Next‐Generation Bioelectronic Neural Interfaces: From Material Design to Closed‐Loop Systems

The convergence of neuroscience and bioelectronics is redefining neural interfaces. The field is moving beyond conventional electrical recording toward integrated platforms that combine multimodal sensing with closed‐loop neuromodulation. This transition is driven by persistent challenges in signal fidelity, long‐term stability, and functional adaptability, which have limited both fundamental neuroscience studies and clinical applications. Achieving high‐performance interfaces requires coordinated advances at multiple scales: materials must minimize mechanical and electrical mismatch while enabling biofunctional integration; devices must enable multiplexed, multimodal readout without compromising biocompatibility or power efficiency; and systems must orchestrate sensing, processing, and actuation with minimal latency and high reliability. Furthermore, multimodal neuromodulation is emerging as a key direction, using optical, magnetic, and chemical modalities for precise, minimally invasive control. The demand for long‐term autonomous operation is driving the development of self‐powered and adaptive systems, but increased complexity challenges fabrication, scalability, and reliability. Against this backdrop, this special issue of Small Methods, titled “Technologies in the Neural‐Material Interface”, assembles 16 reviews and 6 research papers highlighting recent advances and key bottlenecks in next‐generation neural interfaces.

At the materials level, a recurring theme across recent studies is the design of multifunctional interfaces that better match the mechanical, electrical, and biochemical properties of neural tissue, although achieving simultaneous optimization across these dimensions remains a fundamental challenge. In this context, Zhang et al. [1] (smtd.2501219) summarize conductive material strategies for peripheral nerve interfaces, spanning electrode coatings, implantable substrates, and regenerative scaffolds. These material systems enhance interfacial charge transport and mechanical compliance, which can improve signal coupling efficiency. However, long‐term operational stability and translational viability remain unresolved barriers for clinical deployment. Building on material‐based interface engineering, Shin et al. [2] (smtd. 2501228) examine two‐dimensional materials as platforms for ultrathin and mechanically compliant neural interfaces, including graphene, transition metal dichalcogenides, and MXenes. These materials support the fabrication of flexible, low‐impedance electrodes and enable hybrid bioelectronic systems that couple electrophysiological recording with optical modalities. However, challenges remain in large‐area fabrication consistency and long‐term biointerface stability. Compared with rigid or semi‐rigid systems based on conductive or two‐dimensional materials, soft‐matter platforms offer intrinsically more compliant interfaces that better match tissue mechanics. Kim et al. [3] (smtd.2501625) reviewed ion‐conducting gels as adaptive bioelectronic media, emphasizing their tunable polymer networks and compatibility with device‐level integration and closed‐loop operation. These gels allow tunable ionic transport and mechanical compliance, supporting stable electrode coupling at low impedance. Extending material‐level interface engineering, Kim et al. [4] (smtd.2501708) investigate motion artifacts in skin‐interfaced neural recording, a persistent issue arising from mechanical mismatch between soft tissue and rigid or semi‐conformal electrodes. By comparing thin‐film conformal electrodes and three‐dimensional adhesive architectures, they highlights that soft, adaptive materials such as liquid metals, ion gels, and hydrogels can partially alleviate electromechanical mismatch and reduce motion artifacts in EEG recordings. Ma et al. [5] (smtd. 2501134) focus on hydrogels as a representative class for improving electrode‐tissue coupling, where mechanical compliance and ionic conductivity jointly determine interfacial performance, while also highlighting trade‐offs with structural robustness and long‐term degradation. Their analysis spans coating strategies, bulk hydrogel electrodes, and integrated device architectures. At the interface level, Ji et al. [6] (smtd.2501242) demonstrate that conductive hydrogel electrodes can improve scalp‐electrode coupling even in hair‐covered regions, leading to higher EEG signal quality and improved user comfort. From a biotic‐abiotic interface perspective, Jekal et al. [7] (smtd. 2501620) examine strategies for neural recording, stimulation, and repair, emphasizing the gradual convergence toward closed‐loop and individualized neuromodulation paradigms. These studies indicate that interface design is shifting toward functionally adaptive systems. While, achieving stable, long‐term adaptive regulation in vivo remains an unresolved challenge.

