Stratum corneum lipid and cytokine biomarkers at age 2 months predict the future onset of atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) commonly occurs in children and can progress into severe phenotypes or atopic march, causing significant impairment in quality of life. It is important to find early biomarkers of future onset of AD before any clinical manifestations. OBJECTIVE: We sought to find early predictors of future onset of AD in skin stratum corneum (SC). METHODS: Skin tape strips were collected from the forearm of newborns (n = 111) with and without family history of atopic diseases at the age of 2 months before any signs of clinical AD. Children were clinically monitored until they reached age 2 years to ensure the presence or absence of AD. Skin tape strips were subjected to lipidomic analyses by the liquid chromatography electrospray ionization tandem mass spectrometry and cytokine determination by Meso Scale Discovery U-Plex assay. RESULTS: Overall, 22 of 74 (29.7%) and 5 of 37 (13.5%) infants developed AD in the risk group and the control group, respectively. In the SC of future AD children, protein-bound ceramides were decreased (P < .001), whereas unsaturated sphingomyelin species (P < .0001) and "short-chain" nonhydroxy fatty acid sphingosine and alpha-hydroxy fatty acid sphingosine ceramides were elevated (P < .01 and .05, respectively) as compared with healthy children. Thymic stromal lymphopoietin and IL-13 levels were increased in the SC of future AD subjects (by 74.5% and 78.3%, P = .0022 and P < .0001, respectively). Multivariable logistic regression analysis revealed strong AD predicting power of the combination of family history, type 2 cytokines, and dysregulated lipids, with an odds ratio reaching 54.0 (95% CI, 9.2-317.5). CONCLUSIONS: Noninvasive skin tape strip analysis at age 2 months can identify asymptomatic children at risk of future AD development with a high probability.

Novel Dithienopyrrole-Based Conjugated Copolymers: Importance of Backbone Planarity in Achieving High Electrical Conductivity and Thermoelectric Performance.

The development of conjugated polymers with structures that are suitable for efficient molecular doping and charge transport is a key challenge in the construction of high-performance conjugated polymer-based thermoelectric devices. In this study, three novel conjugated polymers based on dithienopyrrole (DTP) are synthesized and their thermoelectric properties are compared. When doped with p-dopant, a donor-acceptor type copolymer, DPP-MeDTP, exhibits higher electrical conductivity and thermoelectric power factor compared to the other donor-donor type copolymers. The high electrical conductivity of DPP-MeDTP compared to the other polymers originates from the high degree of backbone planarity and molecular order, which contributes to its high charge carrier mobility. In addition, the highly crystalline structure of DPP-MeDTP is well maintained upon doping, while the crystalline order of the other polymers decreases significantly upon doping. The findings of this work not only provide insights into the design of DTP-based conjugated polymers for thermoelectric use but also demonstrate the significance of a high degree of molecular order and structural robustness upon doping to achieve high thermoelectric performance.

Two-Dimensional MXene Synapse for Brain-Inspired Neuromorphic Computing.

MXenes, an emerging class of two-dimensional (2D) transition metal carbides and nitrides, have attracted wide attention because of their fascinating properties required in functional electronics. Here, an atomic-switch-type artificial synapse fabricated on Ti3 C2 Tx MXene nanosheets with lots of surface functional groups, which successfully mimics the dynamics of biological synapses, is reported. Through in-depth analysis by X-ray photoelectron spectroscopy, transmission electron microscopy, and energy dispersive X-ray spectroscopy, it is found that the synaptic dynamics originated from the gradual formation and annihilation of the conductive metallic filaments on the MXene surface with distributed functional groups. Subsequently, via training and inference tasks using a convolutional neural network for the Canadian-Institute-For-Advanced-Research-10 dataset, the applicability of the artificial MXene synapse to hardware neural networks is demonstrated.

Avalanche Carrier Multiplication in Multilayer Black Phosphorus and Avalanche Photodetector.

