The transition of eldercare responsibility and traditional filial piety concepts and its urban-rural differences in China: an age-period-cohort analysis from 2006 to 2017.

BACKGROUND: With rapid urbanization, massive migration, and non-family-based eldercare involvement, Chinese concepts of eldercare responsibility and filial piety are shifting. We performed age-period-cohort (APC) analyses to assess the transition of old-age pension coverage, eldercare responsibility, and filial piety concepts and its urban-rural differences among Chinese adults using data from the China General Social Survey (2006-2017). METHODS: Old-age pension coverage (yes/no) and primary eldercare responsibility (government/offspring/self/sharing) were investigated in 2010, 2012, 2013, 2015, and 2017. Filial piety was evaluated using customized questionnaires in 2006 and 2017. The APC effects were estimated using mixed effects and generalized additive models. RESULTS: Among 66,182 eligible participants (mean age: 48.8 years, females: 51.7%) in the six waves, APC analyses indicated that old-age pension coverage increased with aging and over time. Across cohort groups, it grew as the cohort was younger in urban residents but decreased in rural residents. The concept of offspring-based (> 50%) and government/self/offspring-shared eldercare (> 30%) predominated. APC analyses revealed that the offspring-based concept declined with aging (OR = 0.81, 95% CI: 0.79-0.84), whereas the government-based (OR = 1.37, 95% CI: 1.33-1.41) and self-based (OR = 1.55, 95% CI: 1.47-1.63) concepts increased with aging. People born around the 1940s have a comparatively higher possibility to perceive that the primary eldercare responsibility should be undertaken by the government and elder parents. In contrast, people born in the younger cohort were more likely to perceive that adult children are responsible for their parents' primary eldercare. Filial piety score slightly increased with aging (ß = 0.18, SD: 0.05) but decreased as the birth cohort was younger. In addition, rural participants were more likely to perceive offspring-based eldercare and maintain filial piety, and the related urban-rural difference was intensified by aging. CONCLUSIONS: The traditional concept that eldercare solely relies on offspring has changed to relying on multiple entities, including the government and self-reliance. Diluted filial piety in people born in the young cohort requires reinforcement. Moreover, future healthy aging policies need to focus more on urban-rural disparities to promote equity in social well-being.

Bibliometric study and visualization of cellular senescence associated with osteoarthritis from 2009 to 2023.

BACKGROUND: Osteoarthritis is a common degenerative joint disease that is highly prevalent in the elderly population. Along with the occurrence of sports injuries, osteoarthritis is gradually showing a younger trend. Osteoarthritis has many causative factors, and its pathogenesis is currently unknown. Cellular senescence is a stable form of cell cycle arrest exhibited by cells in response to external stimuli and plays a role in a variety of diseases. And it is only in the last decade or so that cellular senescence has gradually become cross-linked with osteoarthritis. However, there is no comprehensive bibliometric analysis in this field. The aim of this study is to present the current status and research hotspots of cellular senescence in the field of osteoarthritis, and to predict the future trends of cellular senescence in osteoarthritis research from a bibliometric perspective. METHODS: This study included 298 records of cellular senescence associated with osteoarthritis from 2009 to 2023, with data from the Web of Science Core Collection database. CiteSpace, Scimago Graphica software, VOSviewer, and the R package "bibliometrix" software were used to analyze regions, institutions, journals, authors, and keywords to predict recent trends in cellular senescence related to osteoarthritis research. RESULTS: The number of publications related to cellular senescence associated with osteoarthritis is increasing year by year. China and the United States contribute more than 70% of the publications and are the mainstay of research in this field. Central South University is the most active institution with the largest number of publications. International Journal of Molecular Sciences is the most popular journal in the field with the largest number of publications, while Osteoarthritis and Cartilage is the most cited journal. Loeser, Richard F. is not only the most prolific author, but also the most frequently cited author, contributing greatly to the field. CONCLUSION: In the last decade or so, this is the first bibliometric study that systematically describes the current status and development trend of research on cellular senescence associated with osteoarthritis. The study comprehensively and systematically summarizes and concludes the research hotspots and development trends, providing valuable references for researchers in this field.

Utility of contrast-enhanced MRI radiomics features combined with clinical indicators for predicting induction chemotherapy response in primary central nervous system lymphoma.

