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Phase-Change Materials Light the Way to Brain-Like Photonic Computers

October 15, 2026
in Science News
Cassandra Pierce
By Cassandra Pierce Scienmag Editorial Profile - Systems Neuroscience
Reading Time: 6 mins read
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Phase-Change Materials Light the Way to Brain-Like Photonic Computers

Phase-Change Materials Light the Way to Brain-Like Photonic Computers

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Modern artificial intelligence is hitting a wall that has little to do with how fast transistors can switch. The real problem is moving data. In today’s computing systems, the energy and latency required to shuttle information between memory and processing units—what researchers call the communication bottleneck—can cost orders of magnitude more energy than the arithmetic operations themselves. As CMOS scaling slows and the classical von Neumann separation between storage and compute becomes a dominant constraint, a team of French researchers argues that the missing ingredient for practical photonic processors may be found in a remarkable class of chalcogenide alloys known as phase-change materials, or PCMs.

In a review published in Frontiers in Photonics, Ranjeet Dwivedi, Charles Pourny, Anthony Albanese and colleagues from INSA Lyon, CNRS-Université Bourgogne Europe, CEA-LETI and the University Grenoble Alpes survey recent advances in photonic devices that integrate phase-change materials, with an eye toward neuromorphic computing—computing architectures inspired by the brain. Their central claim is bold: PCMs are not merely an optional tuning layer on photonic chips, but a key enabling material that bridges photonics’ high-throughput compute capability with the dense, persistent, low-energy programmability that practical AI hardware demands.

Photonics has long been touted as an attractive route around the energy problem. Optical signals propagate with very high bandwidth, low latency, and inherent parallelism through wavelength, spatial, and temporal multiplexing. These properties have motivated optical neural networks, photonic matrix-vector multiplication engines, and photonic tensor cores as potential accelerators for the linear-algebra operations that dominate inference and signal-processing workloads. But a central challenge remains: practical photonic processors require dense, programmable, reliable, and energy-efficient memory elements to store weights, biases, routing states, and calibration parameters directly inside the photonic circuit. Thermo-optic or free-carrier-based photonic circuits must be continuously powered to hold a given configuration, creating a static energy overhead that grows with system size.

Phase-change materials solve this missing memory problem in a striking way. Chalcogenide PCMs such as GeSbTe (GST), GeSbSeTe (GSST), Sb2S3 and Sb2Se3 exhibit large, reversible changes in optical refractive index and absorption between their amorphous and crystalline states. Crucially, these states are nonvolatile: once programmed, the optical state is retained without continuous electrical power. This makes PCM-based devices especially relevant for photonic computing, where many synaptic weights must remain fixed during inference while optical signals perform matrix-vector multiplication operations at high speed. Demonstrations have already shown PCM-based photonic in-memory computing, all-optical neurosynaptic systems, integrated photonic memories, and photonic tensor cores combining PCM weight banks with wavelength multiplexing.

The review begins with the materials science. Metavalent bonding (MVB) has been identified as a distinctive bonding mechanism that characterizes the crystalline phase of PCMs, placing them between covalently bonded and metallically bonded materials. Materials exhibiting metavalent bonding possess a characteristic set of features, including a high optical dielectric constant, enhanced chemical bond polarizability reflected by large Born effective charges, strong lattice anharmonicity associated with high Grüneisen parameters, and moderate electrical conductivity. From an optical perspective, PCMs exhibit significant differences between their amorphous (covalent) and crystalline (metavalent) phases, which is why they have long served as the working medium of optical data storage technologies such as CD-RW, DVD-RAM, and Blu-ray disks. The amorphous phase is obtained by heating the material above its melting temperature and then rapidly quenching it; the crystalline phase is achieved by annealing above the crystallization temperature, followed by slow cooling.