A highly sensitive avalanche photodetector (APD) is fabricated by utilizing the avalanche multiplication mechanism in black phosphorus (BP), where a strong avalanche multiplication of electron-hole pairs is observed. Owing to the small bandgap (0.33 eV) of the multilayer BP, the carrier multiplication occurs at a significantly lower electric field than those of other 2D semiconductor materials. In order to further enhance the quantum efficiency and increase the signal-to-noise (S/N) ratio, Au nanoparticles (NPs) are integrated on the BP surface, which improves the light absorption by plasmonic effects. The BP-Au-NPs structure effectively reduces both dark current (≈10 times lower) and onset of avalanche electric field, leading to higher carrier multiplication, photogain, quantum efficiency, and S/N ratio. For the BP-Au-NPs APD, it is obtained that the external quantum efficiency (EQE) is 382 and the responsivity is 160 A W-1 at an electric field of 5 kV cm-1 (Vd ≈ 3.5 V, note that for the BP APD, EQE = 4.77 and responsivity = 2 A W-1 obtained at the same electric field). The significantly increased performance of the BP APD is promising for low-power-consumption, high-sensitivity, and low-noise photodevice applications, which can enable high-performance optical communication and imaging systems.

Generalized Scheme for High Performing Photodetectors with a p-Type 2D Channel Layer and n-Type Nanoparticles.

A generalized scheme for the fabrication of high performance photodetectors consisting of a p-type channel material and n-type nanoparticles is proposed. The high performance of the proposed hybrid photodetector is achieved through enhanced photoabsorption and the photocurrent gain arising from its effective charge transfer mechanism. In this paper, the realization of this design is presented in a hybrid photodetector consisting of 2D p-type black phosphorus (BP) and n-type molybdenum disulfide nanoparticles (MoS2 NPs), and it is demonstrated that it exhibits enhanced photoresponsivity and detectivity compared to pristine BP photodetectors. It is found that the performance of hybrid photodetector depends on the density of NPs on BP layer and that the response time can be reduced with increasing density of MoS2 NPs. The rising and falling times of this photodetector are smaller than those of BP photodetectors without NPs. This proposed scheme is expected to work equally well for a photodetector with an n-type channel material and p-type nanoparticles.

Defect-selective dry etching for quick and easy probing of hexagonal boron nitride domains.

In this study, we demonstrate a new method to selectively etch the point defects or the boundaries of as-grown hexagonal boron nitride (hBN) films and flakes in situ on copper substrates using hydrogen and argon gases. The initial quality of the chemical vapor deposition-grown hBN films and flakes was confirmed by UV-vis absorption spectroscopy, atomic force microscopy, and transmission electron microscopy. Different gas flow ratios of Ar/H2 were then employed to etch the same quality of samples and it was found that etching with hydrogen starts from the point defects and grows epitaxially, which helps in confirming crystalline orientations. However, etching with argon is sensitive to line defects (boundaries) and helps in visualizing the domain size. Finally, based on this defect-selective dry etching technique, it could be visualized that the domains of a polycrystalline hBN monolayer merged together with many parts, even with those that grew from a single nucleation seed.

Ferroelectric Stochasticity in 2D CuInP2S6 and Its Application for True Random Number Generator.

True random number generators (TRNGs), which create cryptographically secure random bitstreams, hold great promise in addressing security concerns regarding hardware, communication, and authentication in the Internet of Things (IoT) realm. Recently, TRNGs based on nanoscale materials have gained considerable attention for avoiding conventional and predictable hardware circuitry designs that can be vulnerable to machine learning (ML) attacks. In this article, a low-power and low-cost TRNG developed by exploiting stochastic ferroelectric polarization switching in 2D ferroelectric CuInP2S6 (CIPS)-based capacitive structures, is reported. The stochasticity arises from the probabilistic switching of independent electrical dipoles. The TRNG exhibits enhanced stochastic variability with near-ideal entropy, uniformity, uniqueness, Hamming distance, and independence from autocorrelation variations. Its unclonability is systematically examined using device-to-device variations. The generated cryptographic bitstreams pass the National Institute of Standards and Technology (NIST) randomness tests. This nanoscale CIPS-based TRNG is circuit-integrable and exhibits potential for hardware security in edge devices with advanced data encryption.

Spiking Neural Network Integrated with Impact Ionization Field-Effect Transistor Neuron and a Ferroelectric Field-Effect Transistor Synapse.

