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Abstract A method for the characterization of organic electrochemical transistors (OECTs) based on small signal analysis is presented that allows to determine the electronic mobility as a function of continuous gate potential using a standard two-channel AC potentiostat. Vector analysis in the frequency domain allows to exclude parasitic components in both ionic and electronic conduction regardless of film thickness, thus resulting in a standard deviation as low as 4%. Besides the electronic mobility, small signal analysis of OECTs also provides information about a wide range of other parameters including the conductance, transconductance, conductivity and volumetric capacitance through a single measurement. General applicability of small signal analysis is demonstrated by characterizing devices based on n-type, p-type, and ambipolar materials operating in accumulation or depletion modes. Accurate benchmarking of organic mixed ionic-electronic conductors through small signal analysis can be anticipated to guide both materials development and the design of bioelectronic devices.

Abstract Quantum error correction offers a promising path for performing high fidelity quantum computations. Although fully fault-tolerant executions of algorithms remain unrealized, recent improvements in control electronics and quantum hardware enable increasingly advanced demonstrations of the necessary operations for error correction. Here, we perform quantum error correction on superconducting qubits connected in a heavy-hexagon lattice. We encode a logical qubit with distance three and perform several rounds of fault-tolerant syndrome measurements that allow for the correction of any single fault in the circuitry. Using real-time feedback, we reset syndrome and flag qubits conditionally after each syndrome extraction cycle. We report decoder dependent logical error, with average logical error per syndrome measurement in Z(X)-basis of ~0.040 (~0.088) and ~0.037 (~0.087) for matching and maximum likelihood decoders, respectively, on leakage post-selected data.

Anthropogenic nitrogen (N) inputs can have detrimental environmental effects, necessitating a comprehensive understanding of the nitrogen budget (NB) and its spatial correlation with the water quality. This study, utilizing a 2016 dataset, scrutinized 850 subwatersheds with diverse land covers across the Republic of Korea (ROK). Employing Geographically Weighted Regression (GWR), it examined the spatial correlations between the NBs and the quality of the groundwater and river water at the watershed scale. Robust correlations (R2 = 0.87) were observed between the groundwater quality and NBs, surpassing those of the surface water (R2 = 0.48). Sensitivity analyses highlighted the importance of high-resolution spatial data in capturing nuances within complex land covers. The integration of such data led to increases in the spatial correlations between the groundwater and river water quality of approximately 0.6–0.9 and 0.3–0.5, respectively. Notably, when the agricultural land cover exceeded 10%, significant enhancements in the spatial correlations were observed, emphasizing the pivotal role of agriculture in nutrient and water quality. At a 10% cropland ratio, the spatial correlations between the watershed-scale NBs and river/groundwater quality increased by approximately 76% and 501%, respectively. This study provides novel insights into the spatial relationships among NBs, water quality, and land use, highlighting the significance of high-resolution data and the impact of agricultural practices on watershed management. These findings contribute valuable information for developing strategies to mitigate nitrogen pollution.

ABSTRACTNatural products and their derivatives historically represent alternatives to conventional synthetic molecules for pharmacotherapy, ranging from cancer chemotherapeutics to cosmetic ingredients that exert anti-aging activities. Cellular senescence is considered a main driver of skin aging, yet natural products that target skin senescence in a specific manner are not thoroughly explored. Here, we performed a focused compound screen to identify natural products that exert anti-senescence effects. We found that Isatis tinctoria, woad extracts, displayed a senolytic effect on senescent human skin fibroblasts. Furthermore, treatment with woad extracts attenuated the expression of pro-inflammatory senescence-associated secretory phenotype (SASP), showing a senostatic activity. Intriguingly, woad extracts displayed only a marginal cytotoxic effect toward senescent human lung fibroblasts. Thus, our results reveal the potential activities of woad extracts for targeting skin senescence and suggest that woad extracts could be an attractive ingredient for cosmetics to prevent skin aging.