PURPOSE: To assess the utility of combining contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics features with clinical variables in predicting the response to induction chemotherapy (IC) for primary central nervous system lymphoma (PCNSL). METHODS: A total of 131 patients with PCNSL (101 in the training set and 30 in the testing set) who had undergone contrast-enhanced MRI scans were retrospectively analyzed. Pyradiomics was utilized to extract radiomics features, and the clinical variables of the patients were gathered. Radiomics prediction models were developed using different combinations of feature selection methods and machine learning models, and the best combination was ultimately chosen. We screened clinical variables associated with treatment outcomes and developed clinical prediction models. The predictive performance of radiomics model, clinical model, and combined model, which integrates the best radiomics model and clinical characteristics, was independently assessed and compared using Receiver Operating Characteristic (ROC) curves. RESULTS: In total, we extracted 1598 features. The best radiomics model we selected as the best utilized T-test and Recursive Feature Elimination (RFE) for feature selection and logistic regression for model building. Serum Interleukin 2 Receptor (IL-2R) and Eastern Cooperative Oncology Group (ECOG) Score were utilized to develop a clinical predictive model for assessing the response to induction chemotherapy. The results of the testing set revealed that the combined prediction model (radiomics and IL-2R) achieved the highest area under the ROC curve at 0.868 (0.683, 0.967), followed by the radiomics model at 0.857 (0.681, 0.957), and the clinical prediction model (IL-2R and ECOG) at 0.618 (0.413, 0.797). The combined model was significantly more accurate than the clinical model, with an AUC of 0.868 compared to 0.618 (P < 0.05). While the radiomics model had slightly better predictive power than the clinical model, this difference was not statistically significant (AUC, 0.857 vs. 0.618, P > 0.05). CONCLUSIONS: Our prediction model, which combines radiomics signatures from CE-MRI with serum IL-2R, can effectively stratify patients with PCNSL before high-dose methotrexate (HD-MTX) -based chemotherapy.

Construction of MnO2-Mn3O4 heterostructures to facilitate high-performance aqueous magnesium ion energy storage.

MnO2-Mn3O4 heterostructure materials are applied in aqueous magnesium ion energy storage for the first time. The heterostructure yields an exceptionally high pseudocapacitance contribution, resulting in a specific capacitance of 313.5 F g-1 at 1 A g-1, which contrasts with that of MnO2 (108.8 F g-1) and Mn3O4 (123.5 F g-1). Additionally, it shows potential for practical applications as a cathode for magnesium ion hybrid supercapacitors (MHS).

The Application of CT Radiomics in the Diagnosis of Vein Wall Invasion in Patients With Renal Cell Carcinoma Combined With Tumor Thrombus.

OBJECTIVE: The objective of this study was to explore the application of radiomics combined with machine learning to establish different models to assist in the diagnosis of venous wall invasion in patients with renal cell carcinoma and venous tumor thrombus and to evaluate the diagnostic efficacy. MATERIALS AND METHODS: We retrospectively reviewed the data of 169 patients in Peking University Third Hospital from March 2015 to January 21, who was diagnosed as renal mass with venous invasion. According to the intraoperative findings, 111 patients were classified to the venous wall invasion group and 58 cases in the non-invasion group. ITK-snap was used for tumor segmentation and PyRadiomics 3.0.1 package was used for feature extraction. A total of 1598 features could be extracted from each CT image. The patients were divided into training set and testing set by time. The elastic-net regression with 4-fold cross-validation was used as a dimension-reduction method. After feature selection, a support vector machines (SVM) model, a logistic regression (LR) model, and an extra trees (ET) model were established. Then the sensitivity, specificity, accuracy, and the area under the curve (AUC) were calculated to evaluate the diagnostic performance of each model on the testing set. RESULTS: Patients before September 2019 were divided into the training set, of which 88 patients were in the invasion group and 42 patients were in the non-invasion group. The others were in the testing set, of which 32 patients were in the invasion group and 16 patients were in the non-invasion group. A total of 34 radiomics features were obtained by the elastic-net regression. The SVM model had an AUC value of 0.641 (95% CI, 0.463-0.769), a sensitivity of 1.000, and a specificity of 0.062. The LR model had an AUC value of 0.769 (95% CI, 0.620-0.877), a sensitivity of 0.913, and a specificity of 0.312. The ET model had an AUC value of 0.853 (95% CI, 0.734-0.948), a sensitivity of 0.783, and a specificity of 0.812. Among the 3 models, the ET model had the best diagnostic effect, with a good balance of sensitivity and specificity. And the higher the tumor thrombus grade, the better the diagnostic efficacy of the ET model. In inferior vena cava tumor thrombus, the sensitivity, specificity, accuracy, and AUC of ET model can be improved to 0.889, 0.800, 0.857, 0.878 (95% CI, 0.745-1.000). CONCLUSION: Machine learning combined with radiomics method can effectively identify whether venous wall was invaded by tumor thrombus and has high diagnostic efficacy with an AUC of 0.853 (95% CI, 0.734-0.948).

Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP presence. PURPOSE: To develop deep learning models for detecting AP presence, and to compare the performance of these models with those of a clinical model (CM) and radiologists' interpretation (RI). STUDY TYPE: Retrospective. POPULATION: Totally, 616 men from six institutions who underwent radical prostatectomy, were divided into a training cohort (508 patients from five institutions) and an external validation cohort (108 patients from one institution). FIELD STRENGTH/SEQUENCES: T2-weighted imaging with a turbo spin echo sequence and diffusion-weighted imaging with a single-shot echo plane-imaging sequence at 3.0 T. ASSESSMENT: The reference standard for AP was histopathological extracapsular extension, seminal vesicle invasion, or positive surgical margins. A deep learning model based on the Swin-Transformer network (TransNet) was developed for detecting AP. An integrated model was also developed, which combined TransNet signature with clinical characteristics (TransCL). The clinical characteristics included biopsy Gleason grade group, Prostate Imaging Reporting and Data System scores, prostate-specific antigen, ADC value, and the lesion maximum cross-sectional diameter. STATISTICAL TESTS: Model and radiologists' performance were assessed using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The Delong test was used to evaluate difference in AUC. P < 0.05 was considered significant. RESULTS: The AUC of TransCL for detecting AP presence was 0.813 (95% CI, 0.726-0.882), which was higher than that of TransNet (0.791 [95% CI, 0.702-0.863], P = 0.429), and significantly higher than those of CM (0.749 [95% CI, 0.656-0.827]) and RI (0.664 [95% CI, 0.566-0.752]). DATA CONCLUSION: TransNet and TransCL have potential to aid in detecting the presence of AP and some single adverse pathologic features. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 4.

N-Doped Porous Carbon-Nanofiber-Supported Fe3C/Fe2O3 Nanoparticles as Anode for High-Performance Supercapacitors.

Exploring anode materials with an excellent electrochemical performance is of great significance for supercapacitor applications. In this work, a N-doped-carbon-nanofiber (NCNF)-supported Fe3C/Fe2O3 nanoparticle (NCFCO) composite was synthesized via the facile carbonizing and subsequent annealing of electrospinning nanofibers containing an Fe source. In the hybrid structure, the porous carbon nanofibers used as a substrate could provide fast electron and ion transport for the Faradic reactions of Fe3C/Fe2O3 during charge-discharge cycling. The as-obtained NCFCO yields a high specific capacitance of 590.1 F g-1 at 2 A g-1, superior to that of NCNF-supported Fe3C nanoparticles (NCFC, 261.7 F g-1), and NCNFs/Fe2O3 (NCFO, 398.3 F g-1). The asymmetric supercapacitor, which was assembled using the NCFCO anode and activated carbon cathode, delivered a large energy density of 14.2 Wh kg-1 at 800 W kg-1. Additionally, it demonstrated an impressive capacitance retention of 96.7%, even after 10,000 cycles. The superior electrochemical performance can be ascribed to the synergistic contributions of NCNF and Fe3C/Fe2O3.

What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?

The present study aimed to explore the potential of artificial intelligence (AI) methodology based on magnetic resonance (MR) images to aid in the management of prostate cancer (PCa). To this end, we reviewed and summarized the studies comparing the diagnostic and predictive performance for PCa between AI and common clinical assessment methods based on MR images and/or clinical characteristics, thereby investigating whether AI methods are generally superior to common clinical assessment methods for the diagnosis and prediction fields of PCa. First, we found that, in the included studies of the present study, AI methods were generally equal to or better than the clinical assessment methods for the risk assessment of PCa, such as risk stratification of prostate lesions and the prediction of therapeutic outcomes or PCa progression. In particular, for the diagnosis of clinically significant PCa, the AI methods achieved a higher summary receiver operator characteristic curve (SROC-AUC) than that of the clinical assessment methods (0.87 vs. 0.82). For the prediction of adverse pathology, the AI methods also achieved a higher SROC-AUC than that of the clinical assessment methods (0.86 vs. 0.75). Second, as revealed by the radiomics quality score (RQS), the studies included in the present study presented a relatively high total average RQS of 15.2 (11.0-20.0). Further, the scores of the individual RQS elements implied that the AI models in these studies were constructed with relatively perfect and standard radiomics processes, but the exact generalizability and clinical practicality of the AI models should be further validated using higher levels of evidence, such as prospective studies and open-testing datasets.

