Enhanced Oxygen Evolution and Zinc-Air Battery Performance via Electronic Spin Modulation in Heterostructured Catalysts.

Beyond optimizing electronic energy levels, the modulation of the electronic spin configuration is an effective strategy, often overlooked, to boost activity and selectivity in a range of catalytic reactions, including the oxygen evolution reaction (OER). This electronic spin modulation is frequently accomplished using external magnetic fields, which makes it impractical for real applications. Herein, spin modulation is achieved by engineering Ni/MnFe2O4 heterojunctions, whose surface is reconstructed into NiOOH/MnFeOOH during the OER. NiOOH/MnFeOOH shows a high spin state of Ni, which regulates the OH- and O2 adsorption energy and enables spin alignment of oxygen intermediates. As a result, NiOOH/MnFeOOH electrocatalysts provide excellent OER performance with an overpotential of 261 mV at 10 mA cm-2. Besides, rechargeable zinc-air batteries based on Ni/MnFe2O4 show a high open circuit potential of 1.56 V and excellent stability for more than 1000 cycles. This outstanding performance is rationalized using density functional theory calculations, which show that the optimal spin state of both Ni active sites and oxygen intermediates facilitates spin-selected charge transport, optimizes the reaction kinetics, and decreases the energy barrier to the evolution of oxygen. This study provides valuable insight into spin polarization modulation by heterojunctions enabling the design of next-generation OER catalysts with boosted performance.

Nanoscale doping of polymeric semiconductors with confined electrochemical ion implantation.

Nanoresolved doping of polymeric semiconductors can overcome scaling limitations to create highly integrated flexible electronics, but remains a fundamental challenge due to isotropic diffusion of the dopants. Here we report a general methodology for achieving nanoscale ion-implantation-like electrochemical doping of polymeric semiconductors. This approach involves confining counterion electromigration within a glassy electrolyte composed of room-temperature ionic liquids and high-glass-transition-temperature insulating polymers. By precisely adjusting the electrolyte glass transition temperature (Tg) and the operating temperature (T), we create a highly localized electric field distribution and achieve anisotropic ion migration that is nearly vertical to the nanotip electrodes. The confined doping produces an excellent resolution of 56 nm with a lateral-extended doping length down to as little as 9.3 nm. We reveal a universal exponential dependence of the doping resolution on the temperature difference (Tg - T) that can be used to depict the doping resolution for almost infinite polymeric semiconductors. Moreover, we demonstrate its implications in a range of polymer electronic devices, including a 200% performance-enhanced organic transistor and a lateral p-n diode with seamless junction widths of <100 nm. Combined with a further demonstration in the scalability of the nanoscale doping, this concept may open up new opportunities for polymer-based nanoelectronics.

Evolution of Musculoskeletal Electronics.

The musculoskeletal system, constituting the largest human physiological system, plays a critical role in providing structural support to the body, facilitating intricate movements, and safeguarding internal organs. By virtue of advancements in revolutionized materials and devices, particularly in the realms of motion capture, health monitoring, and postoperative rehabilitation, "musculoskeletal electronics" has actually emerged as an infancy area, but has not yet been explicitly proposed. In this review, the concept of musculoskeletal electronics is elucidated, and the evolution history, representative progress, and key strategies of the involved materials and state-of-the-art devices are summarized. Therefore, the fundamentals of musculoskeletal electronics and key functionality categories are introduced. Subsequently, recent advances in musculoskeletal electronics are presented from the perspectives of "in vitro" to "in vivo" signal detection, interactive modulation, and therapeutic interventions for healing and recovery. Additionally, nine strategy avenues for the development of advanced musculoskeletal electronic materials and devices are proposed. Finally, concise summaries and perspectives are proposed to highlight the directions that deserve focused attention in this booming field.

High-Performance and Ecofriendly Organic Thermoelectrics Enabled by N-Type Polythiophene Derivatives with Doping-Induced Molecular Order.

The ability of n-type polymer thermoelectric materials to tolerate high doping loading limits further development of n-type polymer conductivity. Herein, two alcohol-soluble n-type polythiophene derivatives that are n-PT3 and n-PT4 are reported. Due to the ability of two polymers to tolerate doping loading more significantly than 100 mol%, both achieve electrical conductivity >100 S cm-1 . Moreover, the conductivity of both polythiophenes remains almost constant at high doping concentrations with excellent doping tunability, which may be related to their ability to overcome charging-induced backbone torsion and morphology change caused by saturated doping. The characterizations reveal that n-PT4 has a high doping level and carrier concentration (>3.10 × 1020  cm-3 ), and the carrier concentration continues to increase as the doping concentration increases. In addition, doping leads to improved crystal structure of n-PT4, and the crystallinity does not decrease significantly with increasing doping concentration; even the carrier mobility increases with it. The synergistic effect of these two leads to both n-PT3 and n-PT4 achieving a breakthrough of 100 in conductivity and power factor. The DMlmC-doped n-PT4 achieves a power factor of over 150 µW m-1  K-2 . These values are among the highest for n-type organic thermoelectric materials.

