Yuebing Zheng

Surface lattice resonances (SLRs) in metasurfaces have become a transformative platform for subwavelength optical devices. However, current high quality-factor (high-Q) SLR implementations are fundamentally limited by their dependence on homogeneous dielectric environments. To overcome this limitation, we introduce guided-surface lattice resonances (gSLRs) by integrating nanoparticle arrays within slab waveguides. This configuration facilitates efficient coupling between scattered light and Bloch modes, enabling high-Q multimodal resonances even in index-discontinuous environments, realizing a quality-factor (Q-factor) of 1489. The coupling strength and resonance intensity of these multimodal gSLRs can be continuously modulated by adjusting the vertical displacement of the nanoparticle arrays within the slab layers. To augment the sensitivity to local dielectric variations, we investigate gSLRs in metasurfaces integrated with metallic substrates, demonstrating suitability for biosensors. A mathematical sensing model, incorporating biochemical reaction kinetics and optical responses, is established and validated through bovine serum albumin (BSA) sensing, achieving a limit-of-detection as low as 0.65 pM.

High-entropy alloys (HEAs) provide broad compositional tunability for electrocatalysis, but conventional synthesis is energy-intensive, batch-limited, and requires postprocessing. A laser-directed bubble-printing method is introduced for the direct, ambient-condition fabrication of HEA catalysts on conductive substrates with microscale precision. Unlike conventional powder-based syntheses, bubble-printing enables in situ substrate growth through optothermal bubble confinement, combining ion accumulation and localized hydrothermal reactions. Using this approach, CuFeRhPdPt alloys are synthesized that exhibit a short-range ordered face-centered cubic microstructure, as confirmed by scanning transmission electron microscopy and selected-area electron diffraction. The printed alloys demonstrate efficient hydrogen evolution reaction (HER) activity in acidic media, achieving overpotentials of 5.23 and 18.49 mV at −10 and −200 mA·cm geo –2, respectively, with a corresponding Tafel slope of 27.3 mV·dec –1 . These results demonstrate competitive HER performance relative to reported multimetallic catalysts under comparable conditions. Bubble-printing enables high-throughput discovery of HEA electrocatalysts, with tunable stoichiometry and combinatorial arrays applicable to reactions beyond the HER.

Acoustic tweezers can transport particles along arbitrarily defined paths with unprecedented robustness across defects and sharp corners.

Colloidal particles emerge as promising building blocks for the construction of novel materials and devices owing to their tailorable morphologies, abundant species, and intriguing properties. In comparison to other assembly approaches, optical colloidal assembly relies on photophysical or photochemical interactions and allows the arrangement of particles into desired geometries on a substrate with high spatial and temporal resolution. Typically, optical colloidal assembly involves two major processes, i.e., optical manipulation for colloidal arrangement and light-triggered interparticle bonding for colloidal immobilization. In this review, we first categorize the optical manipulation techniques based on different working principles and discuss their technical features and assembly capabilities. We then provide a comprehensive overview of different colloidal bonding schemes, including van der Waals attraction, dipole-dipole interaction, biochemical linking, photopolymerization, and surface ligand bonding. Finally, we summarize the cutting-edge applications of assembled colloidal structures and end with our vision for the existing challenges and future development in this field.

Precise and scalable enrichment of dispersed analytes is vital for biosensing, environmental monitoring, and nanomaterial processing. However, current methods often lack versatility and spatial resolution. Here, we introduce optothermal ice-water interface management (OIIM), a universal, label-free approach for cross-scale enrichment and sensing. By optically guiding a movable ice-water interface, OIIM creates a tunable and controllable nanovessel that actively drives analytes, from angstrom-scale dyes to micrometer-scale particles, into confined regions. This versatile approach efficiently enriches diverse targets, including nucleotides, proteins, and synthetic nanomaterials. Molecular dynamics simulations and fluorescence imaging have been investigated to elucidate the solute-interface interactions and the enhanced interfacial trapping underlie the observed enrichment behavior. Furthermore, OIIM supports multisite enrichment, spatial consolidation, and the formation of femtoliter-scale microreactors for accelerated enzyme-cascade reactions. Notably, OIIM offers unique capabilities for enriching and analyzing ultrashort nucleic acids that elude conventional purification methods, establishing a flexible, molecular-level optothermal strategy within ice.

