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Graphitic carbon nitride (g-C3N4) has gained significant attention as a promising nonmetallic semiconductor photocatalyst due to its photochemical stability, favorable electronic properties, and efficient light absorption. Nevertheless, its practical applications are hindered by limitations such as low specific surface area, rapid recombination of photogenerated charge carriers, poor electrical conductivity, and restricted photo-response ranges. This review explores recent advancements in the synthesis, modification and application of g-C3N4 and its nanocomposites with a focus on addressing these challenges.

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Effect of Temperature on Condensed State Structure and Conductivity Characteristics of Micron-Level Biaxially Oriented Polypropylene Films.

ACS Appl Mater Interfaces

January 2025

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.

Polymer-based dielectric films are increasingly demanded for devices under high electric fields used in new energy vehicles, photovoltaic grid connections, oil and gas exploration, and aerospace. However, leakage current is one of the significant factors limiting the improvement of the insulation performance. This paper tested the leakage current and condensed state structure characteristics of biaxially oriented polypropylene (BOPP) films and obtained the nonlinear characteristics of leakage current of BOPP films in the range of 40-440 V/μm and 40-110 °C.

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Mechanical Modulation of S-S and S-T Energy Gaps of 11- and All- Retinal Schiff Bases.

J Phys Chem B

January 2025

Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Alcalá de Henares, Madrid E-28871, Spain.

The retinal Schiff base is a chromophore of significant biological relevance, as it is responsible for capturing sunlight in rhodopsins, which are photoactive proteins found in various living organisms. Additionally, this chromophore is subjected to various mechanical forces in different proteins, which alter its structure and, consequently, its properties. To thoroughly understand the mechanical response limits of the retinal excitation energy, a simple first-order formalism has been developed to quantify the chromophore's optimal mechanical response to applied external forces (on the order of tens of pN).

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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors.

PLoS One

January 2025

Renewable Energy Science and Engineering Department, Faculty of Postgraduate Studies for Advanced Sciences (PSAS), Beni-Suef University, Beni-Suef, Egypt.

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE).

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This brief report aimed to investigate the optical absorbance spectra of normal, dysplastic, and malignant epithelial cell lines under normal and nutritional stress conditions. HaCAT (keratinocyte), DOK (oral dysplastic), and oral squamous cell carcinoma (OSCC) cell lines (CA1, Luc4, SCC9) were evaluated regarding their optical absorbance after culture with 0-10% fetal bovine serum. Absorbance measurements indicated that HaCAT under serum starvation exhibited higher absorbance at blue (430 nm) and near-infrared (906 nm) wavelengths.

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