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