In this study, accelerated chloride diffusion tests are performed on ordinary Portland cement (OPC), ground granulated blast furnace slag (GGBFS), and fly ash (FA) concretes aged 4–6 years. Passed charge is evaluated according to ASTM-C-1202 for 12 mixtures, considering water–binder (W/B) ratios (0.37, 0.42, and 0.47), GGBFS replacement rates (0%, 30%, 50%), and FA replacement rates (0% and 30%). The effects of aged days on passed charge reduction behavior are quantified through repetitive regression analysis. Among existing machine learning (ML) models, linear, lasso, and ridge models are used to analyze the correlation of aged days and mix properties with passed charge. Passed charge analysis considering long-term age shows a significant variability decrease of passed charge by W/B ratio with increasing age and added admixtures (GGBFS and FA). Furthermore, the higher the water–binder ratio in GGBFS and FA concretes, the greater the decrease in passed charge due to aged days. The ML model-based regression analysis shows high correlation when compressive strength and independent variables are considered together. Future work includes a correlational analysis between mixture properties and chloride ingress durability performance using deep learning models based on the time series properties of evaluation data.

Amid the ongoing global warming crisis, there has been growing interest in hydrogen energy as an environmentally friendly energy source to achieve carbon neutrality. A stable and large-scale hydrogen storage infrastructure is essential to satisfy the increasing demand for hydrogen energy. Particularly for hydrogen refueling stations located in urban areas, technological solutions are required to ensure the stability of adjacent civil structures in the event of hydrogen storage tank explosions. In this study, a numerical analysis using equivalent trinitrotoluene (TNT) and Concrete Damage Plasticity (CDP) models was employed to analyze the dynamic behavior of the ground in response to hydrogen gas explosions in shallow underground hydrogen storage facilities and to assess the stability of nearby structures against explosion effects. According to the simulation results, it was possible to ensure the structural stability of nearby buildings and tunnel structures by maintaining a minimum separation distance. In the case of nearby building structures, a distance of at least 6 to 7 m is needed to be maintained from the underground hydrogen storage facility to prevent explosion damage from a hydrogen gas explosion. For nearby tunnel structures, a distance of at least 10 m is required to ensure structural stability.

Ensuring the operational safety and reliability of rotary machinery systems, especially in oil plants, has become a focal point in both academic and industry arenas. Specifically, in terms of key rotary machinery components such as shafts, the diagnosis of these systems is paramount for achieving enhanced generalization capabilities in fault diagnosis, encompassing multiple sensor-derived variables with their respective fault patterns. This study introduces a multi-stage approach to generalize capabilities for fault diagnosis that considers multiple sensor-derived variables and their fault patterns. This method combines the Convolutional Triplet Network for feature extraction with an ensemble model for fault classification. Initially, vibration signals are processed to yield the most representative temporal and spatial features. Then, an ensemble approach is used to maximize both diversity and accuracy by balancing the contributions of the individual classifiers. The approach can detect three representative types of shaft faults more accurately than traditional single-stage machine learning models. Comprehensive experiments, detailed within, showcase the method’s efficacy in diagnosing rotary machine faults across diverse operational scenarios.

Abstract This study proposes using microalgae‐containing carbohydrate bioactives, an Euglena gracilis‐derived extracellular microvesicle (EMVEG) system, for enhanced skin regeneration. The critical deformation ratio, 1.67, during cell extrusion enables the authors to tune the particle size of the EMVEG at ≈1 µm, thus satisfying the encapsulation yield of β‐1,3‐glucan and the cellular delivery performance. In vitro 5‐bromo‐2'‐deoxyuridine and cell scratch assays reveal that the EMVEG promotes the proliferation and migration of skin cells, thereby increasing both collagen synthesis and the expressions of proliferation‐associated proteins. An ex vivo wound‐healing test using both artificial and porcine skin reveals that similar to that seen using β‐1,3‐glucan, the EMVEG can substantially increase the cell population, expressing the proliferation‐related protein, termed proliferating cell nuclear antigen. These results demonstrate that the EMVEG system shows considerable potential in the field of skin regeneration. This technique is expected to design new types of extracellular vesicles that are applicable for skin regeneration in the pharmaceutical and cosmetic industries.

