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Abstract Printable structural colors, originating from the interaction of light with micro- and nanostructures, have emerged as a promising approach for creating vibrant, durable, and environmentally friendly coloration. The mechanisms of natural structural colors are introduced. Current printing techniques, including nozzle-based and light-based methods, are discussed, along with their respective color generation strategies. These strategies are categorized into three main approaches: nanostructure self-assembly, high-resolution printing, and total reflection interfaces. Additionally, this review addresses the current challenges within the field for each strategy and proposes potential future directions for the development of printable structural colors. Graphical abstract 

Chirality, a fundamental attribute of asymmetry, pervades in both nature and functional soft materials. In chiral material systems design, achieving global symmetry breaking of building blocks during assembly, with or without the aid of additives, has emerged as a promising strategy across domains including chiral sensing, electronics, photonics, spintronics, and biomimetics. We first introduce the fundamental aspects of chirality, including its structural basis and symmetry-breaking mechanisms considering free energy minimization. We particularly emphasize supramolecular assembly, such as through the formation of chiral liquid crystal phases. Next, we summarize processing strategies to control chiral symmetry breaking, exploiting external fields such as flow, magnetic fields, and templates. The final section discusses interactions between chiral molecular assemblies with circularly polarized (CP) light and electronic spin and their applications in CP light detectors, CP-spin-organic light-emitting diodes, CP displays, and spintronic devices based on the chirality-induced spin selectivity effect. 

Abstract Conjugated polymers can undergo complex, concentration‐dependent self‐assembly during solution processing, yet little is known about its impact on film morphology and device performance of organic solar cells. Herein, lyotropic liquid crystal (LLC) mediated assembly across multiple conjugated polymers is reported, which generally gives rise to improved device performance of blade‐coated non‐fullerene bulk heterojunction solar cells. Using D18 as a model system, the formation mechanism of LLC is unveiled employing solution X‐ray scattering and microscopic imaging tools: D18 first aggregates into semicrystalline nanofibers, then assemble into achiral nematic LLC which goes through symmetry breaking to yield a chiral twist‐bent LLC. The assembly pathway is driven by increasing solution concentration – a common driving force during evaporative assembly relevant to scalable manufacturing. This assembly pathway can be largely modulated by coating regimes to give 1) lyotropic liquid crystalline assembly in the evaporation regime and 2) random fiber aggregation pathway in the Landau–Levich regime. The chiral liquid crystalline assembly pathway resulted in films with crystallinity 2.63 times that of films from the random fiber aggregation pathway, significantly enhancing the T80 lifetime by 50‐fold. The generality of LLC‐mediated assembly and enhanced device performance is further validated using polythiophene and quinoxaline‐based donor polymers. 

Abstract Many of the greatest challenges facing society today likely have molecular solutions that await discovery. However, the process of identifying and manufacturing such molecules has remained slow and highly specialist dependent. Interfacing the fields of artificial intelligence (AI) and synthetic organic chemistry has the potential to powerfully address both limitations. The Molecule Maker Lab Institute (MMLI) brings together a team of chemists, engineers, and AI‐experts from the University of Illinois Urbana‐Champaign (UIUC), Pennsylvania State University, and the Rochester Institute of Technology, with the goal of accelerating the discovery, synthesis and manufacture of complex organic molecules. Advanced AI and machine learning (ML) methods are deployed in four key thrusts: (1) AI‐enabled synthesis planning, (2) AI‐enabled catalyst development, (3) AI‐enabled molecule manufacturing, and (4) AI‐enabled molecule discovery. The MMLI's new AI‐enabled synthesis platform integrates chemical and enzymatic catalysis with literature mining and ML to predict the best way to make new molecules with desirable biological and material properties. The MMLI is transforming chemical synthesis and generating use‐inspired AI advances. Simultaneously, the MMLI is also acting as a training ground for the next generation of scientists with combined expertise in chemistry and AI. Outreach efforts aimed toward high school students and the public are being used to show how AI‐enabled tools can help to make chemical synthesis accessible to nonexperts. 

The fine balance between enhanced processability and decreased device performance in donor–acceptor polymeric semiconductors is elucidated using discrete siloxane side chains.