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Carbazole-linked through-space TADF emitters for OLEDs: tuning photophysics via molecular architecture and exciton dynamics
No full textThermally activated delayed fluorescence (TADF) offers a promising route to highly efficient organic light-emitting diodes (OLEDs), yet conventional D–A–D and A–D–A architectures often suffer from conformational flexibility, leading to multiple singlet excited states and enhanced non-radiative decay. These effects compromise both emission efficiency and color purity. While multi-resonant TADF (MR-TADF) systems provide improved rigidity, their planar structures favor π–π stacking, causing aggregation-induced quenching (ACQ). This study presents a molecular design strategy integrating a carbazole unit as a rigid, non-planar bridge to mitigate intramolecular rotation and suppress ACQ by disrupting parallel stacking. A set of 21 such D–A–D and A–D–A type molecules was computationally designed and analyzed. The optimized structures exhibit spatially separated frontier orbitals, resulting in small singlet–triplet energy gaps (ΔEST), fast radiative and reverse intersystem crossing rates, and near-unity photoluminescence quantum yields (PLQYs). Exciton dynamics simulations further confirm efficient TADF behavior, while molecular dynamics trajectories reveal conformational stability and through-space charge transfer characteristics. Notably, A1–D3–A1 achieves an exceptionally small ΔEST of 0.001 eV and the highest kTADF of 1.34 × 106 s−1, enabling rapid triplet harvesting, while D1–A2–D3 combines high oscillator strength with efficient TADF dynamics. These results demonstrate that subtle architectural tuning can yield substantial performance improvements, highlighting carbazole-bridged TADF emitters as a pathway toward stable, high-efficiency OLED materials
Detecting the early inspiral of a gravitational-wave signal with convolutional neural networks
No full textWe introduce a novel methodology for the operation of an early alert system for gravitational waves. It is based on short convolutional neural networks. We focus on compact binary coalescences, for light, intermediate and heavy binary-neutron-star systems. The signals are 1-dimensional time series - the whitened time-strain - injected in Gaussian noise built from the power-spectral density of the LIGO detectors at design sensitivity. We build short 1-dimensional convolutional neural networks to detect these types of events by training them on part of the early inspiral. We show that such networks are able to retrieve these signals from a small portion of the waveform
Integrated machine learning and hydrodynamic modeling for flood susceptibility mapping in the lower Narmada River Basin, India
No full textROS regulation of stigma papillae growth and maturation in Arabidopsis thaliana
No full textHighly specialized stigma papillae cells play a critical role in plant reproduction. Their main purpose is to catch and interact with pollen, to mediate compatibility responses, to regulate pollen germination, and to guide pollen tubes to the transmitting tract so that the sperm cells carried in the pollen can be delivered to the female gametophyte to achieve double fertilization. In Arabidopsis thaliana, the stigma consists of single-celled stigma papillae that emerge from the apex of the fused carpels. Despite their critical function in plant reproduction, the molecular mechanisms that govern growth and maturation of stigma papillae remain poorly understood. Reactive Oxygen Species (ROS) have been implicated in stigma receptivity, but their roles in papillae development are less explored. Here we show that reactive oxygen species (ROS) also play different roles in stigma papillae development, with superoxide accumulating during the initiation and growth phase and hydrogen peroxide accumulating in mature papillae that are receptive to pollen. Reducing superoxide levels in the stigma by pharmacological treatments or over-expressing superoxide dismutase enzymes under an early stigma promoter inhibited stigma papillae growth, suggesting that ROS homeostasis is critical to papillae growth and differentiation for optimal pollination
Cross-material synergies of carbon nanomaterials, MOFs, and COFs: Innovative approaches for sustainable environmental remediation and resource recovery
No full textSustainable environmental remediation and resource recovery are critical to addressing pollution, resource depletion, and ecosystem degradation. This review introduces the new concept of cross-material synergies, integrating carbon nanomaterials (CNMs), Metal-Organic Frameworks (MOFs), and Covalent Organic Frameworks (COFs) into multi-functional composite systems. By leveraging their complementary properties, these materials overcome key challenges such as structural instability, poor selectivity, and scalability limitations. Cross-material composites—including MOF@COF hybrids and CNM-MOF integrations—enhance adsorption performance, stability, and reusability compared to their individual components. Our review demonstrate how these hybrid systems improve pollutant removal, catalytic degradation, and resource recovery, aligning with sustainability goals. Their ability to transform waste into valuable materials supports circular economy principles and key Sustainable Development Goals (SDGs), including SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). Furthermore, the review highlights strategies for optimising material performance, ensuring industrial scalability, and minimising environmental impact through Safe and Sustainable by Design (SSbD) approaches. Unlike previous reviews that focus on individual materials, this work provides a holistic roadmap for designing and deploying cross-material composites for real-world applications. By bridging fundamental research with industrial implementation, these systems present a transformative step toward sustainable material science, with far-reaching implications for environmental remediation and resource recovery. Future research should focus on enhancing synthesis efficiency, ensuring long-term material stability, and addressing economic feasibility for large-scale deployment
