Copper coin-embedded printed circuit board for heat dissipation: manufacture, thermal simulation and reliability

Purpose - The purpose of this paper is to form copper coin-embedded printed circuit board (PCB) for high heat dissipation. Design/methodology/approach - Manufacturing optimization of copper coin-embedded PCB involved in the design and treatment of copper coin, resin flush removal and flatness control. Thermal simulation was used to investigate the effect of copper coin on heat dissipation of PCB products. Lead-free reflow soldering and thrust tests were used to characterize the reliable performance of copper coin-embedded PCB. Findings - The copper coin-embedded PCB had good agreement with resin flush removal and flatness control. Thermal simulation results indicated that copper coin could significantly enhance the heat-dissipation rate by means of a direct contact with the high-power integrated circuit chip. The copper coin-embedded PCB exhibited a reliable structure capable of withstanding high-temperature reflow soldering and high thrust testing. Originality/value - The use of a copper coin-embedded PCB could lead to higher heat dissipation for the stable performance of high-power electronic components. The copper coin-embedded method could have important potential for improving the design for heat dissipation in the PCB industry

Effects of surface-functionalized aluminum nitride on thermal, electrical, and mechanical behaviors of polyarylene ether nitrile-based composites

Aluminum nitride (AlN) with high thermal conductivity was blended in polyarylene ether nitrile (PEN) to obtain a composite system. A ball milling process could provide AlN particles of smaller size with higher surface silylation for homogeneous particle distribution in polymeric matrix. Thermal, electrical, and mechanical behaviors of the produced composites were characterized to investigate the effects of particles on the performance of PEN-based composites with functionalized AlN. The composite exhibited thermal conductivity of 0.779 W m−1 K−1, a dielectric constant of 7.7, dielectric loss of 0.032, electrical resistivity of 1.39 GΩ.cm, and break strength of 36 N when the fraction of functionalized AlN increased to 42.3 vol%. A fitted equation based on the improved Russell's model could effectively predict a trend for thermal conductivity of the composite systems with consideration of interfacial resistance between AlN and surrounding PEN

Characterization and application of aggregated porous copper oxide flakes for cupric source of copper electrodeposition

Copper oxide was prepared with thermal decomposition of basic copper carbonate to complement the concentration of cupric ions for copper electrodeposition in a plating system with insoluble anode. Copper oxide particles with a structure of aggregated porous flakes had a wide size distribution ranging from 100 nm to 100 μm. Copper oxide exhibited a dissolution rate of about 15 s in 12.5 vol% H2SO4 solution. During copper electrodeposition, copper deposits with fine growth formed in the electrolyte with stable cupric concentration provided by rapid dissolution of copper oxide

Properties and application of polyimide-based composites by blending surface functionalized boron nitride nanoplates

Properties and application of polyimide-based composites by blending surface functionalized boron nitride nanoplate

Image_4_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.tif

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p

Image_1_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.tif

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p

Table_3_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.xlsx

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p

Table_4_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.xlsx

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p

Image_3_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.tif

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p

Image_2_Comprehensive analysis of aerobic glycolysis-related genes for prognosis, immune features and drug treatment strategy in prostate cancer.tif

BackgroundThe dysregulated expression of aerobic glycolysis-related genes is closely related to prostate cancer progression and metastasis. However, reliable prognostic signatures based on aerobic glycolysis have not been well established.MethodsWe screened aerobic glycolysis-related gene modules by weighted gene co-expression network analysis (WGCNA) and established the aerobic glycolysis-related prognostic risk score (AGRS) by univariate Cox and lasso-Cox. In addition, enriched pathways, genomic mutation, and tumor-infiltrating immune cells were analyzed in AGRS subgroups and compared to each other. We also assessed chemotherapeutic drug sensitivity and immunotherapy response among two subgroups.ResultsAn aerobic glycolysis-related 14-gene prognostic model has been established. This model has good predictive prognostic performance both in the training dataset and in two independent validation datasets. Higher AGRS group patients had better immunotherapy response. Different AGRS patients were also associated with sensitivity of multiple prostate cancer chemotherapeutic drugs. We also predicted eight aerobic glycolysis-related small-molecule drugs by differentially expressed genes.ConclusionIn summary, the aerobic glycolysis-derived signatures are promising biomarkers to predict clinical outcomes and therapeutic responses in prostate cancer.</p