In the early positioning method of unmanned aerial vehicle inspection tree obstacles under the three-dimensional reconstruction of distribution network corridors, the pixel gradient changes are calculated with the potential feature area as the center, and the gradient amplitude and direction are calculated to form feature vectors; Using feature similarity matching algorithm to complete image registration and logical operation to extract tree obstacle images, constructing UAV kinematic equations, obtaining tracking time-domain function through Laplace transform, determining tree obstacle positioning position, and achieving accurate positioning. The experimental results show that the design method is effective in path planning, with a path length of approximately 115 meters for 10 tree obstacle points and 135 meters for 20 tree obstacle points, both avoiding the no fly zone and being close to the tower within 2.5 meters. In the data verification, 5 gathering areas were accurately identified, and 12 dangerous points were marked in the S1 gathering area. In terms of positioning results, the accuracy of data such as safe distance, height deviation, and horizontal offset distance of each location point proves that the method can effectively improve the efficiency of early positioning of tree obstacles.

Tightly focused Gaussian beams are the cornerstone of traditional optical tweezers. Flat-top beams also enable consummate control of particles over a two-dimensional plane. The former depends on the intensity gradient, while the latter the phase gradient. Here we present a promising alternative for micro/nano-manipulation that complement the phase gradient force in a flat-top beam: utilizing the light-recoiling, particle can be reversibly manipulated or trapped, even along directions without phase or intensity gradients. Typically, these photon-recoil forces are dependent heavily on the details of the microscopic structures of matter, thus limiting both their tunability and reversibility. The photon-recoil-based manipulation technique (PMT) we develop utilizes polarization modulation to exert tunable and reversible lateral forces on simple nanospheres by shaping the imaginary Poynting momentum (IPM) in a flat-top beam. By harnessing recoil forces arising from IPM, our PMT creates edge-specific pathways, enabling tunable driving forces for nanoparticle transport and the formation of stable potential wells. Furthermore, PMT makes it possible to achieve negative optical torque on single nanowires, thereby overcoming previous limitations and opening different avenues in optical manipulation.

Abstract CRISPR–Cas systems are central to prokaryotic adaptive immunity, widely harnessed for biotechnology. Yet, their vast and uncharacterized diversity, especially non-canonical variants, impedes full exploitation. Here we present BioPrinCRISPR, a class-agnostic computational framework leveraging gene co-conservation, protein domain co-occurrence, and embedding similarity to identify and characterize CRISPR–Cas systems across prokaryotic genomes. Applying BioPrinCRISPR to over one million bacterial genomes, we uncovered extensive canonical and uncharacterized systems, revealing a rich landscape of atypical Cas proteins and novel domain architectures. Notably, we identified recurrent fusion proteins with unique enzymatic combinations, suggesting roles in regulatory control or nucleic acid remodeling. Experimental validation of two divergent Cas13an-like effectors demonstrated RNA knockdown capacity in human cells, confirming our framework’s predictive power. These findings expand the functional repertoire of CRISPR-associated proteins and highlight unexplored modes of microbial immunity. BioPrinCRISPR thus stands as a powerful tool for comprehensively mapping CRISPR–Cas diversity, offering new insights into prokaryotic defense and facilitating discovery of novel candidates for next-generation genome engineering. An accompanying interactive web platform was also developed to facilitate data exploration.