The integration of artificial spiking neurons based on steep-switching logic devices and artificial synapses with neuromorphic functions enables an energy-efficient computer architecture that mimics the human brain well, known as a spiking neural network (SNN). 2D materials with impact ionization or ferroelectric characteristics have the potential for use in such devices. However, research on 2D spiking neurons remains limited and investigations of 2D artificial synapses far more common. An innovative 2D spiking neuron is implemented using a WSe2 impact ionization transistor (I2FET), while a spiking neural network is formed by combining it with a 2D ferroelectric synaptic device (FeFET). The suggested 2D spiking neuron demonstrates precise spiking behavior that closely resembles that of actual neurons. In addition, it achieves a low energy consumption of 2 pJ/spike. The better impact ionization properties of WSe2 are responsible for this efficiency. Furthermore, an all-2D SNN consisting of 2D I2FET neurons and 2D FeFET synapses is constructed, which achieves high accuracy of 87.5% in a face classification task by unsupervised learning. The integration of a 2D SNN with 2D steep-switching spiking neuronal devices and 2D synaptic devices shows great potential for the development of neuromorphic systems with improved energy efficiency and computational capabilities.

AI-assisted Analysis to Facilitate Detection of Humeral Lesions on Chest Radiographs.

Purpose To develop an artificial intelligence (AI) system for humeral tumor detection on chest radiographs (CRs) and evaluate the impact on reader performance. Materials and Methods In this retrospective study, 14 709 CRs (January 2000 to December 2021) were collected from 13 468 patients, including CT-proven normal (n = 13 116) and humeral tumor (n = 1593) cases. The data were divided into training and test groups. A novel training method called false-positive activation area reduction (FPAR) was introduced to enhance the diagnostic performance by focusing on the humeral region. The AI program and 10 radiologists were assessed using holdout test set 1, wherein the radiologists were tested twice (with and without AI test results). The performance of the AI system was evaluated using holdout test set 2, comprising 10 497 normal images. Receiver operating characteristic analyses were conducted for evaluating model performance. Results FPAR application in the AI program improved its performance compared with a conventional model based on the area under the receiver operating characteristic curve (0.87 vs 0.82, P = .04). The proposed AI system also demonstrated improved tumor localization accuracy (80% vs 57%, P < .001). In holdout test set 2, the proposed AI system exhibited a false-positive rate of 2%. AI assistance improved the radiologists' sensitivity, specificity, and accuracy by 8.9%, 1.2%, and 3.5%, respectively (P < .05 for all). Conclusion The proposed AI tool incorporating FPAR improved humeral tumor detection on CRs and reduced false-positive results in tumor visualization. It may serve as a supportive diagnostic tool to alert radiologists about humeral abnormalities. Keywords: Artificial Intelligence, Conventional Radiography, Humerus, Machine Learning, Shoulder, Tumor Supplemental material is available for this article. © RSNA, 2024.

One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System.

The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, this work presents a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step is achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) channels are successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and are directly used as electrochemical synaptic transistor with synaptic plasticity over 100 s. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor is easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density.

High-κ Dielectric (HfO2)/2D Semiconductor (HfSe2) Gate Stack for Low-Power Steep-Switching Computing Devices.

Herein, a high-quality gate stack (native HfO2 formed on 2D HfSe2) fabricated via plasma oxidation is reported, realizing an atomically sharp interface with a suppressed interface trap density (Dit ≈ 5 × 1010 cm-2 eV-1). The chemically converted HfO2 exhibits dielectric constant, κ ≈ 23, resulting in low gate leakage current (≈10-3 A cm-2) at equivalent oxide thickness ≈0.5 nm. Density functional calculations indicate that the atomistic mechanism for achieving a high-quality interface is the possibility of O atoms replacing the Se atoms of the interfacial HfSe2 layer without a substitution energy barrier, allowing layer-by-layer oxidation to proceed. The field-effect-transistor-fabricated HfO2/HfSe2 gate stack demonstrates an almost ideal subthreshold slope (SS) of ≈61 mV dec-1 (over four orders of IDS) at room temperature (300 K), along with a high Ion/Ioff ratio of ≈108 and a small hysteresis of ≈10 mV. Furthermore, by utilizing a device architecture with separately controlled HfO2/HfSe2 gate stack and channel structures, an impact ionization field-effect transistor is fabricated that exhibits n-type steep-switching characteristics with a SS value of 3.43 mV dec-1 at room temperature, overcoming the Boltzmann limit. These results provide a significant step toward the realization of post-Si semiconducting devices for future energy-efficient data-centric computing electronics.