Improved antioxidant activity of rutin via lipase-mediated esterification with oleic acid.

BACKGROUND: Oxidation is a major problem for oils and fats, which can be mitigated by antioxidants. Rutin has excellent antioxidant activity, but its poor lipid solubility greatly limits its practical application. In this study, an efficient enzymatic synthesis route of lipophilic rutin ester was established using oleic acid as an acyl donor, and the antioxidant potential of rutin oleate was evaluated for the first time by proton (1 H) nuclear magnetic resonance (NMR) spectroscopy. RESULTS: The synthesized product was finally identified as rutin oleate by Fourier transform infrared, high-performance liquid chromatography-mass spectrometry, and 1 H, carbon-13, and DEPT-135 NMR analyses, and the acylation site was the 4‴-OH of the rhamnose group in the rutin molecule. The maximum conversion was over 93% after 48 h of reaction using Novozym 435 as catalyst under the best conditions among these tests. The conversion of rutin ester decreased with the increase of carbon chain length and the number of carbon-carbon double bonds of the fatty acid molecule. Most importantly, rutin oleate exhibited antioxidant capacity comparable to butylated hydroxytoluene and its counterparts (rutin and oleic acid) at low temperatures (60° C), but had a significant advantage at high temperatures (120° C). CONCLUSION: The antioxidant activity of rutin was significantly enhanced by lipase-mediated esterification with oleic acid. Therefore, rutin oleate could be further developed as a novel antioxidant for use in oil- and fat-based foods. © 2023 Society of Chemical Industry.

Ultrafast Electron Transfer Dynamics of Organic Polymer Nanoparticles with Graphene Oxide.

We prepared organic polymer poly-3-hexylthiophene (p3ht) nanoparticles (NPs) and graphene oxide (GO)/reduced graphene oxide (RGO) composites p3ht NPs-GO/RGO by using the reprecipitation method. We demonstrated that GO/RGO could improve the ordering and planarity of p3ht chains as well as the formation of p3ht NPs, and confirmed the effects of GO/RGO on the fluorescence and carrier transport dynamics of p3ht NPs by using femtosecond fluorescence upconversion and transient absorption (TA) techniques. Ultrafast electron transfer (∼1 ps) between GO/RGO and p3ht NPs quenched the fluorescence of p3ht NPs, indicating excellent properties of p3ht NPs-GO/RGO as the charge transfer complexes. Efficient electron transfer may promote the applications of p3ht NPs-GO/RGO composites in organic polymer solar cells and photocatalysis. Moreover, RGO had stronger interfacial interactions and more matched conduction band energy levels with p3ht NPs than GO did, which implied that p3ht NPs-RGO might have greater application values than p3ht NPs-GO.

Predicting clinically significant prostate cancer with a deep learning approach: a multicentre retrospective study.

PURPOSE: This study aimed to develop deep learning (DL) models based on multicentre biparametric magnetic resonance imaging (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa) and compare the performance of these models with that of the Prostate Imaging and Reporting and Data System (PI-RADS) assessment by expert radiologists based on multiparametric MRI (mpMRI). METHODS: We included 1861 consecutive male patients who underwent radical prostatectomy or biopsy at seven hospitals with mpMRI. These patients were divided into the training (1216 patients in three hospitals) and external validation cohorts (645 patients in four hospitals). PI-RADS assessment was performed by expert radiologists. We developed DL models for the classification between benign and malignant lesions (DL-BM) and that between csPCa and non-csPCa (DL-CS). An integrated model combining PI-RADS and the DL-CS model, abbreviated as PIDL-CS, was developed. The performances of the DL models and PIDL-CS were compared with that of PI-RADS. RESULTS: In each external validation cohort, the area under the receiver operating characteristic curve (AUC) values of the DL-BM and DL-CS models were not significantly different from that of PI-RADS (P > 0.05), whereas the AUC of PIDL-CS was superior to that of PI-RADS (P < 0.05), except for one external validation cohort (P > 0.05). The specificity of PIDL-CS for the detection of csPCa was much higher than that of PI-RADS (P < 0.05). CONCLUSION: Our proposed DL models can be a potential non-invasive auxiliary tool for predicting csPCa. Furthermore, PIDL-CS greatly increased the specificity of csPCa detection compared with PI-RADS assessment by expert radiologists, greatly reducing unnecessary biopsies and helping radiologists achieve a precise diagnosis of csPCa.