Bubble etching introduces a sustainable, on-demand nanomanufacturing solution that addresses critical challenges in the field, such as the high cost, limited design flexibility, and environmental impact of conventional mask-based lithography. This maskless, laser-driven technique utilizes laser-generated bubbles as localized reactors for precise, high-resolution patterning. By integrating optothermal manipulation with controlled chemical etching, bubble etching enables customizable fabrication while significantly reducing chemical waste and energy consumption. Advancing green nanomanufacturing, this method provides a scalable and environmentally friendly approach for producing next-generation materials and devices.

Opto-thermoelectric nanotweezers (OTENT) have emerged as a versatile tool for nanoscale trapping and particle manipulation. Leveraging the high-throughput and large-scale trapping capabilities of OTENT, this study integrates a periodic opto-thermoelectric lattice with a microfluidic channel to achieve precise nanoparticle sorting based on size and composition. Dynamic manipulation is facilitated by the generation of periodic potential wells through holographic optical tweezers, enabling kinetically locked-in states for nanoparticles. By strategically varying the orientation of the trap array relative to an external driving force, this approach can effectively isolate nanoparticles smaller than 200nm, a size range that presents significant challenges for conventional optical techniques. This method enhances the selectivity and efficiency of nanoparticle manipulation, opening new opportunities for advancements in nanotechnology, materials science, and biomedical research.

We introduce a groundbreaking, free-form optothermocapillary manipulation platform for C. elegans research, addressing key limitations of traditional microfluidic-based methods. C. elegans, a model organism crucial in studies of Alzheimer's disease, drug delivery, behavior, and axon regeneration, is traditionally constrained by microfluidic devices that require labor-intensive fabrication and limit worm orientation and interaction. Our innovative technique leverages laser-generated microbubbles on a gold nano-island substrate, providing scalable, biocompatible manipulation across all developmental stages. This platform enables total immobilization for in vivo imaging, tail pinning for observing omni-directional responses, and precise translational control for multi-worm behavioral studies. By overcoming the limitations of conventional approaches, this sustainable and adaptable platform paves the way for studying complex biological phenomena and advancing C. elegans research.

Abstract The electroreduction of uranyl ions from seawater is a promising and sustainable method to smelt uranium (U) for the nuclear power industry. However, electrostatic repulsion prevents conventional catalytic centers in terms of nanoparticles and cations from making full contact with uranyl ions, leading to poor uranium extraction performance of the electrode materials. Herein, molybdate anions serving as electronegative catalytic centers are integrated into a porous aromatic framework to obtain the porous electrode (Mo@PAF‐6). The metalate anions in Mo@PAF‐6 bind U(VI) cations in the form of Mo─O─U bonds; since the relative distance is limited in the range of 3−4 Å, U(VI) is electrically reduced to U(V) and precipitated as charge‐neutral species. Mo@PAF‐6 outperforms conventional catalysts with electropositive metal centers by 100% for uranium extraction in an 8 ppm uranium‐spiked solution. Moreover, the uranium extraction capacity of Mo@PAF‐6 in real seawater reaches 24.21 mg g −1 during 56 days‐contact, far exceeding that of the classical poly(amidoxime)‐based electrode by a factor of ≈12 000.

Uranium plays an important role in the modern nuclear industry. However, such a radioactive element can also cause severe damage to the environment once leaked or discharged into water or air, having a huge impact on the safety of the biosphere. In this work, we pioneered the use of fluorescent monomers as imprinted units, which promoted fluorescence emission of the material. A novel porous aromatic framework was obtained with uranyl ion chelating sites, namely MIPAF-15. The unique N-O chelating pockets on the 4-bromo-1-H-indole-7-carboxylic acid gave rise to high coordination affinity toward uranyl ions, which enabled the fast adsorption rate of uranyl ions and a uranyl ion adsorption capacity of 44.88 mg·g−1 at 298 K with an initial pH value of 6.0 and the uranyl concentration of 10 ppm. At the same time, the fluorescence quenching effect of MIPAF-15 was observed upon its adsorption of uranyl ions, which allowed the selective detection of uranyl ions with a detection limit of 5.04 × 10−8 M, lower than the maximum concentration of uranyl ions in drinking water specified by the World Health Organization (6.30 × 10−8 M) and United States Environmental Protection Agency (1.11 × 10−7 M). This kind of multifunctional porous material produces a favorable pathway for the detection, removal and degeneration of highly pollutive ions, promoting the overall sustainable development of the natural environment.