Plant-derived exosomes can exert therapeutic effects against various dermatological conditions. Several studies have demonstrated that plant-derived exosomes can have positive effects on the skin, preventing aging, hyperpigmentation, and hair loss. In this study, the protective effects of Iris germanica L. rhizome-derived exosomes (Iris-exosomes) on oxidative-stress-induced cellular dysfunction were investigated in human epidermal keratinocytes (nHEKs). Iris-exosomes with a diameter range of 100–300 nm were detected. In the cytotoxicity assay, Iris-exosomes with up to 107 particles per milliliter were found to possess no cytotoxicity, and we recovered H2O2-induced cell viability loss. In nHEKs, H2O2-induced ROS levels were significantly reduced using Iris-exosomes and additionally associated with increases in antioxidant enzyme transcription. The H2O2-induced SA-β-gal-positive nHEKs were decreased using Iris-exosomes; these effects correlate with the changed levels of cell cycle arrest marker p21. Furthermore, the H2O2-induced loss of in vitro wound-healing properties and early detection of keratin 1 and 10—keratinization markers—were restored to control levels using Iris-exosomes. Altogether, these results indicate the possibility that Iris-exosomes exert antioxidant and anti-senescence effects in order to protect against oxidative-stress-induced cellular dysfunction in nHEKs.

We demonstrate a modified stochastic gradient (Tiki-Taka v2 or TTv2) algorithm for deep learning network training in a cross-bar array architecture based on ReRAM cells. There have been limited discussions on cross-bar arrays for training applications due to the challenges in the switching behavior of nonvolatile memory materials. TTv2 algorithm is known to overcome the device non-idealities for deep learning training. We demonstrate the feasibility of the algorithm for a linear regression task using 1R and 1T1R ReRAM devices. Using the measured device properties, we project the performance of a long short-term memory (LSTM) network with 78 K parameters. We show that TTv2 algorithm relaxes the criteria for symmetric device update response. In addition, further optimization of the algorithm increases noise robustness and significantly reduces the required number of states, thereby drastically improving the model accuracy even with non-ideal devices and achieving the test error close to that of the conventional learning algorithm with an ideal device.

Background: Lung cancer has a high incidence worldwide, and most lung cancer-associated deaths are attributable to cancer metastasis. Although several medicinal properties of Panax ginseng Meyer have been reported, the effect of ginsenosides Rk1 and Rg5 on epithelial-mesenchymal transition (EMT) stimulated by transforming growth factor beta 1 (TGF- β1) and self-renewal in A549 cells is relatively unknown. Methods: We treated TGF-β1 or alternatively Rk1 and Rg5 in A549 cells. We used western blot analysis, real-time polymerase chain reaction (qPCR), wound healing assay, Matrigel invasion assay, and anoikis assays to determine the effect of Rk1 and Rg5 on TGF-mediated EMT in lung cancer cell. In addition, we performed tumorsphere formation assays and real-time PCR to evaluate the stem-like properties. Results: EMT is induced by TGF-β1 in A549 cells causing the development of cancer stem-like features. Expression of E-cadherin, an epithelial marker, decreased and an increase in vimentin expression was noted. Cell mobility, invasiveness, and anoikis resistance were enhanced with TGF-β1 treatment. In addition, the expression of stem cell markers, CD44, and CD133, was also increased. Treatment with Rk1 and Rg5 suppressed EMT by TGF-β1 and the development of stemness in a dose-dependent manner. Additionally, Rk1 and Rg5 markedly suppressed TGF-β1-induced metalloproteinase-2/9 (MMP2/9) activity, and activation of Smad2/3 and nuclear factor kappa B/extra-cellular signal regulated kinases (NF-kB/ERK) pathways in lung cancer cells. Conclusions: Rk1 and Rg5 regulate the EMT inducing TGF-β1 by suppressing the Smad and NF-κB/ERK pathways (non-Smad pathway).