Association of Glycemic Variability With Imaging Markers of Vascular Burden, ß-Amyloid, Brain Atrophy, and Cognitive Impairment.

BACKGROUND AND OBJECTIVE: We aimed to investigate the association between glycemic variability (GV) and neuroimaging markers of white matter hyperintensities (WMH), beta-amyloid (Aß), brain atrophy, and cognitive impairment. METHODS: This was a retrospective cohort study that included participants without dementia from a memory clinic. They all had Aß PET, brain MRI, and standardized neuropsychological tests and had fasting glucose (FG) levels tested more than twice during the study period. We defined GV as the intraindividual visit-to-visit variability in FG levels. Multivariable linear regression and logistic regression were used to identify whether GV was associated with the presence of severe WMH and Aß uptake with DM, mean FG levels, age, sex, hypertension, and presence of APOE4 allele as covariates. Mediation analyses were used to investigate the mediating effect of WMH and Aß uptake on the relationship between GV and brain atrophy and cognition. RESULTS: Among the 688 participants, the mean age was 72.2 years, and the proportion of female participants was 51.9%. Increase in GV was predictive of the presence of severe WMH (coefficient [95% CI] 1.032 [1.012-1.054]; p = 0.002) and increased Aß uptake (1.005 [1.001-1.008]; p = 0.007). Both WMH and increased Aß uptake partially mediated the relationship between GV and frontal-executive dysfunction (GV → WMH → frontal-executive; direct effect, -0.319 [-0.557 to -0.080]; indirect effect, -0.050 [-0.091 to -0.008]) and memory dysfunction (GV → Aß â†’ memory; direct effect, -0.182 [-0.338 to -0.026]; indirect effect, -0.067 [-0.119 to -0.015]), respectively. In addition, increased Aß uptake completely mediated the relationship between GV and hippocampal volume (indirect effect, -1.091 [-2.078 to -0.103]) and partially mediated the relationship between GV and parietal thickness (direct effect, -0.00101 [-0.00185 to -0.00016]; indirect effect, -0.00016 [-0.00032 to -0.000002]). DISCUSSION: Our findings suggest that increased GV is related to vascular and Alzheimer risk factors and neurodegenerative markers, which in turn leads to subsequent cognitive impairment. Furthermore, GV can be considered a potentially modifiable risk factor for dementia prevention.

Distinct effects of blood pressure parameters on Alzheimer's and vascular markers in 1,952 Asian individuals without dementia.

BACKGROUND: Risk factors for cardiovascular disease, including elevated blood pressure, are known to increase risk of Alzheimer's disease. There has been increasing awareness of the relationship between long-term blood pressure (BP) patterns and their effects on the brain. We aimed to investigate the association of repeated BP measurements with Alzheimer's and vascular disease markers. METHODS: We recruited 1,952 participants without dementia between August 2015 and February 2022. During serial clinic visits, we assessed both systolic BP (SBP) and diastolic BP (DBP), and visit-to-visit BP variability (BPV) was quantified from repeated measurements. In order to investigate the relationship of mean SBP (or DBP) with Alzheimer's and vascular markers and cognition, we performed multiple linear and logistic regression analyses after controlling for potential confounders (Model 1). Next, we investigated the relationship of with variation of SBP (or DBP) with the aforementioned variables by adding it into Model 1 (Model 2). In addition, mediation analyses were conducted to determine mediation effects of Alzheimer's and vascular makers on the relationship between BP parameters and cognitive impairment. RESULTS: High Aß uptake was associated with greater mean SBP (ß = 1.049, 95% confidence interval 1.016-1.083). High vascular burden was positively associated with mean SBP (odds ratio = 1.293, 95% CI 1.015-1.647) and mean DBP (1.390, 1.098-1.757). High tau uptake was related to greater systolic BPV (0.094, 0.001-0.187) and diastolic BPV (0.096, 0.007-0.184). High Aß uptake partially mediated the relationship between mean SBP and the Mini-Mental State Examination (MMSE) scores. Hippocampal atrophy mediated the relationship between diastolic BPV and MMSE scores. CONCLUSIONS: Each BP parameter affects Alzheimer's and vascular disease markers differently, which in turn leads to cognitive impairment. Therefore, it is necessary to appropriately control specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairments might enable us to select the managements targeting the specific BP parameters to prevent dementia effectively.