Abstract Dynamic thermal management materials are pivotal for advancing energy‐efficient buildings and promoting global sustainability. However, existing materials typically offer only a single‐function of temperature regulation, lacking the integrated power supply capability essential for sustaining indoor activities and building sustainability, particularly in the face of frequent power outages. A photonic battery that combines all‐season dynamic radiative thermoregulation with electrical power supply in a single silicon‐based unit is demonstrated. This device delivers dual functionality with high infrared emissivity regulation (0.53 at 8–13 µm) and superior energy storage performance, featuring a high specific capacity (≈3271 mAh g −1 ), areal capacity (≈0.38 mAh cm −2 ), and efficient energy recycling (71.6%). A reversible ion‐interaction‐induced phase change mechanism, enabling continuous and non‐volatile electro‐optical‐thermal transformation and significant infrared tunability, is proposed. Our simulations indicate that the implementation of these dynamic materials into buildings could significantly reduce energy consumption by up to 18.4%, equating to 544.8 GJ, and achieve an annual reduction in CO 2 emissions of 124.1 tons. This work paves the way for the development of energy‐saving electro‐driven dynamic materials, marking a significant step forward in global sustainability initiatives.

Multivalent strategies have been widely applied in the microfluidic interface to boost the capture efficiency of target cells. However, achieving a balance between binding kinetics and thermodynamics in existing multivalent affinity interfaces remains challenging. Here, we propose a synergistic A ptamer-nanobody hetero- M ultivalency P rogrammable magnetic fluid microfluidic chip ( AMP-chip ) which utilizes the combined advantages of ligands to enhance both thermodynamic and kinetic properties of the capture interface. The AMP-chip integrates two distinct noninterfering recognition molecules: one with high affinity and another with rapid binding capability, both of which are assembled onto nanomagnetic beads. This integration achieves intermolecular complementarity, effectively enhancing the binding kinetics and thermodynamic stability. We chose mutually noninterfering CD71 recognition targets, a high-affinity nanobody (NB) and a rapid-binding aptamer (XQ 2d), and fully utilized the respective advantages of these ligands to facilitate rapid and tight recognition of the CD71 receptor on target cells. By integrating a herringbone microarray into an AMP-chip to further increase the cell–ligand interaction, we significantly improved the sensitivity and accuracy of circulating nucleated red blood cell (cNRBC) isolation from the peripheral blood mononuclear cells (PBMCs) of pregnant women. Additionally, the ligands were primarily fixed to the chip by magnetic force without chemical bonding, enabling nondestructive cell release and preserving high cell viability for subsequent molecular analyses. Overall, this approach offers a novel thermodynamic–kinetic synergistic heteromultivalency interface with significant potential for clinical applications.

Abstract Biomimetic nanochannels enable fast and selective transport of mononuclear metal ions; however, their construction for complex ion transport remains in its infancy due to the nonuniform charge distribution and large geometric dimensions of coordination compounds. Herein, an ionic electrostatic interaction template strategy is proposed to prepare biomimetic channels for the capture of complex ions. Using the [UO 2 (CO 3 ) 3 ] 4− ion as a template, various quaternary ammonium monomers with lengths of 6.2−8.4 Å are decorated on 1D porous channels of the TpBDOH framework via the Williamson ether reaction. Accordingly, the pore size is modulated in the sub‐nanometer range of 9−13 Å, facilitating multiple electrostatic attractions between quaternary ammonium fragments and the three equatorial carbonate ions on the [UO 2 (CO 3 ) 3 ] 4− ion. The unique structure enabled highly efficient uranium adsorption with a capacity of 501.5 mg g −1 and a high selectivity coefficient for uranium over vanadium of >163.1. The resulting electropositive nanochannels selectively captured [UO 2 (CO 3 ) 3 ] 4− ions from natural seawater, achieving a high uptake of 25.3 mg g −1 in 35 days.