At the device level, driven by the need to capture coupled electrical, chemical, and biochemical neural dynamics, neural interfaces are increasingly extending beyond single‐channel electrical readout toward multimodal sensing. Qian et al. [8] (smtd. 2501884) examine organic electrochemical transistors (OECTs) as neural sensing and modulation platforms, where volumetric ion‐electron coupling provides intrinsic amplification of weak bioelectrical and biochemical signals. They further summarize their evolution from material optimization to planar, vertical, and fiber‐based architectures, enabling flexible array formation and closed‐loop integration. Wang et al. [9] (smtd. 2501966) discuss organic transistor‐based neuromorphic electronics that emulate synaptic and neuronal dynamics, enabling in‐sensor computation for neuromorphic processing and sensing tasks, while emphasizing advantages in low power, flexibility, and biocompatibility. Zhang et al. [10] (smtd.2500783) introduce a conical‐tip glutamate nanosensor enabling single‐synapse resolution measurements of neurotransmitter dynamics during long‐term potentiation. This approach extends neural interfaces from electrical recording toward direct probing of synaptic biochemical processes. Li et al. [11] (smtd. 2501329) present an MRI‐compatible fiber ion sensor enabling simultaneous monitoring of extracellular ion dynamics and whole‐brain fMRI signals with minimal artifacts in a unified experimental platform. These advances reflect a shift from purely electrical readout toward electrochemically and biochemically enriched sensing, but integration across scales remains limited by trade‐offs in speed, stability, and complexity.

At the system level, Kim et al. [12] (smtd. 2501227) systematically reviewed multi‐channel neural interfaces for mapping brain and spinal cord circuits, highlighting high spatiotemporal recording combined with multimodal functions, including electrophysiology, drug delivery, optical stimulation, and chemical sensing. They further emphasize the role of flexible materials and structural engineering in maintaining mechanical stability during chronic implantation, alongside computational strategies for high‐dimensional neural decoding. Li et al. [13] (smtd.2501471) reviewed the evolution of brain‐machine interfaces toward multimodal biochemical systems, where electrical and electrochemical sensing modalities are increasingly integrated with flexible and closed‐loop architectures. Zhao et al. [14] (smtd. 2500470) demonstrate a wireless photometric probe enabling real‐time calcium imaging in freely behaving animals, integrating optical excitation, fluorescence readout, and wireless data transmission within a compact implantable platform. This work represents a step toward fully integrated neural recording systems capable of operating under unconstrained behavioral conditions. Overall, neural interfaces are evolving from isolated devices toward integrated systems operating in complex physiological environments. These studies indicate a transition from isolated neural recording devices toward system‐level integrated platforms.

On this basis, multimodal neuromodulation emerges as a key direction. Li et al. [15] (smtd. 2501228) report a silicon‐based optoelectronic interface capable of spatially resolved bidirectional photoresponse and polarity modulation, which provides insight into interfacial capacitive coupling as a governing mechanism for optically driven neural modulation. Chen et al. [16] (smtd. 2501460) analyze magnetic neuromodulation strategies, including magnetoelectric, magnetothermal, and magnetic‐force mechanisms, which offer advantages in deep tissue penetration and reduced invasiveness compared to optical or electrical approaches. Liu et al. [17] (smtd. 2501275) summarized stimuli‐responsive nanomaterials for wireless neuromodulation, emphasizing precise, minimally invasive control of neural circuits and design strategies based on energy conversion, catalysis, and bioactive multifunctional systems. Wang et al. [18] (smtd. 2501371) discuss non‐genetic optoelectronic neuromodulation strategies that leverage light‐matter interactions to achieve wireless control of excitable tissues with high spatiotemporal precision. System reliability and long‐term operation have become key issues, pushing interest toward self‐powered and practical deployment. Zhang et al. [19] (smtd. 2501241) demonstrate triboelectric nanogenerators capable of harvesting environmental mechanical energy to enable battery‐free sensing platforms, their relatively low sensitivity and unstable output under variable conditions limit practical neural interface applications. Xiao et al. [20] (smtd. 2501443) extend self‐powered concepts to implantable systems, providing a taxonomy of device architectures while identifying long‐term electrochemical and mechanical stability as a central barrier to clinical translation. Lan et al. [21] (smtd. 2501142) developed a wireless electrical tactile interface with hydrogel electrodes, achieving low‐threshold stimulation and demonstrating braille recognition and navigation in human tests. As systems become more complex, fabrication has emerged as a key bottleneck. Troughton et al. [22] (smtd. 2501560) analyze laser micromachining techniques for bioelectronics, encompassing cutting, thin‐film structuring, and localized material modification, which offer flexibility and high spatial resolution beyond conventional lithographic approaches. Overall, these studies indicate a shift toward neural interfaces that are self‐sustained, manufacturable, and suitable for in vivo and clinical deployment.

This Special Issue of Small Methods presents recent advances in neural interfaces across materials, devices, and system‐level applications, with particular emphasis on multimodal sensing and multiphysical neuromodulation strategies.

Conflicts of Interest

The authors declare no conflict of interest.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.