Among all PCMs, Ge2Sb2Te5 (GST225) is the most extensively studied. Located on the GeTe–Sb2Te3 pseudo-binary line of the Ge–Sb–Te ternary phase diagram, GST225 crystallizes at approximately 150–180 °C and offers a large refractive index contrast across the visible, near-infrared, and mid-infrared spectral ranges. At the telecommunication wavelength of 1550 nm, however, crystallization also increases the extinction coefficient by about an order of magnitude, leading to high optical losses. To evaluate and compare different PCMs for photonic applications, the researchers employ a material figure of merit (FOM) that quantifies the trade-off between optical modulation efficiency and insertion losses. Conventional GST225 thin films exhibit a FOM of approximately 2 at 1550 nm, while GeTe reaches 6.2 and Sb2S3 4.2. A distinct class of ultra-low-loss PCMs such as Sb2S3 and Sb2Se3 keeps the extinction coefficient close to zero in both states, though with a substantially smaller refractive index contrast attributed to their predominantly covalent bonding character.

The most intriguing materials lie at the border between covalent and metavalent systems: the GeSe–GeTe pseudo-binary line (GeSe1-xTex alloys). This alloy series bridges GeSe, characterized by a covalently bonded orthorhombic crystalline structure and ultra-low optical losses, and GeTe, a prototypical phase-change material whose rhombohedral crystalline phase is governed by metavalent bonding. Most GeSe1-xTex compositions exhibit a large refractive index contrast with limited absorption changes, resulting in FOM values up to 550 percent higher than GST225 and up to three times greater than GSST2241. Nitrogen-doped GeSe1-xTex thin films perform even better: N-doped GeSe0.5Te0.5 combines a FOM of 11.6 at 1550 nm, a large refractive index contrast, low optical losses, and a high crystallization temperature of about 345 °C. The material properties can be tailored by adjusting the Se/Te ratio and nitrogen content during deposition. As a bonus, all these alloys exhibit exceptionally high nonlinear Kerr coefficients and negligible two-photon absorption, outperforming many conventional nonlinear photonic materials and making them attractive for supercontinuum and frequency-comb generation.

Turning to devices, the review presents novel photonic designs for electrical PCM actuation. A key requirement for advanced photonic computing is the ability to encode multiple discrete phase levels, typically achieved through partial amorphization of the PCM layer, where intermediate refractive indices correspond to intermediate phase shifts. Conventional designs based on uniform heaters suffer from abrupt phase transitions because small variations in pulse parameters can produce disproportionately large phase shifts. To overcome this, the researchers propose a segmented heater architecture in which the heater width varies along the propagation direction, introducing a controlled thermal gradient so that different segments of the PCM experience distinct degrees of amorphization. When averaged across multiple segments, the cumulative effect is a smooth overall amorphization and a nearly continuous phase-shift response. This approach enables up to 164 distinguishable phase levels—greater than 7-bit resolution—with low insertion loss of approximately 0.6 dB in the worst case, while complying with standard foundry constraints (minimum heater width of 1 µm with incremental increases of 50 nm). The average power dissipation across the segmented heater is approximately 0.94 W, with programming pulse durations from 142 to 1015 ns, corresponding to an energy consumption ranging from 133 nJ to 955 nJ.

The researchers also present a hybrid-mode interferometer (HMI) that directly integrates phase-change modulation with modal interference in a single compact structure. The HMI exploits interference between hybridized transverse modes in a silicon waveguide integrated with a PCM layer at 1550 nm. By utilizing the vertical asymmetry of the structure, the waveguide is engineered to support hybridization between the fundamental TM mode and the first higher-order TE mode. In the crystalline state, the PCM-integrated waveguide length is selected to allow constructive interference, providing high transmittance with ultra-low insertion loss. In the amorphous state, nearly equal modal amplitudes arise from near-perfect hybridization, resulting in very low transmittance because the phase difference approaches destructive interference. This mechanism enables a high extinction ratio of about 14 dB within a compact footprint of roughly 24 µm length, with transmittance varying from 0.98 to 0.04—suitable for analog encoding and multi-bit storage with sub-microsecond switching speeds. Compared with conventional architectures, the HMI provides a good trade-off between compactness, multilevel encoding capability, and low insertion losses: MZI-based PCM phase shifters have large footprints (hundreds to thousands of square micrometers) because of input/output couplers and cross-talk constraints, while ring resonators, though compact, encode only a limited number of levels—for example, up to only 14 distinct optical levels demonstrated with a graphene-actuated Sb2Se3-based ring resonator.

