are evaluated. Their influence on BFR is found to be considerable, especially for lower tower ground resistance values. The lightning peak current distributions yield more pronounced effects on BFR. The results of this study stress the need for computing BFR using a more accurate expression than the simplified one based on CIGRE TB 63.

A semi-cellular Z-type Gate SOI-LDMOS with Improved Gate Control Capability

A Semi-cellular Z-type Gate SOI-LDMOS (ZG LDMOS) with Improved Gate Control Capability is proposed, and its physical mechanism is studied by SENTAURUS. It is a semi-cellular structure similar to "Z" consisting of a Trench Gate (TG) and a Planar Gate (PG). At the on-state, the inversion layer of the conductive channel is not only formed at the top of the P-well region, but also formed along the side wall of the Z Gate, expanding the width of the channel, improving the electron injection ability and reducing the specific on-resistance (Ron,sp). In addition, the Z Gate can also form a uniform current distribution from the drift region to the bottom, which is helpful to reduce the Ron,sp, improve the transconductance and enhance the current control ability. The 3D simulation results show that BV, Ron,sp are 187.3 V and 4.45 mΩ cm2, respectively. The FOM reached 7.91 MW/cm2. Compared with the conventional LDMOS, the FOM value of ZG LDMOS increased by 58.8 %, which breaks through the silicon limit of RESURF.

Broadband absorptive metamaterials enhanced by magnetic rubber to broaden bandwidth

A method to extend the operational bandwidth of metal-dielectric-metal (MDM) type absorptive metamaterials is proposed. An ultrathin, five-band absorptive metamaterial with wide-angle absorption and polarization sensitivity in the X-band is designed. The total absorption bandwidth across the five bands, with reflection losses below −10 dB (absorption rate greater than 90 %), is nearly 1 GHz. The physical mechanisms of absorption are analyzed through the distributions of surface current, electric field, and magnetic field. Samples were fabricated and tested, and the results were consistent with the simulation outcomes. To enhance the bandwidth of the absorptive metamaterial and its application prospects, magnetic materials such as barium ferrite and carbonyl iron were introduced into a rubber vulcanization layer, which was then combined with the ultrathin absorptive material to create a novel absorptive material. When the magnetic material content in the rubber layer was 50 wt%, the frequency range with reflection losses below −10 dB increased by approximately nine times, covering 69.5 % of the C-Ku band. This significantly broadens the bandwidth of the pure MDM-type absorptive metamaterial, providing a feasible solution for the design of broadband ultrathin absorptive materials.