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Abstract Chalcogenide-based nonvolatile phase change materials (PCMs) have a long history of usage, from bulk disk memory to all-optic neuromorphic computing circuits. Being able to perform uniform phase transitions over a subwavelength scale makes PCMs particularly suitable for photonic applications. For switching between nonvolatile states, the conventional chalcogenide phase change materials are brought to a melting temperature to break the covalent bonds. The cooling rate determines the final state. Reversible polymorphic layered materials provide an alternative atomic transition mechanism for low-energy electronic (small domain size) and photonic nonvolatile memories (which require a large effective tuning area). The small energy barrier of breaking van der Waals force facilitates low energy, fast-reset, and melting-free phase transitions, which reduces the chance of element segregation-associated device failure. The search for such material families starts with polymorphic In2Se3, which has two layered structures that are topologically similar and stable at room temperature. In this perspective, we first review the history of different memory schemes, compare the thermal dynamics of phase transitions in amorphous-crystalline and In2Se3, detail the device implementations for all-optical memory, and discuss the challenges and opportunities associated with polymorphic memory.
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High-speed multifunctional photonic memory on a foundry-processed photonic platform
The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but it requires nonvolatile photonic memory capable of rapid updates during on-chip training sessions or when new information becomes available during deployment. Phase-change materials (PCMs) are promising for providing compact, nonvolatile optical weighting; however, they face limitations in terms of bit precision, programming speed, and cycling endurance. Here, we propose a novel photonic memory cell that merges nonvolatile photonic weighting using PCMs with high-speed, volatile tuning enabled by an integrated PN junction. Our experiments demonstrate that the same PN modulator, fabricated via a foundry-compatible process, can achieve dual functionality. It supports coarse programmability for setting initial optical weights and facilitates high-speed fine-tuning to adjust these weights dynamically. The result shows a 400-fold increase in volatile tuning speed and a 10,000-fold enhancement in efficiency. This multifunctional photonic memory with volatile and nonvolatile capabilities could significantly advance the performance and versatility of photonic memory cells, providing robust solutions for dynamic computing environments.
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- PAR ID:
- 10565839
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optica
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2334-2536
- Format(s):
- Medium: X Size: Article No. 31
- Size(s):
- Article No. 31
- Sponsoring Org:
- National Science Foundation
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