Artificial Visual Systems Fabricated with Ferroelectric van der Waals Heterostructure for In-Memory Computing Applications.

Rapid developments in artificial neural network techniques and retina-inspired artificial visual systems are required to realize the sensing, processing, and memorization of an optical signal in a single device. Herein, a ferroelectric field-effect transistor fabricated with CuInP2S6 and α-In2Se3 van der Waals heterostructures is proposed and demonstrated for the development of an artificial visual system. The dipole polarizations are coupled and bidirectionally locked inside the ferroelectric α-In2Se3 along the in-plane and out-of-plane directions and are controlled by the gate voltages. Furthermore, light-induced polarization can change the order of polarization of the dipoles inside α-In2Se3. We demonstrate that using the combined control of these electrical and optical signals, the device may function like a retina-inspired vision system. The device can operate across a wide wavelength range (405-850 nm) and detect very low incident light (0.03 mW/cm2). Color recognition, high paired-pulse facilitation (∼170%), and short- to long-term memory transitions through quick learning are observed using this device. Additionally, this device demonstrates different complex processing abilities, including pattern recognition, light adaptation, optical logic operation, and event learning. The proposed ferroelectric heterostructure-based artificial visual system can serve as an essential bridge for fulfilling the future requirements of all-in-one sensing and memory-processing devices.

Anisotropy of impact ionization in WSe2 field effect transistors.

Carrier multiplication via impact ionization in two-dimensional (2D) layered materials is a very promising process for manufacturing high-performance devices because the multiplication has been reported to overcome thermodynamic conversion limits. Given that 2D layered materials exhibit highly anisotropic transport properties, understanding the directionally-dependent multiplication process is necessary for device applications. In this study, the anisotropy of carrier multiplication in the 2D layered material, WSe2, is investigated. To study the multiplication anisotropy of WSe2, both lateral and vertical WSe2 field effect transistors (FETs) are fabricated and their electrical and transport properties are investigated. We find that the multiplication anisotropy is much bigger than the transport anisotropy, i.e., the critical electric field (ECR) for impact ionization of vertical WSe2 FETs is approximately ten times higher than that of lateral FETs. To understand the experimental results we calculate the average energy of the carriers in the proposed devices under strong electric fields by using the Monte Carlo simulation method. The calculated average energy is strongly dependent on the transport directions and we find that the critical electric field for impact ionization in vertical devices is approximately one order of magnitude larger than that of the lateral devices, consistent with experimental results. Our findings provide new strategies for the future development of low-power electric and photoelectric devices.

A steep-switching impact ionization-based threshold switching field-effect transistor.

A steep switching device with a low subthreshold swing (SS) that overcomes the fundamental Boltzmann limit (kT/q) is required to efficiently process a continuously increasing amount of data. Recently, two-dimensional material-based impact ionization transistors with various structures have been reported with the advantages of a low critical electric field and a unique quantum confinement effect. However, most of them cannot retain steep switching at room temperature, and device performance degradation issues caused by impact ionization-induced hot carriers have not been structurally addressed. In this study, we presented an impact-ionization-based threshold switching field-effect transistor (I2S-FET) fabricated with a serial connection of a MoS2 FET and WSe2 impact ionization-based threshold switch (I2S). We obtained repetitive operation with low SS (32.8 mV dec-1) at room temperature, along with low dielectric injection efficiency (10-6), through a structural design with separation of the conducting region, which determines on-state carrier transport, and the steep-switching region where the transition from off- to on-state occurs via impact ionization. Furthermore, compared to previously reported threshold-switching devices, our device demonstrated hysteresis-free switching characteristics. This study provides a promising approach for developing next-generation energy-efficient electronic devices and ultralow-power applications.

Age-associated mortality is partially mediated by TERT promoter mutation status in differentiated thyroid carcinoma.

