14 research outputs found

    Solution-Processed Gold Nanorods Integrated with Graphene for Near-Infrared Photodetection via Hot Carrier Injection

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    Graphene-based photodetectors have attracted wide interest due to their high-speed, wide-band photodetection and potential as highly energy-efficient integrated devices. However, the inherently low-absorption cross-section and nonselective spectra response hinder its utilization as a high-performance photodetector. Here, we report a solution-processed and high-spectral-selectivity photodetector based on a gold nanorods (Au NRs)–graphene heterojunction with near-infrared (NIR) detection. Au NRs are used as a subwavelength scattering source, and nanoantennas with wide light absorption range from ultraviolet to near-infrared via tuning their geometry. Photons couple into Au NRs, exciting resonant plasmas and generating hot carriers that pump into graphene, resulting in selective NIR photodetection. A flexible NIR photodetector is also demonstrated based on this simple structure. Au NRs can achieve variable resonance frequencies by the design of different aspect ratios as nanoantennae for graphene, which promises the selective amplifying of the photoresponsivity and enables highly specific detection

    Two-Dimensional CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> Perovskite: Synthesis and Optoelectronic Application

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    Hybrid organic–inorganic perovskite materials have received substantial research attention due to their impressively high performance in photovoltaic devices. As one of the oldest functional materials, it is intriguing to explore the optoelectronic properties in perovskite after reducing it into a few atomic layers in which two-dimensional (2D) confinement may get involved. In this work, we report a combined solution process and vapor-phase conversion method to synthesize 2D hybrid organic–inorganic perovskite (<i>i.e.</i>, CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub>) nanocrystals as thin as a single unit cell (∼1.3 nm). High-quality 2D perovskite crystals have triangle and hexagonal shapes, exhibiting tunable photoluminescence while the thickness or composition is changed. Due to the high quantum efficiency and excellent photoelectric properties in 2D perovskites, a high-performance photodetector was demonstrated, in which the current can be enhanced significantly by shining 405 and 532 nm lasers, showing photoresponsivities of 22 and 12 AW<sup>–1</sup> with a voltage bias of 1 V, respectively. The excellent optoelectronic properties make 2D perovskites building blocks to construct 2D heterostructures for wider optoelectronic applications

    Graphene–Bi<sub>2</sub>Te<sub>3</sub> Heterostructure as Saturable Absorber for Short Pulse Generation

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    Rapid progresses have been achieved in the photonic applications of two-dimensional materials such as graphene, transition metal dichalcogenides, and topological insulators. The strong light–matter interactions and large optical nonlinearities in these atomically thin layered materials make them promising saturable absorbers for pulsed laser applications. Either Q-switching or mode-locking pulses with particular output characteristics can be achieved by using different saturable absorbers. However, it remains still very challenging to produce saturable absorbers with tunable optical properties, in particular, carrier dynamics, saturation intensity as well as modulation depth, to suit for self-starting, high energy or ultrafast pulse laser generation. Here we report a new type of saturable absorber which is a van der Waals heterostructure consisting of graphene and Bi<sub>2</sub>Te<sub>3</sub>. The synergetic integration of these two materials by epitaxial growth affords tunable optical properties, that is, both the photocarrier dynamics and the nonlinear optical modulation are variable by tuning the coverage of Bi<sub>2</sub>Te<sub>3</sub> on graphene. We further fabricated graphene–Bi<sub>2</sub>Te<sub>3</sub> saturable absorbers and incorporated them into a 1.5 μm fiber laser to demonstrate both Q-switching and mode-locking pulse generation. This work provides a new insight for tailoring two-dimensional heterostructures so as to develop desired photonic applications

    Table_2_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

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    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    Table_5_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    DataSheet_2_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    Table_3_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    Table_4_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    Table_6_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p

    Table_1_Relationship between metastasis and second primary cancers in women with breast cancer.xlsx

    No full text
    BackgroundBreast cancer (BC) survivors have an increased risk of developing second primary cancers (SPCs); however, it is still unclear if metastasis is a risk factor for developing SPCs. Usually, long-term cancer survivors face an increased risk of developing SPCs; however, less attention has been paid to SPCs in patients with metastatic cancer as the survival outcomes of the patients are greatly reduced.MethodsA total of 17,077 American women diagnosed with breast cancer between 2010 and 2018 were identified from Surveillance, Epidemiology, and End Results (SEER) database and were included in the study. The clinical characteristics, standardized incidence ratio (SIR), standardized mortality ratio (SMR), and patterns of SPCs in BC patients with no metastasis, regional lymph node metastasis, and distant metastasis were investigated. Kaplan-Meier method was used to compare the prognosis of BC patients after developing SPCs with different metastatic status. XGBoost, a high-precision machine learning algorithm, was used to create a prediction model to estimate the prognosis of metastatic breast cancer (MBC) patients with SPCs.ResultsThe results reveal that the SIR (1.01; 95% CI, 0.99–1.03, p>0.05) of SPCs in non-metastasis breast cancer (NMBC) patients was similar to the general population. Further, patients with regional lymph node metastasis showed an 8% increased risk of SPCs (SIR=1.08, 95%CI, 1.05–1.11, pConclusionsOur study provides novel insight into the impact of metastasis on SPCs in BC patients. Metastasis could promote the second primary tumorigenesis which further increased cancer-related deaths. Therefore, more attention should be paid to the occurrence of SPCs in MBC patients.</p
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