Ultrafast charge transfer dynamics of Rhodamine B with graphene oxide.

Graphene and its derivatives, due to their two-dimensional carbon nanostructures, have provided new opportunities to fortify organic dye-based photovoltaic and photocatalytic assemblies. In this article, we employed organic dyes Rhodamine B (RdB) and graphene oxide (GO) [or reduced graphene oxide (RGO)] to assemble the composite materials RdB-GO and RdB-RGO. It was found that both GO and RGO could strongly quench the fluorescence (FL) intensity of RdB. The mechanisms of FL quenching in both RdB-GO and RdB-RGO have been investigated by using femtosecond fluorescence up-conversion and transient absorption spectroscopy. When RdB was anchored on the GO (or RGO) surface, the solvent relaxation component 3.1 ps of pure RdB disappeared; instead, the ultrafast excited state electron transfer process (1-2ps) in RdB-GO and RdB-RGO was found and originated from the LUMO of RdB to the conduction band of GO (or RGO). We further reveal that the energy level change caused by GO reduction makes the energy levels of RGO closer to those of RdB, resulting in the electron transfer being more effective in RdB-RGO. Therefore, the RdB-RGO composite materials may have higher application values for dye-sensitized solar cells.

Tunable ultrafast electron transfer in WSe2-graphene heterostructures enabled by atomic stacking order.

Efficient interfacial light-electric interconversion in van der Waals (vdW) heterostructures is crucial for their optoelectronic applications. However, an in-depth understanding of the necessary process for device operation, namely interfacial charge transfer (CT), has thus far remained elusive. In this study, by using photon energy-dependent transient THz spectroscopy, we complementarily investigate the interfacial CT process in heterostructures comprising monolayers of WSe2 and graphene with varying stacking orders on a sapphire substrate. We observe that the CT mechanism of the sub-A-exciton excitation is different from that of the above-A-exciton excitation. Notably, the CT process occurs via a photo-thermionic emission for sub-A-exciton excitations and a direct electron (or hole) transfer for above-A-exciton excitations. Furthermore, we demonstrate that the effective electric field induced by the sapphire substrate could adjust the Schottky barrier from a p-type contact (WSe2/Gr/sapphire) to an n-type contact (Gr/WSe2/sapphire). Consequently, it is more beneficial for the photo-thermionic electrons to transfer from graphene to WSe2 over the Schottky barrier in Gr/WSe2/sapphire. These results can provide new insights into the CT process in graphene-transition metal dichalcogenide (TMDC) vdW interfaces, which are critical to potential optoelectronic applications of graphene-TMDC heterostructures.

Quick stabilization of capillary for rapid determination of potassium ions in the blood of epilepsy patients by capillary electrophoresis without sample pretreatment.

Mutations in the potassium channel genes may be linked to the development of epilepsy and affect the blood potassium levels. Therefore, accurate determination of potassium in the blood will be critical to diagnose the cause of epilepsy. CE is a competent technique for the fast detection of multiple ions, but complicated matrices of a blood sample may cause significant variation of migration times and the peak shape. In this work, a procedure for rapid stabilization of the capillary inner surface through preflushing of a blood sample was employed. The process takes only 40 min for a capillary and then it can be used for more than 2 weeks. No pretreatment of the blood sample or other surface modification of the capillary is needed for the analysis. The RSDs of the migration time and peak area were reduced to 1.5 and 5.1% from 12.6 and 14.5%, respectively. The proposed method has been successfully applied to the determination of the potassium contents in the blood sample of patients with epilepsy at different stages. The recoveries of potassium ions in these blood samples are in a range from 86.5 to 104.5%.

Influence of a substrate on ultrafast interfacial charge transfer and dynamical interlayer excitons in monolayer WSe2/graphene heterostructures.