Finally, the review presents experimental results for optically actuated GST225-based waveguides on silicon-on-insulator. GST225 patches integrated onto SOI waveguides were characterized under all-optical programming and readout conditions, with propagation losses of approximately 5 dB/µm at 1550 nm. A heterodyne interferometric setup—using a short 400 ps amorphization pulse followed 25 µs later by a longer, less intense recrystallization pulse, with a low-power 0.6 mW probe laser—monitored transmission and phase variations in real time. For a 1.5 µm-long GST225 patch, 400 ps amorphization pulses with an energy of approximately 100 pJ produced a transmission increase of about 60 percent and a phase-delay reduction of 55°. The write–erase sequence, using optimized pulse energies of 100 pJ and 7.4 nJ, was repeated over a 14-hour cycling test, providing a quantitative assessment of reversibility and endurance under repeated optical programming. The researchers conclude that the combination of devices based on electrical and optical actuation using different PCM compounds can provide a path toward achieving both static synaptic weighting (electrically) and dynamic synaptic reconfigurability, signal summation, and activation functions (optically)—the missing ingredient to enable next-generation computing systems where all the key functions can be addressed by either optical or electrical stimuli, depending on the exact required function.

Subject of Research: Physics

Article Title: Photonic devices based on phase-change materials for neuromorphic computing

Article References: Dwivedi, R., Pourny, C., Albanese, A., Yadav, A., Orobtchouk, R., Benane, G., Sawant, R., Tomelleri, M., Brulé, Y., Rogemont, A., Coillet, A., Charbonnier, B., Noé, P., Cluzel, B., & Pavanello, F. (2026). Photonic devices based on phase-change materials for neuromorphic computing. Frontiers in Photonics, 7, Article 1918762. https://doi.org/10.3389/fphot.2026.1918762

Image Credits: AI Generated

DOI: 10.3389/fphot.2026.1918762

Keywords: phase-change materials, photonics, neuromorphic computing, photonic computing, chalcogenides, optical memory, silicon photonics, Photonic, devices, based, phase-change, materials

Cite Scienmag News

Cassandra Pierce. (October 15, 2026). Phase-Change Materials Light the Way to Brain-Like Photonic Computers. Scienmag. https://scienmag.com/phase-change-materials-light-the-way-to-brain-like-photonic-computers/

Cassandra Pierce. "Phase-Change Materials Light the Way to Brain-Like Photonic Computers." Scienmag, 15 October 2026, https://scienmag.com/phase-change-materials-light-the-way-to-brain-like-photonic-computers/. Accessed 15 October 2026.

Cassandra Pierce. "Phase-Change Materials Light the Way to Brain-Like Photonic Computers." Scienmag. October 15, 2026. https://scienmag.com/phase-change-materials-light-the-way-to-brain-like-photonic-computers/

Tags: advances in photonic device materialsbasedbrain-inspired neuromorphic architectureschalcogenide alloys in photonicschalcogenidescommunication bottleneck in computing systemsdevicesenergy-efficient data transfer in photonicshigh-throughput photonic computing for AIlow-energy programmable photonic memorymaterialsneuromorphic computingoptical memoryovercoming von Neumann architecture limitationsPCM integration in optical devicesphase change materialsphase-changephase-change materials in photonic computingPhotonicphotonic computingphotonic computing for AI hardwarephotonic processors for artificial intelligencePhotonicssilicon photonics
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