Photochemistry of [Ru(pytz)(btz)₂]²⁺ and Characterization of a κ¹‑btz Ligand-Loss Intermediate

We report the synthesis, characterization, and photochemical reactivity of the triazole-containing complex [Ru­(pytz)­(btz)₂]²⁺ (<b>1</b>, pytz = 1-benzyl-4-(pyrid-2-yl)-1,2,3-triazole, btz = 1,1′-dibenzyl-4,4′-bi-1,2,3-triazolyl). The UV–vis absorption spectrum of <b>1</b> exhibits pytz- and btz-centered ¹MLCT bands at 365 and 300 nm, respectively. Upon photoexcitation, acetonitrile solutions of <b>1</b> undergo conversion to the ligand-loss intermediate, <i>trans</i>-[Ru­(pytz)­(κ²-btz)­(κ¹-btz)­(NCMe)]²⁺ (<b>2</b>, Φ₃₆₃ = 0.013) and ultimately to the ligand-loss product <i>trans</i>-[Ru­(pytz)­(btz)­(NCMe)₂]²⁺ (<b>3</b>), both of which are observed and characterized by ¹H NMR spectroscopy. Time-dependent density functional theory calculations reveal that the S₁ state of the complex has primarily HOMO → LUMO pytz-based ¹MLCT character. Data show that the ³MLCT and ³MC states are in close energetic proximity (≤0.11 eV to 2 d.p.) and that the T₁ state from a single-point triplet state calculation at the S₀ geometry suggests ³MC character. Optimization of the T₁ state of the complex starting from the ground state geometry leads to elongation of the two Ru–N­(btz) bonds <i>cis</i> to the pytz ligand to 2.539 and 2.544 Å leading to a pseudo-4-coordinate ³MC state rather than the ³MLCT state. The work therefore provides additional insights into the photophysical and photochemical properties of ruthenium triazole-containing complexes and their excited state dynamics

The risks of using ChatGPT to obtain common safety-related information and advice

ChatGPT is a highly advanced AI language model that has gained widespread popularity. It is trained to understand and generate human language and is used in various applications, including automated customer service, chatbots, and content generation. While it has the potential to offer many benefits, there are also concerns about its potential for misuse, particularly in relation to providing inappropriate or harmful safety-related information. To explore ChatGPT's (specifically version 3.5) capabilities in providing safety-related advice, a multidisciplinary consortium of experts was formed to analyse nine cases across different safety domains: using mobile phones while driving, supervising children around water, crowd management guidelines, precautions to prevent falls in older people, air pollution when exercising, intervening when a colleague is distressed, managing job demands to prevent burnout, protecting personal data in fitness apps, and fatigue when operating heavy machinery. The experts concluded that there is potential for significant risks when using ChatGPT as a source of information and advice for safety-related issues. ChatGPT provided incorrect or potentially harmful statements and emphasised individual responsibility, potentially leading to ecological fallacy. The study highlights the need for caution when using ChatGPT for safety-related information and expert verification, as well as the need for ethical considerations and safeguards to ensure users understand the limitations and receive appropriate advice, especially in low- and middle-income countries. The results of this investigation serve as a reminder that while AI technology continues to advance, caution must be exercised to ensure that its applications do not pose a threat to public safety.</p