Quantity of questing black-legged ticks and associated micro-scale environmental data collected from four Suburban Parks near New York City.

During 2017 and 2018, we collected the quantity of questing black-legged ticks (Ixodes scapularis), also known as deer ticks, in 124 sampling sites of 5m by 5m in four state parks-Caumsett State Historic Park, Connetquot River State Park, Rockefeller State Park, and Fire Island National Seashore-around New York City. The black-legged tick is the primary vector for the spirochete Borrelia burgdorferi, the pathogen of Lyme disease, in Northeastern United States. Using the flagging method, we collected and counted the numbers of adult and nymphal black-legged ticks at each stie. Along with these quantities, we also recorded the geographic coordinates, ambient temperature, and relative humidity at the sampling sites. Using high-resolution aerial imagery and LiDAR data, we further derived land cover composition, ecotone boundary length, normalized difference vegetation index (NDVI), elevation, solar radiation, and other environmental factors. The data could be used to conduct longitudinal analysis at the same sampling sites as well as comparison with other sites. Ecologists and environmental scientists can use the data for spatiotemporal and statistical analyses of tick ecology at the local scale.

Identification of autophagy-related genes and immune cell infiltration characteristics in sepsis via bioinformatic analysis.

Background: Sepsis is a life-threatening disease with a high mortality in the intensive care unit (ICU), and autophagy plays an essential role in the development of sepsis. The purpose of this study was to identify potential autophagy-related genes in sepsis and their relationship with immune cell infiltration by bioinformatics analysis. Methods: The messenger RNA (mRNA) expression profile of the GSE28750 data set was collected from the Gene Expression Omnibus (GEO) database. The potential differentially expressed autophagy-related genes of sepsis were screened with the "limma" package in R (The Foundation for Statistical Computing). The hub genes were selected by weighted gene coexpression network analysis (WGCNA) networks with Cytoscape, and functional enrichment analysis was performed. The expression level and diagnostic value of the hub genes were validated by Wilcoxon test and receiver operating characteristic (ROC) curve analysis of the GSE95233 data set. The compositional patterns of immune cell infiltration in sepsis were estimated using the CIBERSORT algorithm. Spearman rank correlation analysis was used to associate the identified biomarkers with infiltrating immune cells. A competing endogenous (ceRNA) network was constructed to predict related noncoding RNAs of identified biomarkers with the miRWalk platform. Results: In all, 80 differential autophagy-related genes were obtained. GABARAPL2, GAPDH, WDFY3, MAP1LC3B, DRAM1, WIPI1, and ULK3 were identified as hub genes and diagnostic biomarker groups for sepsis. In addition, 7 differentially infiltrated immune cells correlated with the hub autophagy-related genes were identified. The ceRNA network predicted 23 microRNAs and 122 long noncoding RNAs related to 5 hub autophagy-related genes. Conclusions: GABARAPL2, GAPDH, WDFY3, MAP1LC3B, DRAM1, WIPI1, and ULK3 may influence the development of sepsis and have a vital impact on sepsis immune regulation as autophagy-related genes.

Boosting the Thermoelectric Performance of the Doped DPP-EDOT Conjugated Polymer by Incorporating an Ionic Additive.

The thermoelectric (TE) performance of organic materials is limited by the coupling of Seebeck coefficient and electrical conductivity. Herein a new strategy is reported to boost the Seebeck coefficient of conjugated polymer without significantly reducing the electrical conductivity by incorporation of an ionic additive DPPNMe3 Br. The doped polymer PDPP-EDOT thin film exhibits high electrical conductivity up to 1377 ± 109 S cm-1 but low Seebeck coefficient below 30 µV K-1 and a maximum power factor of 59 ± 10 µW m-1 K-2 . Interestingly, incorporation of small amount (at a molar ratio of 1:30) of DPPNMe3 Br into PDPP-EDOT results in the significant enhancement of Seebeck coefficient along with the slight decrease of electrical conductivity after doping. Consequently, the power factor (PF) is boosted to 571 ± 38 µW m-1 K-2 and ZT reaches 0.28 ± 0.02 at 130 °C, which is among the highest for the reported organic TE materials. Based on the theoretical calculation, it is assumed that the enhancement of TE performance for the doped PDPP-EDOT by DPPNMe3 Br is mainly attributed to the increase of energetic disorder for PDPP-EDOT.

