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3D printing of micro-nano devices and their applications

In recent years, the utilization of 3D printing technology in micro and nano device manufacturing has garnered significant attention. Advancements in 3D printing have enabled achieving sub-micron level precision. Unlike conventional micro-machining techniques, 3D printing offers versatility in material selection, such as polymers. 3D printing technology has been gradually applied to the general field of microelectronic devices such as sensors, actuators and flexible electronics due to its adaptability and efficacy in microgeometric design and manufacturing processes. Furthermore, 3D printing technology has also been instrumental in the fabrication of microfluidic devices, both through direct and indirect processes. This paper provides an overview of the evolving landscape of 3D printing technology, delineating the essential materials and processes involved in fabricating microelectronic and microfluidic devices in recent times. Additionally, it synthesizes the diverse applications of these technologies across different domains.

Innovating beyond electrophysiology through multimodal neural interfaces

Neural circuits distributed across different brain regions mediate how neural information is processed and integrated, resulting in complex cognitive capabilities and behaviour. To understand dynamics and interactions of neural circuits, it is crucial to capture the complete spectrum of neural activity, ranging from the fast action potentials of individual neurons to the population dynamics driven by slow brain-wide oscillations. In this Review, we discuss how advances in electrical and optical recording technologies, coupled with the emergence of machine learning methodologies, present a unique opportunity to unravel the complex dynamics of the brain. Although great progress has been made in both electrical and optical neural recording technologies, these alone fail to provide a comprehensive picture of the neuronal activity with high spatiotemporal resolution. To address this challenge, multimodal experiments integrating the complementary advantages of different techniques hold great promise. However, they are still hindered by the absence of multimodal data analysis methods capable of providing unified and interpretable explanations of the complex neural dynamics distinctly encoded in these modalities. Combining multimodal studies with advanced data analysis methods will offer novel perspectives to address unresolved questions in basic neuroscience and to develop treatments for various neurological disorders.

Photonic-crystal surface-emitting lasers

High-performance lasers are important to realize a range of applications including smart mobility and smart manufacturing, for example, through their uses in key technologies such as light detection and ranging (LiDAR) and laser processing. However, existing lasers have a number of performance limitations that hinder their practical use. For example, conventional semiconductor lasers are associated with low brightness and low functionality, even though they are compact and highly efficient. Conventional semiconductor lasers therefore require external optics and mechanical elements for reshaping and scanning of emitted beams, resulting in large, complicated systems for various practical uses. Furthermore, even with such external elements, the brightness of these lasers cannot be sufficiently increased for use in laser processing. Similarly, gas and solid-state lasers, while having high-brightness, are also large and complicated. Photonic-crystal surface-emitting lasers (PCSELs) boast both high brightness and high functionality while maintaining the merits of semiconductor lasers, and thus PCSELs are solutions to the issues of existing laser technologies. In this Review, we discuss recent progress of PCSELs towards high-brightness and high-functionality operations. We then elaborate on new trends such as short-pulse and short-wavelength operations as well as the combination with machine learning and quantum technologies. Finally, we outline future research directions of PCSELs with regard to various applications, including not only LiDAR and laser processing, as described above, but also communications, mobile technologies, and even aerospace and laser fusion.

Shaping exciton polarization dynamics in 2D semiconductors by tailored ultrafast pulses

The ultrafast formation of strongly bound excitons in two-dimensional semiconductors provides a rich platform for studying fundamental physics as well as developing novel optoelectronic technologies. While extensive research has explored the excitonic coherence, many-body interactions, and nonlinear optical properties, the potential to study these phenomena by directly controlling their coherent polarization dynamics has not been fully realized. In this work, we use a sub-10 fs pulse shaper to study how temporal control of coherent exciton polarization affects the generation of four-wave mixing in monolayer ({rm{WS}}{{rm{e}}}_{2}) under ambient conditions. By tailoring multiphoton pathway interference, we tune the nonlinear response from destructive to constructive interference, resulting in a 2.6-fold enhancement over the four-wave mixing generated by a transform-limited pulse. This demonstrates a general method for nonlinear enhancement by shaping the pulse to counteract the temporal dispersion experienced during resonant light–matter interactions. Our method allows us to excite both 1s and 2s states, showcasing a selective control over the resonant state that produces nonlinearity. By comparing our results with theory, we find that exciton-exciton interactions dominate the nonlinear response, rather than Pauli blocking. This capability to manipulate exciton polarization dynamics in atomically thin crystals lays the groundwork for exploring a wide range of resonant phenomena in condensed matter systems and opens up new possibilities for precise optical control in advanced optoelectronic devices.

A thalamic hub-and-spoke network enables visual perception during action by coordinating visuomotor dynamics

For accurate perception and motor control, an animal must distinguish between sensory experiences elicited by external stimuli and those elicited by its own actions. The diversity of behaviors and their complex influences on the senses make this distinction challenging. Here, we uncover an action–cue hub that coordinates motor commands with visual processing in the brain’s first visual relay. We show that the ventral lateral geniculate nucleus (vLGN) acts as a corollary discharge center, integrating visual translational optic flow signals with motor copies from saccades, locomotion and pupil dynamics. The vLGN relays these signals to correct action-specific visual distortions and to refine perception, as shown for the superior colliculus and in a depth-estimation task. Simultaneously, brain-wide vLGN projections drive corrective actions necessary for accurate visuomotor control. Our results reveal an extended corollary discharge architecture that refines early visual transformations and coordinates actions via a distributed hub-and-spoke network to enable visual perception during action.

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