Soft grippers are ideal for grasping delicate, deformable objects with complex geometries. Universal soft grippers have proven effective for grasping common objects, however complex objects or environments require bespoke gripper designs. Multi-material printing presents a vast design-space which, when coupled with an expressive computational design algorithm, can produce numerous, novel, high-performance soft grippers. Finding high-performing designs in challenging design spaces requires tools that combine rapid iteration, simulation accuracy, and fine-grained optimization across a range of gripper designs to maximize performance, no current tools meet all these criteria. Herein, a diversity-based soft gripper design framework combining generative design and topology optimization (TO) are presented. Compositional pattern-producing networks (CPPNs) seed a diverse set of initial material distributions for the fine-grained TO. Focusing on vacuum-driven multi-material soft grippers, several grasping modes (e.g. pinching, scooping) emerging without explicit prompting are demonstrated. Extensive automated experimentation with printed multi-material grippers confirms optimized candidates exceed the grasp strength of comparable commercial designs. Grip strength, durability, and robustness is evaluated across 15,170 grasps. The combination of fine-grained generative design, diversity-based design processes, high-fidelity simulation, and automated experimental evaluation represents a new paradigm for bespoke soft gripper design which is generalizable across numerous design domains, tasks, and environments.

Nanopore sensors, owing to their distinctive structural properties, can be used to detect biomolecular translocation events. These sensors operate by monitoring variations in electric current amplitude and duration, thereby enabling the calibration and distinction of various biomolecules. As a result, nanopores emerge as a potentially powerful tool in the field of deoxyribonucleic acid (DNA) sequencing. However, the interplay between testing bandwidth and noise often leads to the loss of part of the critical translocation signals, presenting a substantial challenge for the precise measurement of biomolecules. In this context, innovative detection mechanisms have been developed, including optical detection, tunneling current detection, and nanopore field-effect transistor (FET) detection. These novel detection methods are based on but beyond traditional nanopore techniques and each of them has unique advantages. Notably, nanopore FET sensors stand out for their high signal-to-noise ratio (SNR) and high bandwidth measurement capabilities, overcoming the limitations typically associated with traditional solid-state nanopore (SSN) technologies and thus paving the way for new avenues to biomolecule detection. This review begins by elucidating the fundamental detection principles, development history, applications, and fabrication methods for traditional SSNs. It then introduces three novel detection mechanisms, with a particular emphasis on nanopore FET detection. Finally, a comprehensive analysis of the advantages and challenges associated with both SSNs and nanopore FET sensors is performed, and then insights into the future development trajectories for nanopore FET sensors in DNA sequencing are provided. This review has two main purposes: firstly, to provide researchers with a preliminary understanding of advancements in the nanopore field, and secondly, to offer a comprehensive analysis of the fabrication techniques, transverse current detection principles, challenges, and future development trends in the field of nanopore FET sensors. This comprehensive analysis aims to help give researchers in-depth insights into cutting-edge advancements in the field of nanopore FET sensors.