Senescent fibroblasts progressively deteriorate the functional properties of skin tissue. Senescent cells secrete senescence-associated secretory phenotype (SASP) factor, which causes the aging of surrounding non-senescent cells and accelerates aging in the individuals. Recent findings suggested the senomorphic targeting of the SASP regulation as a new generation of effective therapeutics. We investigated whether Isatis tinctoria L. leaf extract (ITE) inhibited senescence biomarkers p53, p21CDKN1A, and p16INK4A gene expression, and SASP secretions by inhibiting cellular senescence in the replicative senescent human dermal fibroblast (RS-HDF). ITE has been demonstrated to inhibit the secretion of SASP factors in several senomorphic types by regulating the MAPK/NF-κB pathway via its inhibitory effect on mTOR. ITE suppressed the inflammatory response by inhibiting mTOR, MAPK, and IκBα phosphorylation, and blocking the nuclear translocation of NF-κB. In addition, we observed that autophagy pathway was related to inhibitory effect of ITE on cellular senescence. From these results, we concluded that ITE can prevent and restore senescence by blocking the activation and secretion of senescence-related factors generated from RS-HDFs through mTOR-NF-κB regulation.

The lack of understanding of mixed transport in ion-permeable conjugated polymer films hinders the advance of organic electrochemical transistors for bioelectronics. Here, the authors elucidate the structure-property-performance relationships for conventional and crystallized PEDOT:PSS films.

Water supply systems are essential elements for human life and industry, and water leaks and water supply cut-off may cause major problems. Local water leaks and pipe failures in the water supply system are inevitable problems due to the aging of pipes. Therefore, leakage detection and prevention are required to monitor the integrity of the water supply system. This paper is a fundamental study on the applicability of the smart bolt, which was developed as a monitoring system to detect water leakage in water supply monitoring. Detection experiments were conducted using a smart bolt with a built-in strain sensor and an accelerometer. Through finite element analysis using ANSYS 2019 R2 and tensile strength testing, the strength of the smart bolt was confirmed to have the acceptable tensile strength. The smart bolt used in this study was verified to meet the allowable criteria of torque and tensile stress for a municipal water supply system. The frequency responses of the simulated leakage pipe system, according to the leakage of the valve and the main pipe, were analyzed, and a leak signal at the valve leak point was detected in the 60-Hz band. The main pipe leaking point was observed to produce a leak signal with a much higher-order mode than that of the valve leak point. Therefore, the smart bolt can be applied to detect warning leak signs from water supply valves and to monitor for loosening of the bolts.

In order to detect damage to underwater infrastructure for inspection, an expensive survey by a diver is generally conducted, but it carries the risk of accidents. Accordingly, the development of an effective unmanned underwater survey system is an important priority. The unmanned underwater survey system used in this study is equipped with sonar towed by an- Unmanned Surface Vehicle (USV) to conduct the survey, but the USV is more affected by the waves and swells than a common boat. As a result, distorted sonar data causes errors in the information regarding the damage of underwater infrastructure. This study proposes the method of sonar image stabilization to minimize the errors of the distortion of sonar data by using a motion sensor. The change in the amount of the roll was calculated from the motion sensor, and the sonar data was corrected in the sonar ping unit. The sonar image stabilization algorithm was verified through field tests, and the error rate before and after correction was reduced by 15%. It is expected that, in the future, the proposed approach will be used as a standard data-gathering system for securing the reliability of sonar data when performing an unmanned underwater survey.

The ground freezing technique was first invented for the undisturbed sampling of the granular soils. With increasing necessity of liquefaction evaluation under earthquake loading, there has been more research with high-quality granular samples, with ground freezing techniques in the world. However, there has been little research on the ground freezing techniques since Korea had no records of liquefactions until the Pohang earthquake in 2017. Since more than 10 places were reported with liquefaction phenomena, it is required to assess the liquefaction potential with high-quality samples of granular soils. Therefore, in order to obtain undisturbed samples of granular soils, a new local ground freezing equipment and an operating system were developed in this study. The applied coolant was liquid nitrogen and circulated through a double tube inserted in the ground. To evaluate the performance of the system, laboratory scale tests were performed with water only and saturated fine sands. In the laboratory evaluation, a frozen soil column of 60 cm diameter was made after 20 hours and the average freezing rate was approximately 12 mm/hr in radial direction. After laboratory evaluation, the freezing system was applied in the field and the performance was evaluated with the 2D electrical resistivity tomography. In the field evaluation, the frozen region was 4 m diameter with 6.5 m depth in a cylindrical shape.