Identification of iron metabolism-related genes in the circulation and myocardium of patients with sepsis via applied bioinformatics analysis.

Background: Early diagnosis of septic cardiomyopathy is essential to reduce the mortality rate of sepsis. Previous studies indicated that iron metabolism plays a vital role in sepsis-induced cardiomyopathy. Here, we aimed to identify shared iron metabolism-related genes (IMRGs) in the myocardium and blood monocytes of patients with sepsis and to determine their prognostic signature. Methods: First, an applied bioinformatics-based analysis was conducted to identify shared IMRGs differentially expressed in the myocardium and peripheral blood monocytes of patients with sepsis. Second, Cytoscape was used to construct a protein-protein interaction network, and immune infiltration of the septic myocardium was assessed using single-sample gene set enrichment analysis. In addition, a prognostic prediction model for IMRGs was established by Cox regression analysis. Finally, the expression of key mRNAs in the myocardium of mice with sepsis was verified using quantitative polymerase chain reaction analysis. Results: We screened common differentially expressed genes in septic myocardium and blood monocytes and identified 14 that were related to iron metabolism. We found that HBB, SLC25A37, SLC11A1, and HMOX1 strongly correlated with monocytes and neutrophils, whereas HMOX1 and SLC11A1 strongly correlated with macrophages. We then established a prognostic model (HIF1A and SLC25A37) using the common differentially expressed IMRGs. The prognostic model we established was expected to better aid in diagnosing septic cardiomyopathy. Moreover, we verified these genes using datasets and experiments and found a significant difference between the sepsis and control groups. Conclusion: Common differential expression of IMRGs was identified in blood monocytes and myocardium between sepsis and control groups, among which HIF1A and SLC25A37 might predict prognosis in septic cardiomyopathy. The study may help us deeply understand the molecular mechanisms of iron metabolism and aid in the diagnosis and treatment of septic cardiomyopathy.

Technology Roadmap for Flexible Sensors.

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Constant Force-Tracking Control Based on Deep Reinforcement Learning in Dynamic Auscultation Environment.

Intelligent medical robots can effectively help doctors carry out a series of medical diagnoses and auxiliary treatments and alleviate the current shortage of social personnel. Therefore, this paper investigates how to use deep reinforcement learning to solve dynamic medical auscultation tasks. We propose a constant force-tracking control method for dynamic environments and a modeling method that satisfies physical characteristics to simulate the dynamic breathing process and design an optimal reward function for the task of achieving efficient learning of the control strategy. We have carried out a large number of simulation experiments, and the error between the tracking of normal force and expected force is basically within ±0.5 N. The control strategy is tested in a real environment. The preliminary results show that the control strategy performs well in the constant force-tracking of medical auscultation tasks. The contact force is always within a safe and stable range, and the average contact force is about 5.2 N.

Self-Doping Naphthalene Diimide Conjugated Polymers for Flexible Unipolar n-Type OTFTs.

The development of high-performance organic thin-film transistor (OTFT) materials is vital for flexible electronics. Numerous OTFTs are so far reported but obtaining high-performance and reliable OTFTs simultaneously for flexible electronics is still challenging. Herein, it is reported that self-doping in conjugated polymer enables high unipolar n-type charge mobility in flexible OTFTs, as well as good operational/ambient stability and bending resistance. New naphthalene diimide (NDI)-conjugated polymers PNDI2T-NM17 and PNDI2T-NM50 with different contents of self-doping groups on their side chains are designed and synthesized. The effects of self-doping on the electronic properties of resulting flexible OTFTs are investigated. The results reveal that the flexible OTFTs based on self-doped PNDI2T-NM17 exhibit unipolar n-type charge-carrier properties and good operational/ambient stability thanks to the appropriate doping level and intermolecular interactions. The charge mobility and on/off ratio are fourfold and four orders of magnitude higher than those of undoped model polymer, respectively. Overall, the proposed self-doping strategy is useful for rationally designing OTFT materials with high semiconducting performance and reliability.

Solid state ionics enabled ultra-sensitive detection of thermal trace with 0.001K resolution in deep sea.