Efficient interfacial light-electric interconversion in van der Waals heterostructures is critical for their optoelectronic applications. Using time-resolved terahertz spectroscopy and transient absorption spectroscopy, the charge transfer and the dynamical interlayer excitons were investigated in the heterostructures comprising monolayer WSe2 and monolayer graphene with varying stacking order on a sapphire substrate. Herein, a more comprehensive understanding of ultrafast charge transfer and exciton dynamics in two-dimensional heterostructures is shown. Owing to the effective electric field induced by the sapphire substrate, the WSe2/graphene heterostructure exhibits positive terahertz photoconductivity after photoexcitation, while negative terahertz photoconductivity is observed in the graphene/WSe2 heterostructure. The transient absorption spectra indicate that the exciton lifetimes also exhibit a considerable difference, where WSe2/graphene exhibits the longest exciton lifetime, followed by monolayer WSe2, while graphene/WSe2 exhibits the shortest lifetime. These observations provide a new idea for using van der Waals heterostructures in electronic and photonic devices.

Solution-phase synthesis of CsPbI3 nanowire clusters via polymer-induced anisotropic growth and self-assembly.

A facile solution-phase synthesis of black γ-phase CsPbI3 nanowire clusters was developed using poly(methyl methacrylate) (PMMA) as surfactant. PMMA was found to efficiently retard the crystal growth, thereby inducing anisotropic growth for formation of the nanowire structure, while the intermolecular hydrogen bonds of PMMA act as a driving force for self-assembly of the nanowires.

Novel Wax Valves To Improve Distance-Based Analyte Detection in Paper Microfluidics.

Microfluidic paper-based analytical devices (µPADs) have been extensively studied for disease diagnostics, food quality control, and environmental monitoring due to the advantages of low cost, portability, and simplicity. The lack of flow controllability has triggered the development of valves for such devices. This paper reports the µPADs integrating novel wax valves for distance-based detection. The valves are printed on paper and can be manually opened by organic solvents within seconds. The opened valve does not influence the flow. The µPADs with wax valves were then applied in the distance-based detection of potassium iodate and glucose. The valves allow mixing of reagents and subsequent incubation in the loading zone, resulting in a shorter detection time and larger linear detection range. This study has demonstrated a linear detection range of 0.05-0.5 mM for potassium iodate, while linear ranges of 1-5 and 2.5-80 mg/dL are achieved for glucose when total detection time is 15 and 25 min, respectively. The lower detection limit is only 1/11 of that in a previous study. The detection ranges of iodate and glucose assays cover the concentrations of iodate in salt/milk and glucose in human saliva, respectively. Due to the simplicity, reliability, and ability for high-density integration, the µPADs with wax valves are of great potential in point-of-care (sampling) applications.

The modulation of terahertz photoconductivity in CVD grown n-doped monolayer MoS2 with gas adsorption.

The as-grown atomically thin transition metal dichalcogenides (TMDs) usually have extremely large surface-to-volume ratios. Hence, the electrical and optical properties are always affected by the adsorption of atmospheric gases. By using optical pump terahertz (THz) probe spectroscopy, THz photoconductivity dynamics of chemical vapor deposition grown monolayer MoS2 has been investigated in nitrogen, air and oxygen atmospheric environments. Our study reveals that the photoconductivity of MoS2 at THz frequencies is dramatically altered by the adsorption of oxygen. The relaxation dynamics of photoconductivity strongly depends on atmospheres, which is attributed to photo-excited different quasi-particles, such as free charge carriers, excitons and trions. This study highlights the role of oxygen passivation of the photoconductivity in monolayer MoS2, which may have important applications for the design of future MoS2-based electronic devices.

Near unity charge separation efficiency leads to pure ultraviolet emission in few layer graphene nanosheets.

Two-dimensional materials with van der Waals structure attract intense interest due to their high performance in ultrathin optoelectronic devices. In particular, the high efficiency charge separation between the two-dimensional materials can significantly improve the photo-response of a given device. Here we report the discovery of pure ultraviolet (UV) emission from few layer graphene nanosheets (GNS). Near unity charge separation efficiency is key to pure UV emission. The dynamics of an excited electron were analyzed using femtosecond transient absorption techniques. Electron transfer is observed from surface defect states induced by oxygen-containing functional groups to intrinsic sp2 domain states in few layer GNS. Moreover, a solar blind response device based on few layer GNS with a high on-off ratio was successfully fabricated.