Insulin plays a key role in glucose homeostasis and is hence used to treat hyperglycemia, the main characteristic of diabetes mellitus. Annulohypoxylon annulatum is an inedible ball-shaped wood-rotting fungus, and hypoxylon F is one of the major compounds of A. annulatum. The aim of this study is to evaluate the effects of hypoxylonol F isolated from A. annulatum on insulin secretion in INS-1 pancreatic β-cells and demonstrate the molecular mechanisms involved. Glucose-stimulated insulin secretion (GSIS) values were evaluated using a rat insulin ELISA kit. Moreover, the expression of proteins related to pancreatic β-cell metabolism and insulin secretion was evaluated using Western blotting. Hypoxylonol F isolated from A. annulatum was found to significantly enhance glucose-stimulated insulin secretion without inducing cytotoxicity. Additionally, hypoxylonol F enhanced insulin receptor substrate-2 (IRS-2) levels and activated the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway. Interestingly, it also modulated the expression of peroxisome proliferator-activated receptor γ (PPARγ) and pancreatic and duodenal homeobox 1 (PDX-1). Our findings showed that A. annulatum and its bioactive compounds are capable of improving insulin secretion by pancreatic β-cells. This suggests that A. annulatum can be used as a therapeutic agent to treat diabetes.

Hydraulic factors account for a large part of the causes of bridge collapse. Due to the nature of the underwater environment, quick and accurate inspection is required when damage occurs. In this study, we developed a 2 MHz side scan sonar sensor module and effective operation technique by improving the limitations of existing sonar. Through field tests, we analyzed the correlation of factors affecting the resolution of the sonar data such as the angle of survey, the distance from the underwater structure and the water depth. The effect of the distance and the water depth and the structure on the survey angle was 66~82%. We also derived the relationship between these factors as a regression model for effective operating techniques. It is considered that application of the developed 2 MHz side scan sonar and its operation method could contribute to prevention of bridge collapses and disasters by quickly and accurately checking the damage of bridge substructures due to hydraulic factors.

We introduce a new class of optimization problems called scale invariant problems that cover interesting problems in machine learning and statistics and show that they are efficiently solved by a general form of power iteration called scale invariant power iteration (SCI-PI). SCI-PI is a special case of the generalized power method (GPM) (Journée et al., 2010) where the constraint set is the unit sphere. In this work, we provide the convergence analysis of SCI-PI for scale invariant problems which yields a better rate than the analysis of GPM. Specifically, we prove that it attains local linear convergence with a generalized rate of power iteration to find an optimal solution for scale invariant problems. Moreover, we discuss some extended settings of scale invariant problems and provide similar convergence results. In numerical experiments, we introduce applications to independent component analysis, Gaussian mixtures, and non-negative matrix factorization with the KL-divergence. Experimental results demonstrate that SCI-PI is competitive to application specific state-of-the-art algorithms and often yield better solutions. [ABSTRACT FROM AUTHOR]

The compounds hydrangenol and hydrangenol 8-O-glucoside are abundant in Hydrangea macrophylla. This study investigated the effects of hydrangenol and hydrangenol 8-O-glucoside derived from H. macrophylla on atopic dermatitis (AD). Compared with hydrangenol 8-O-glucoside, hydrangenol resulted in more potent inhibition of interleukin 4 (IL-4) gene expression and β-hexosaminidase release, as well as more potent inhibition of the phosphorylation of signal transducer and activator of transcription 6 (STAT6). Ultra High-Performance Liquid Chromatography (UHPLC), the concentrations of hydrangenol were found to be lower than the concentration of hydrangenol 8-O-glucoside in H. macrophylla extracts. To increase the hydrangenol content of H. macrophylla extract, component conversion methods were studied. Conclusion, microwave processing was found to be the optimal method for deglycosylation. [ABSTRACT FROM AUTHOR]