The deep sea remains the largest uncharted territory on Earth because it's eternally dark under high pressure and the saltwater is corrosive and conductive. The harsh environment poses great difficulties for the durability of the sensing method and the device. Sea creatures like sharks adopt an elegant way to detect objects by the tiny temperature differences in the seawater medium using their extremely thermo-sensitive thermoelectric sensory organ on the nose. Inspired by shark noses, we designed and developed an elastic, self-healable and extremely sensitive thermal sensor which can identify a temperature difference as low as 0.01 K with a resolution of 0.001 K. The sensor can work reliably in seawater or under a pressure of 110 MPa without any encapsulation. Using the integrated temperature sensor arrays, we have constructed a model of an effective deep water mapping and detection device.

Robust functional principal component analysis via a functional pairwise spatial sign operator.

Functional principal component analysis (FPCA) has been widely used to capture major modes of variation and reduce dimensions in functional data analysis. However, standard FPCA based on the sample covariance estimator does not work well if the data exhibits heavy-tailedness or outliers. To address this challenge, a new robust FPCA approach based on a functional pairwise spatial sign (PASS) operator, termed PASS FPCA, is introduced. We propose robust estimation procedures for eigenfunctions and eigenvalues. Theoretical properties of the PASS operator are established, showing that it adopts the same eigenfunctions as the standard covariance operator and also allows recovering ratios between eigenvalues. We also extend the proposed procedure to handle functional data measured with noise. Compared to existing robust FPCA approaches, the proposed PASS FPCA requires weaker distributional assumptions to conserve the eigenspace of the covariance function. Specifically, existing work are often built upon a class of functional elliptical distributions, which requires inherently symmetry. In contrast, we introduce a class of distributions called the weakly functional coordinate symmetry (weakly FCS), which allows for severe asymmetry and is much more flexible than the functional elliptical distribution family. The robustness of the PASS FPCA is demonstrated via extensive simulation studies, especially its advantages in scenarios with nonelliptical distributions. The proposed method was motivated by and applied to analysis of accelerometry data from the Objective Physical Activity and Cardiovascular Health Study, a large-scale epidemiological study to investigate the relationship between objectively measured physical activity and cardiovascular health among older women.

Enhancing the Performance of N-Type Thermoelectric Devices via Tuning the Crystallinity of Small Molecule Semiconductors.

In the development of high-performance organic thermoelectric devices, n-type materials, especially with small molecule semiconductors, lags far behind p-type materials. In this paper, three small molecules are synthesized based on electron-deficient naphthalene bis-isatin building blocks bearing different alkyl chains with the terminal functionalized with 3-ethylrhodanine unit and studied their aggregation and doping mechanism in detail. It is found that crystallinity plays an essential role in tuning the doping behavior of small molecules. Molecules with too strong crystallinity tend to aggregate with each other to form large crystalline domains, which cause significant performance degradation. While molecules with weak crystallinity can tolerate more dopants, most of them exhibit low mobility. By tuning the crystallinity carefully, organic thermoelectric devices based on C12NR can maintain high mobility and realize effective doping simultaneously, and a high power factor of 1.07 µW m-1 K-2 at 100 °C is realized. This delicate molecular design by modulating crystallinity provides a new avenue for realizing high-performance organic thermoelectric devices.

Triggering ZT to 0.40 by Engineering Orientation in One Polymeric Semiconductor.

Breaking the thermoelectric (TE) trade-off relationship is an important task for maximizing the TE performance of polymeric semiconductors. Existing efforts have focused on designing high-mobility semiconductors and achieving ordered molecular doping, ignoring the critical role of the molecular orientation during TE conversion. Herein, the achievement of ZT to 0.40 is reported by fine-tuning the molecular orientation of one diketopyrrolopyrrole (DPP)-based polymer (DPP-BTz). Films with bimodal molecular orientation yield superior doping efficiency by increasing the lamellar spacing and achieve increased splitting between the Fermi energy and the transport energy to enhance the thermopower. These factors contribute to the simultaneous improvement in the Seebeck coefficient and electrical conductivity in an unexpected manner. Importantly, the bimodal film exhibits a maximum power factor of up to 346 µW m-1 K-2 , >400% higher than that of unimodal films. These results demonstrate the great potential of molecular orientation engineering in polymeric semiconductors for developing state-of-the-art organic TE (OTE) materials.

Advances in materials and devices for mimicking sensory adaptation.

Adaptive devices, which aim to adjust electrical behaviors autonomically to external stimuli, are considered to be attractive candidates for next-generation artificial perception systems. Compared with typical electronic devices with stable signal output, adaptive devices possess unique features in exhibiting dynamic fitness to varying environments. To meet this requirement, increasing efforts have been made focusing on developing new materials, functional interfaces and novel device geometry for sensory perception applications. In this review, we summarize the recent advances in materials and devices for mimicking sensory adaptation. Keeping this in mind, we first introduce the fundamentals of biological sensory adaptation. Thereafter, the recent progress in mimicking sensory adaptation, such as tactile and visual adaptive systems, is overviewed. Moreover, we suggest five strategies to construct adaptive devices. Finally, challenges and perspectives are proposed to highlight the directions that deserve focused attention in this flourishing field.

