Colorimetric Assay for Determination of Lead (II) Based on Its Incorporation into Gold Nanoparticles during Their Synthesis

In this report, we present a new method for visual detection of Pb2+. Gold nanoparticles (Au-NPs) were synthesized in one step at room temperature, using gallic acid (GA) as reducer and stabilizer. Pb2+ is added during the gold nanoparticle formation. Analysis of Pb2+ is conducted by a dual strategy, namely, colorimetry and spectrometry. During Au-NPs synthesis, addition of Pb2+ would lead to formation of Pb-GA complex, which can induce the aggregation of newly-formed small unstable gold nanoclusters. Consequently, colorimetric detection of trace Pb2+ can be realized. As the Pb2+ concentration increases, the color turns from red-wine to purple, and finally blue. This method offers a sensitive linear correlation between the shift of the absorption band (Δλ) and logarithm of Pb2+ concentration ranging from 5.0 × 10−8 to 1.0 × 10−6 M with a linear fit coefficient of 0.998, and a high selectivity for Pb2+ detection with a low detection limit down to 2.5 × 10−8 M

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

InN nanoflowers grown by metal organic chemical vapor deposition

Hexangular indium nitride nanoflower pattern is observed from scanning electron microscopy and atomic force microscopy. The sample is grown on c-plane (0001) sapphire by metal organic chemical vapor deposition with intentional introduction of hydrogen gas. With the aid of hydrogen, a stable existence of metallic indium is achieved. This will induce the growth of InN nanoflowers via self-catalysis vapor-liquid-solid (VLS) process. It is found that the VLS process is modulated by the interface kinetics and thermodynamics among the sapphire substrate, indium, and InN, which leads to the special morphology of the authors' InN nanoflower pattern. (c) 2006 American Institute of Physics