BACKGROUND: Age at diagnosis (AAD) and telomerase reverse transcriptase (TERT) promoter mutations are prognostic factors in differentiated thyroid carcinoma (DTC), and the prevalence of the mutations increases with AAD. Considering this correlation, we investigated whether an interaction between AAD and the mutations is present and whether the mutation mediates the effect of AAD on the mortality rate in DTC. METHODS: The study included 393 patients with DTC who were followed-up after thyroidectomy at a single medical center in Korea from 1994 to 2004. Multivariable Cox regression was used to investigate the interaction of AAD and TERT promoter mutation. Mediation analysis was conducted using a regression-based causal mediation model. RESULTS: The age-associated mortality rate increased progressively in all DTC patients and wild-type TERT group (WT-TERT) with a linear trend (p < 0.001) contrary to mutant TERT group (M-TERT) (p = 0.301). Kaplan-Meier curves declined progressively with increasing AAD in the entire group, but the change was without significance in M-TERT. The effect of AAD on mortality was not significant (adjusted HR: 1.07, 95% CI 0.38-3.05) in M-TERT. An interaction between AAD and TERT promoter mutation (p = 0.005) was found in a multivariable Cox regression. TERT promoter mutations mediated the effect of AAD on the mortality rate by 36% in DTC in a mediation analysis. CONCLUSIONS: Considering the mediation of TERT promoter mutation on the effect of AAD on mortality, inclusion of TERT promoter mutation in a stage classification to achieve further individualized prediction in DTC is necessary.

Beneficiation of coal pond ash by physical separation techniques.

In this study, investigations to develop a beneficiation process for separating coal pond ash into various products were undertaken. To this end, coal pond ash samples with different particle size ranges were tested in terms of their washability characteristics in a float-and-sink analysis. It was found that coal pond ash was heterogeneous in nature consisting of particles that varied in terms of their size and composition. However, it can be made more homogenous using a gravity separation method. Therefore, the possibility of separating coal pond ash was tested on standard equipment typically used for gravity concentration. To increase the separation efficiency, coal ash was separated according to the size of the particles and each size fraction was tested using equipment appropriate for the corresponding sizes. A hindered-settling column and a shaking table were tested for their ability to treat the 1.19 × 0.074 mm size fraction, and a Falcon concentrator was evaluated for its ability to treat the -0.074 mm size fraction. The results showed that various marketable products, such as lightweight aggregate, sand and high-carbon fuel, can be recovered from coal pond ash using simple physical separation techniques.

Spatialization and Prediction of Seasonal NO2 Pollution Due to Climate Change in the Korean Capital Area through Land Use Regression Modeling.

Urbanization is causing an increase in air pollution leading to serious health issues. However, even though the necessity of its regulation is acknowledged, there are relatively few monitoring sites in the capital metropolitan city of the Republic of Korea. Furthermore, a significant relationship between air pollution and climate variables is expected, thus the prediction of air pollution under climate change should be carefully attended. This study aims to predict and spatialize present and future NO2 distribution by using existing monitoring sites to overcome deficiency in monitoring. Prediction was conducted through seasonal Land use regression modeling using variables correlated with NO2 concentration. Variables were selected through two correlation analyses and future pollution was predicted under HadGEM-AO RCP scenarios 4.5 and 8.5. Our results showed a relatively high NO2 concentration in winter in both present and future predictions, resulting from elevated use of fossil fuels in boilers, and also showed increments of NO2 pollution due to climate change. The results of this study could strengthen existing air pollution management strategies and mitigation measures for planning concerning future climate change, supporting proper management and control of air pollution.

Two-Dimensional CIPS-InSe van der Waal Heterostructure Ferroelectric Field Effect Transistor for Nonvolatile Memory Applications.

Channel current conduction modulation with the spontaneous polarization of ferroelectric films in ferroelectric field-effect transistors (FeFETs) has been widely investigated. Low interface quality and thermodynamic instability owing to the presence of dangling bonds in the conventional ferroelectrics have limited the memory retention and endurance of FeFETs. This, in turn, prevents their commercialization. However, the atomically thin nature of 2D ferroelectric, semiconducting, and insulating films facilitate the achievement of trap-free interfaces as van der Waal heterostructures (vdWHs) to develop FeFETs with long data retention and endurance characteristics. Here, we demonstrate a 2D vdWH FeFET fabricated with ferroelectric CuInP2S6 (CIPS), hexagonal boron nitride (h-BN) as the dielectric, and InSe as the ferroelectric semiconductor channel. The device shows an excellent performance as nonvolatile memory (NVM) with its large memory window (4.6 V at a voltage sweep of 5 V), high drain current on/off ratio (>104), high endurance, and long data retention (>104 s). These results demonstrate the considerable potential of vdWHs for the development of FeFETs for logic and NVM applications.