An Oligonucleotide-Distortion-Responsive Organic Transistor for Platinum-Drug-Induced DNA-Damage Detection.

Organic transistor with DNA-damage evaluation ability can open up novel opportunities for bioelectronic devices. Even though trace amounts of drugs can cause cumulative gene damage in vivo, the extremely low occurrence proportion makes them hardly transduced into detectable electric signals. Here, an ultrasensitive DNA-damage sensor based on an oligonucleotide-distortion-responsive organic transistor (DROT) is reported by creating controllable conformation change of double-stranded DNA on the surface of organic semiconductors. In combination with interfacial charge redistribution and efficient signal amplification, the DROT provides an ultrasensitive single-site DNA-damage response with 20.5 s even upon 1 × 10-12 m cisplatin. The high generalizability of this DROT to three generations of classical platinum drugs and gene-relevant DNA damage is demonstrated. A biochip is further designed for intelligent damage analysis in complex environments, which holds the potential for high-throughput biotoxicity evaluation and drug screening in the future.

Persistent Conjugated Backbone and Disordered Lamellar Packing Impart Polymers with Efficient n-Doping and High Conductivities.

Solution-processable highly conductive polymers are of great interest in emerging electronic applications. For p-doped polymers, conductivities as high a nearly 105 S cm-1 have been reported. In the case of n-doped polymers, they often fall well short of the high values noted above, which might be achievable, if much higher charge-carrier mobilities determined could be realized in combination with high charge-carrier densities. This is in part due to inefficient doping and dopant ions disturbing the ordering of polymers, limiting efficient charge transport and ultimately the achievable conductivities. Here, n-doped polymers that achieve a high conductivity of more than 90 S cm-1 by a simple solution-based co-deposition method are reported. Two conjugated polymers with rigid planar backbones, but with disordered crystalline structures, exhibit surprising structural tolerance to, and excellent miscibility with, commonly used n-dopants. These properties allow both high concentrations and high mobility of the charge carriers to be realized simultaneously in n-doped polymers, resulting in excellent electrical conductivity and thermoelectric performance.

An Efficient Parameter-Free Learning Automaton Scheme.

The learning automaton (LA) that simulates the interaction between an intelligent agent and a stochastic environment to learn the optimal action is an important tool in reinforcement learning. Being confronted with an unknown environment, most learning automata have more than one parameters to be tuned during a pretraining process in which the LA interacts with the environment. Only after the parameters are tuned properly, an LA can act most properly during the training procedure to obtain the optimal behavior. The cost of parameter tuning can be enormous, e.g., possibly millions of interactions are required to seek the best parameter configuration. Therefore, the parameter-free LA that uses identical parameters for every environment and saves further tuning has become the hot spot of this research. This article proposes an efficient parameter-free learning automaton (EPFLA) that depends on a separating function (SF). Taking advantage of both frequentist inference and Bayesian inference, the SF plays a dual role in the proposed scheme: 1) evaluating the difference in performance between actions in the environment and 2) exploring actions by coining an action selection strategy. A proof is provided to ensure the ϵ -optimality of EPFLA. Comprehensive comparisons verify the privileges of EPFLA over both parameter-based schemes and existing parameter-free schemes.

Chemical doping of organic semiconductors for thermoelectric applications.

Doping is essential to manipulate the electrical performance of both thermoelectric (TE) materials and organic semiconductors (OSCs). Although organic thermoelectric (OTE) materials have experienced a rapid development over the past decade, the chemical doping of OSCs for TE applications lags behind, which has limited further breakthroughs in this cutting-edge field. Recently, increasing efforts have been devoted to the development of energetically matched host and dopant molecules, exploring novel doping methods and revealing the doping mechanisms. This tutorial review covers the basic mechanisms, fundamental requirements, recent advances and remaining challenges of chemical doping in OSCs for TE applications. We first present the basic knowledge of the trade-off relationship in TE materials and its critical requirements for doped OSCs, followed by a brief introduction of recent advances in the molecular design of OSCs and dopants. Moreover, we provide an overview of the existing categories of doping mechanisms and methods, and more importantly, emphasize the summarized doping strategies for the state-of-the-art OTE materials. Finally, challenges and perspectives on the chemical doping of OSCs are proposed to highlight the research directions that deserve attention towards a bright future of OTE materials.