We report on a double moiré system consisting of four graphene layers, where the top and bottom pairs form small-twist-angle bilayer graphene, and the middle interface has a large rotational mismatch. This system shows clear signatures of two sets of spatially separated flat bands associated with the top and bottom twisted bilayer graphene subsystems, each independently tunable. Thermodynamic analysis reveals weak correlations between bilayers that allow the chemical potential to be measured as a function of carrier density for each constituent TBG. We find that correlated insulating states at integer number of electrons per moiré unit cell are most robust near magic angle, whereas gapped states at neutrality are more robust at larger twist angles.

Additive Manufacturing (AM) represents an innovative technique for producing tangible components through a layer-by-layer aggregation process guided by three-dimensional (3D) Computer-Aided Design (CAD) data [ 1 , 2 ]. This sophisticated manufacturing approach offers numerous distinct advantages, including high degrees of design flexibility, superior material utilization ratio, compatibility with various materials, and reduced production cycles. These benefits endow AM with remarkable potential and economic viability across diverse sectors, notably in medical devices [ 1 , 3 ], micromaking strategies [ 1 ], and artificial organs [ 1 ]. Recent years have witnessed the advent of several AM methodologies; among them, Volumetric Additive Manufacturing (VAM) stands out [ 4 ]. VAM involves the conversion of 3D object tomography into two-dimensional images, which are subsequently reconstructed holograph-ically and integrated into stereolithographic slices. These slices are sequentially projected into a rotating printing vessel, enabling rapid, non-contact printing. This technique facilitates the creation of components that do not require support structures and permits overlay printing on pre-existing constructs. Compared to conventional AM processes, VAM significantly saves time. However, VAM faces several challenges, such as limited material selection, predominantly restricted to photosensitive resins, and a paucity of commercially available equipment, which hampers its application beyond laboratory settings. Furthermore, the absence of standardized methods for evaluating VAM-fabricated components

Abstract Fano resonances in photonics arise from the coupling and interference between two resonant modes in structures with broken symmetry. They feature an uneven and narrow and tunable lineshape and are ideally suited for optical spectroscopy. Many Fano resonance structures have been suggested in nanophotonics over the last ten years, but reconfigurability and tailored design remain challenging. Herein, an all‐optical “pick‐and‐place” approach aimed at assembling Fano metamolecules of various geometries and compositions in a reconfigurable manner is proposed. Their coupling behavior by in situ dark‐field scattering spectroscopy is studied. Driven by a light‐directed opto‐thermoelectric field, silicon nanoparticles with high‐quality‐factor Mie resonances (discrete states) and low‐loss BaTiO 3 nanoparticles (continuum states) are assembled into all‐dielectric heterodimers, where distinct Fano resonances are observed. The Fano parameter can be adjusted by changing the resonant frequency of the discrete states or the light polarization. Tunable coupling strength and multiple Fano resonances by altering the number of continuum states and discrete states in dielectric heterooligomers are also shown. This work offers a general design rule for Fano resonance and an all‐optical platform for controlling Fano coupling on demand.

