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certain PTE-based systems employing ionogel or elastomeric substrates have demonstrated inherent softness,
softness alone does not guarantee stable synaptic function under strain. In zero-power configurations relying
on built-in or thermoelectric fields, even minor interfacial distortions can disrupt charge or ion transport
pathways, resulting in degraded or unpredictable synaptic weight modulation. Furthermore, PTE-based
devices inherently rely on localized heating, which affects other electronic components in integrated circuits
and induces thermal crosstalk between neighboring synapses. Thus, PTE-based devices require careful
thermal isolation and architectural design to ensure reliable operation in wearable neuromorphic platforms.

These limitations can be addressed by adopting design principles from soft electronics and by developing
new material systems specifically optimized for zero-power operation. The mechanical softness of all device
components including the substrate, electrodes, active layer, and encapsulation layer must be carefully
considered to ensure compatible mechanical properties. Mechanical mismatch among all components can
lead to stress concentration, interfacial delamination, and irreversible performance degradation under
mechanical deformation. For the substrate and encapsulation layers, hydrophobic elastomeric materials with
intrinsic softness and optical transparency can be employed to provide mechanical compliance while
maintaining synaptic performances and preventing environmental defects [95-97] . Soft electrodes can be
achieved by embedding nanoscale conductive materials in polymer matrices or by using crosslinking
additives to improve flexibility while maintaining electrical conductivity [58,98,99] . The development of
intrinsically stretchable semiconductors and the formation of semiconductor composites with elastomeric
materials are strategies for providing softness to active layer [100,101] . In particular, advancing intrinsically
stretchable electronic materials can enhance mechanical robustness without complex fabrication
processes [102-104] . However, such approaches must also preserve the delicate trap-state dynamics that govern
synaptic behavior, as local trap distributions and carrier pathways are easily perturbed by mechanical strain,
even subtle interfacial distortions can result in signal drift or performance degradation. Moreover, reducing
film thickness enhances stretchability by lowering bending stiffness and surface strain, allowing mechanical
deformation to be accommodated elastically rather than through fracture or delamination. Translating such
material and structural design principles to zero-power optoelectronic synapses is expected to help maintain
stable optoelectronic functionality under mechanical deformation, which is applicable in wearable platforms.

In this context, extending all-soft structural engineering to Schottky junction and heterojunction-based
zero-power optoelectronic synapses offers a promising pathway to construct mechanical stability for
wearable neuromorphic platforms. Therefore, next-generation designs should aim to minimize perturbations
in synaptic weight states to ensure reliable learning and processing under deformation induced by conformal
body motion. Achieving this goal represents a distinct challenge compared with conventional stretchable
devices, requiring materials and architectures that sustain both elasticity and neuromorphic fidelity under
dynamic deformation.

CONCLUSION AND OUTLOOK
Zero-power optoelectronic synapses mark a key inflection point in the evolution of neuromorphic
electronics, providing a foundation for devices that perceive, learn, and adapt using light as their sole energy
source to minimize power consumption during system operation. Recent advances have demonstrated that
built-in potential and PTE effect can drive synaptic functions without external electrical bias, highlighting the
potential for unprecedented energy efficiency. However, realizing fully autonomous, deformable, and
intelligent systems requires overcoming multiple challenges, including photon management, bidirectional
learning, operational stability, mechanical adaptability, and scalable system-level integration.

Addressing these challenges demands cross-disciplinary efforts that connect materials chemistry, device
physics, and circuit and architectural design, rather than focusing on isolated device improvements. To