Recent advances in deep neural network demand more than millions of parameters to handle and mandate the high-performance computing resources with improved efficiency. The cross-bar array architecture has been considered as one of the promising deep learning architectures that shows a significant computing gain over the conventional processors. To investigate the feasibility of the architecture, we examine nonidealities and their impact on the performance. Specifically, we study the impact of failed cells due to the initialization process of the resistive memory-based cross-bar array. Unlike the conventional memory array, individual memory elements cannot be rerouted and, thus, may have a critical impact on model accuracy. We categorize the possible failures and propose hardware implementation that minimizes catastrophic failures. Such hardware optimization bounds the possible logical value of the failed cells and allows us to compensate for the loss of accuracy via off-line training. By introducing the random weight defects during the training, we show that the model becomes more resilient on the device initialization failures, therefore, less prone to degrade the inference performance due to the failed devices. Our study sheds light on the hardware and software co-optimization procedure to cope with potentially catastrophic failures in the cross-bar array. [ABSTRACT FROM AUTHOR]

We propose a general algorithmic framework for Bayesian model selection. A spike-and-slab Laplacian prior is introduced to model the underlying structural assumption. Using the notion of effective resistance, we derive an EM-type algorithm with closed-form iterations to efficiently explore possible candidates for Bayesian model selection. The deterministic nature of the proposed algorithm makes it more scalable to large-scale and high-dimensional data sets compared with existing stochastic search algorithms. When applied to sparse linear regression, our framework recovers the EMVS algorithm (Rockova and George, 2014) as a special case. We also discuss extensions of our framework using tools from graph algebra to incorporate complex Bayesian models such as biclustering and submatrix localization. Extensive simulation studies and real data applications are conducted to demonstrate the superior performance of our methods over its frequentist competitors such as l0 or l1 penalization. [ABSTRACT FROM AUTHOR]

We use self-consistent quantum transport theory to investigate the influence of electron-electron interactions on interlayer transport in semiconductor electron bilayers in the absence of an external magnetic field. We conclude that, even though spontaneous pseudospin order does not occur at zero field, interaction-enhanced quasiparticle tunneling amplitudes and pseudospin transfer torques do alter tunneling I-V characteristics, and can lead to time-dependent response to a dc bias voltage. [ABSTRACT FROM AUTHOR]

A high-pulse conversion technique for high voltage and high power applications such as HVDC transmission system is proposed. The proposed technique, based on the DC current reinjection, further decreases the number of components in the auxiliary circuit to achieve the same pulse number. An optimised control strategy over the whole range of phase delay angle is provided along with sophisticated input current and output voltage analysis. With the pulse multiplication strategy the proposed schemes demonstrate 24-pulse, 36-pulse and 48-pulse characteristics both in the input current and in the output voltage. Experimental results from a 3 KVA laboratory prototype verify the proposed concept. [ABSTRACT FROM AUTHOR]

An epitaxial laterally overgrown (ELOG) GaN layer was deposited on a (0001) sapphire substrate. Here we introduce a maskless and single-step epitaxial lateral overgrowth (ELO) process using high-dose N+-ion-implantation. We employed high-dose N+-ion-implantation as an ELO mask instead of usual dielectric material such as SixNy or SiO2. The GaN layer was laterally grown over the ion implanted array formed in a stripe pattern of 4 μm width, resulting in a complete coalescence after approximately 2.5 μm of growth in the [0001] direction. Transmission electron microscopy and photoluminescence analysis confirmed the reduced dislocation density of the ELO grown GaN layer. [ABSTRACT FROM AUTHOR]

