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The quantum well diode (QWD) performs a dual role, functioning both as an emitter and a detector due to its unique feature of spectral overlap between emission and detection spectra. This dual functionality positions QWDs as promising candidates in the realm of multifunctional sensors. Furthermore, the well-established maturity of optical fiber communication, grounded in its intrinsic property of total reflection, makes it an ideal transmission medium for QWD sensing signals. Leveraging the coexisting emission and detection capabilities of QWDs, we have constructed a sensing system in this article. This system utilizes a QWD, which is stimulated to emit light, with the emitted light traveling through a specified length of optical fiber. A specialized load-bearing film, featuring an aluminum membrane on its rear to act as a mirror and an object of known weight on its front, induces deformation in the film, thereby altering the characteristics of the reflected light. This modulated light is subsequently captured by the QWD via the optical fiber, enabling the computation of the weight of the object. In this article, the QWD's emission peak is around 522 nm, and its detection range extends from 370 to 530 nm. Furthermore, by employing the appropriate approach, integrating QWD with optical fibers can be extended to sensing and measuring various physical quantities such as temperature, solution concentration, wind speed, and more. The advantages of QWDs include cost-effectiveness, multifunctionality, portability, and environmental friendliness. This technology represents a promising avenue for sensor control in the era of the Internet of Things. [ABSTRACT FROM AUTHOR]

Photoresponsive drug delivery stands as a pivotal frontier in smart drug administration, leveraging the non-invasive, stable, and finely tunable nature of light-triggered methodologies. The generative pre-trained transformer (GPT) has been employed to generate molecular structures. In our study, we harnessed GPT-2 on the QM7b dataset to refine a UV-GPT model with adapters, enabling the generation of molecules responsive to UV light excitation. Utilizing the Coulomb matrix as a molecular descriptor, we predicted the excitation wavelengths of these molecules. Furthermore, we validated the excited state properties through quantum chemical simulations. Based on the results of these calculations, we summarized some tips for chemical structures and integrated them into the alignment of large-scale language models within the reinforcement learning from human feedback (RLHF) framework. The synergy of these findings underscores the successful application of GPT technology in this critical domain. [ABSTRACT FROM AUTHOR]

Repurposing enzymes to catalyze non‐natural asymmetric transformations that are difficult to achieve using traditional chemical methods is of significant importance. Although radical C−O bond formation has emerged as a powerful approach for constructing oxygen‐containing compounds, controlling the stereochemistry poses a great challenge. Here we present the development of a dual bio‐/photo‐catalytic system comprising an ene‐reductase and an organic dye for achieving stereoselective lactonizations. By integrating directed evolution and photoinduced single electron oxidation, we repurposed engineered ene‐reductases to steer non‐natural radical C−O formations (one C−O bond for hydrolactonizations and lactonization‐alkylations while two C−O bonds for lactonization‐oxygenations). This dual catalysis gave a new approach to a diverse array of enantioenhanced 5‐ and 6‐membered lactones with vicinal stereocenters, part of which bears a quaternary stereocenter (up to 99 % enantiomeric excess, up to 12.9 : 1 diastereomeric ratio). Detailed mechanistic studies, including computational simulations, uncovered the synergistic effect of the enzyme and the externally added organophotoredox catalyst Rh6G. [ABSTRACT FROM AUTHOR]