Maintenance of temperature within a suitable range is essential for human activity, and thermal management is the science dedicated to this goal. From an optical point of view, thermal management requires engineered photonic materials with versatile responses over the broad solar and thermal spectra to perform complex functions, including cooling, heating, energy conversion, camouflage, and dynamic control of heat flow, many of which are highly desirable in renewable energy research. The sophisticated spectral requirements of these applications pose fundamental challenges in materials design. While advances in computational methods have led to many technological breakthroughs, a parallel route-drawing inspiration from biological systems-has also yielded impressive progress. Guided by the unmatched power of natural selection, biomimetic approaches facilitate the development of high-performance bioinspired materials with intricate hierarchical architectures. In this review, we present the concepts and recent advances in biomimetic photonic materials and strategies for thermal management, along with our perspectives on the current challenges and future directions. The engineering principles evolved in nature to meet complex spectral demands are also broadly applicable to other applications involving ultra-broadband and band-selective optical responses.

studies showed that chronic wounds on C57 mice treated with CS/HA-bilayer MNs achieved nearly complete healing by day 9. These wounds exhibited reduced inflammatory cell infiltration, increased epithelial tissue regeneration, and enhanced collagen deposition. This work integrates the staged management of bacterial infection and angiogenesis and offers promising prospects for enhancing chronic wound healing.

The utilization of uranium (U) fission energy as a high-density, clean power source plays a pivotal role in mitigating greenhouse gas emissions. Uranium extraction from seawater exhibits superior environmental friendliness compared to terrestrial uranium mining, as it avoids substantial generation of radioactive waste and harmful chemicals. However, conventional adsorbents such as fiber, polymer, and biomass materials exhibit slow adsorption rates and low ion selectivity. Porous frameworks with large inner surface, full host-guest interaction, and site utilization are utilized to improve uranium absorption performance. Consequently, devising and synthesizing materials that enable efficient and cost-effective extraction of U(VI) from seawater poses a formidable challenge. Recently, there has been a considerable surge in academic interest regarding the synthesis and design of porous frameworks. By integrating experimental data, spectroscopic analysis, and theoretical calculations, we have conducted an extensive investigation into the actual performance, underlying principles, and practicality of conventional materials (such as fibers) and novel porous materials serving as adsorbents, photocatalysts, and electrocatalysts for U(VI) extraction from seawater.

Optical Microrobotic Swarms in Complex Environments Yuebing Zheng and co-workers (see article number 2400409) introduce a novel control strategy that autonomously navigates microrobotic swarms over long distances in complex environments, ensuring swarm integrity and improving obstacle avoidance. This approach addresses challenges like swarm collapse and particle immobilization, enhancing the robustness of the microrobotic system. The strategy paves the way for advanced applications such as precise drug delivery, nanosurgery, and the study of collective motions.

High-quality (Q)-factor optical resonators with extreme temporal coherence are of both technological and fundamental importance in optical metrology, continuous-wave lasing, and semiconductor quantum optics. Despite extensive efforts in designing high-Q resonators across different spectral regimes, the experimental realization of very large Q-factors at visible wavelengths remains challenging due to the small feature size that is sensitive to fabrication imperfections, and thus is typically implemented in integrated photonics. In the pursuit of free-space optics with the benefits of large space-bandwidth product and massive parallel operations, here we design and fabricate a near-visible-wavelength etch-free metasurface with minimized fabrication defects and experimentally demonstrate a million-scale ultrahigh-Q resonance. A new laser-scanning momentum-space-resolved spectroscopy technique with extremely high spectral and angular resolution is developed to characterize the record-high Q-factor as well as the dispersion of the million-Q resonance in free space. By integrating monolayer WSe2 into our ultrahigh-Q meta-resonator, we further demonstrate laser-like highly unidirectional and narrow-linewidth exciton emission, albeit without any operating power density threshold. Under continuous-wave laser pumping, we observe pump-power-dependent linewidth narrowing at room temperature, indicating the potential of our meta-optics platform in controlling coherent quantum light-sources. Our result also holds great promise for applications like optical sensing, spectral filtering, and few-photon nonlinear optics. Free-space meta-optics with ultrahigh quality(Q)-factor at visible wavelengths is demanded but very challenging to achieve due to the fabrication imperfections. Here, the authors design an etch-free metasurface with minimized fabrication defects and experimentally demonstrate a million-Q resonance at 779 nm wavelength.