As experimental probes have matured to observe ultrafast transient and high frequency responses of materials and devices, so to have the theoretical methods to numerically and analytically simulate time- and frequency-resolved transport. In this review article, we discuss recent progress in the development of the time-dependent and frequency-dependent non-equilibrium Green function (NEGF) technique. We begin with an overview of the theoretical underpinnings of the underlying Kadanoff–Baym equations and derive the fundamental NEGF equations in the time and frequency domains. We discuss how these methods have been applied to a variety of condensed matter systems such as molecular electronics, nanoscale transistors, and superconductors. In addition, we survey the application of NEGF in fields beyond condensed matter, where it has been used to study thermalization in ultra-cold atoms and to understand leptogenesis in the early universe. Throughout, we pay special attention to the challenges of incorporating contacts and interactions, as the NEGF method is uniquely capable of accounting for such features. [ABSTRACT FROM AUTHOR]

As a promising candidate system to realize topological superconductivity, the system of a 3D topological insulator (TI) grown on top of the s-wave superconductor has been extensively studied. To access the topological superconductivity experimentally, the 3D TI sample must be thin enough to allow for Cooper pair tunneling to the exposed surface of TI. The use of magnetically ordered dopants to break time-reversal symmetry may allow the surface of a TI to host Majorana fermion, which are believed to be a signature of topological superconductivity. In this work, we study a magnetically-doped thin film TI-superconductor hybrid system. Considering the proximity induced order parameter in thin film of TI, we analyze the gap closing points of the Hamiltonian and draw the phase diagram as a function of relevant parameters: the hybridization gap, Zeeman energy, and chemical potential of the TI system. Our findings provide a useful guide in choosing relevant parameters to facilitate the observation of topological superconductivity in thin film TI-superconductor hybrid systems. In addition, we further perform numerical analysis on a TI proximity coupled to an s-wave superconductor and find that, due to the spin-momentum locked nature of the surface states in TI, the induced s-wave order parameter of the surface states persists even at large magnitude of the Zeeman energy. [ABSTRACT FROM AUTHOR]

Unconventional superconductivity has been predicted to arise in the topologically nontrivial Fermi surface of doped inversion-symmetric Weyl semimetals (WSMs). In particular, Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) and nodal BCS states are theoretically predicted to be possible superconductor pairing states in inversion-symmetric doped WSMs. In an effort to resolve the preferred pairing state, we theoretically study two separate four-terminal quantum transport methods that each exhibit a unique electrical signature in the presence of FFLO and nodal BCS states in doped WSMs. We first introduce a Josephson junction that consists of a doped WSM and an s-wave superconductor in which we show that the application of a transverse uniform current in s-wave superconductors effectively cancels the momentum carried by FFLO states in doped WSMs. From our numerical analysis, we find a peak in Josephson current amplitude at finite uniform current in s-wave superconductors that serves as an indicator of FFLO states in doped WSMs. Furthermore, we show using a four-terminal measurement configuration that the nodal points may be shifted by an application of transverse uniform current in doped WSMs. We analyze the topological phase transitions induced by nodal pair annihilation in nonequilibrium by constructing the phase diagram and we find a characteristic decrease in the density of states that serves as a signature of the quantum critical point in the topological phase transition, thereby identifying nodal BCS states in doped WSMs. [ABSTRACT FROM AUTHOR]

We study the superconducting properties of the thin film BCS superconductor proximity coupled to a magnetically doped time-reversal invariant topological insulator (TI). Using mean-field theory, we show that Fulde-Ferrell (FF) pairing can be induced in the conventional superconductor through the inverse proximity effect (IPE). This occurs when the IPE of the TI to the superconductor is large enough that the normal bands of the superconductor possess a proximity induced spin-orbit coupling and magnetization. We find that the energetics of the different pairings are dependent on the coupling strength between the TI and the BCS superconductor and the thickness of the superconductor film. As the thickness of the superconductor film is increased, we find a crossover from the FF pairing to the BCS pairing phase. This is a consequence of the increased number of the superconducting bands, which favor the BCS pairing, implying that the FF phase can only be observed in the thin film limit. In addition, we also propose transport experiments that show distinct signatures of the FF phase. [ABSTRACT FROM AUTHOR]