Learning progressions divide the logical system of a subject into ordered and continuously developing levels that are suitable for the cognitive development level of students, which plays an important role in understanding students’ learning process. This paper focuses on the theme of “kinetic energy” in high school physics as the research object. Firstly, the concept map was used to represent the relationship between knowledge, and then five core concepts were selected based on the opinions of high school teachers. Secondly, the test tools were compiled and tested based on the relevant test questions. Finally, the paper analyzed the results based on the Rasch model, clarified students’ cognitive development level of “kinetic energy” and constructed the learning progressions of “kinetic energy” based on the logical order of subject knowledge. The research provides theoretical and methodological support for the study of other subjects and learning progressions, and provides a valuable reference for high school teachers to effectively carry out the instruction of “kinetic energy.”

We report on a double moiré system consisting of four graphene layers, where the top and bottom pairs form small-twist-angle bilayer graphene, and the middle interface has a large rotational mismatch. This system shows clear signatures of two sets of spatially separated flat bands associated with the top and bottom twisted bilayer graphene (TBG) subsystems, each independently tunable. Thermodynamic analysis reveals weak correlations between layers that allow the chemical potential to be measured as a function of carrier density for each constituent TBG. We find that correlated insulating states at integer number of electrons per moiré unit cell are most robust near magic angle, whereas gapped states at neutrality are more robust at larger twist angles.

In exploring the genesis of life, liquid-liquid phase-separated coacervate droplets have been proposed as primitive protocells. Within the hydrothermal hypothesis, these droplets would emerge from molecule-rich hot fluids and thus be subjected to temperature gradients. Investigating their thermophoretic behavior can provide insights into protocell footprints in thermal landscapes, advancing our understanding of life's origins. Here, we report the thermophilic behavior of heat-dissociative droplets, contrary to the intuition that heat-associative condensates would prefer hotter areas. This aspect implies the preferential presence of heat-dissociative primordial condensates near hydrothermal environments, facilitating molecular incorporation and biochemical syntheses. Additionally, our investigations reveal similarities between thermophoretic and electrophoretic motions, dictated by molecular redistribution within droplets due to their fluid nature, which necessitates revising current electrophoresis frameworks for surface charge characterization. Our study elucidates how coacervate droplets navigate thermal and electric fields, reveals their thermal-landscape-dependent molecular characteristics, and bridges foundational theories of early life: the hydrothermal and condensate-as-protocell hypotheses.

Chirality at the nanoscale has emerged as a key area of interest in materials science and engineering, with significant implications for various fields such as spintronics, photonics, optoelectronics, quantum computing, and biomedicine. With their unique properties such as enantioselective interactions with light and spin-polarized electron transport, chiral nanomaterials are opening a new window of opportunities for the design of advanced functional devices. This editorial provides an overview of the current state of research in chirality in nanomaterials. We also showcase several papers from this collection that exemplify the breadth of current work, offering insights into the future directions of this rapidly evolving field.

Machine learning techniques have gained popularity in nanophotonics research, being applied to predict optical properties, and inversely design structures. However, one limitation is the cost of acquiring training data, as complex structures require time-consuming simulations. To address this, researchers have explored using transfer learning, where pre-trained networks can facilitate convergence with fewer data for related tasks, but application to more difficult tasks is still limited. In this work, a nested transfer learning approach is proposed, training models to predict structures of increasing complexity, with transfer between each model and few data used at each step. This allows modeling thin film stacks with higher optical complexity than previously reported. For the forward model, a bidirectional recurrent neural network is utilized, which excels in modeling sequential inputs. For the inverse model, a convolutional mixture density network is employed. In both cases, a relaxed choice of materials at each layer is introduced, making the approach more versatile. The final nested transfer models display high accuracy in retrieving complex arbitrary spectra and matching idealized spectra for specific applications-focused cases such as selective thermal emitters, while keeping data requirements modest. Our nested transfer learning approach represents a promising avenue for addressing data acquisition challenges.