R&D: Three Articles on Phase Change Memories Technologies

R&D: Lorentzian Function-based Simulation and Analysis of Spectral Behaviour in Phase-change Memory

Work presents MATLAB-based simulation study employing the Lorentzian function to investigate the effect of variations in the half-width at half-maximum (Γ) on the spectral profile, and how these variations can be correlated with the material states of GST467.

Next Materials has published an article written by Vikas Bhatnagar, and Adesh Kumar, Department of Electrical & Electronics Engineering, School of Advanced Engineering, UPES, Dehradun, 248007, India.

Abstract: “Phase Change Memory (PCM) materials, including Ge₄Sb₆Te₇ (GST467), are increasingly recognized in advanced data storage for their rapid switching capabilities and scalability. This work presents a MATLAB-based simulation study employing the Lorentzian function to investigate the effect of variations in the half-width at half-maximum (Γ) on the spectral profile, and how these variations can be correlated with the material states of GST467. The study begins with single-peak Lorentzian simulations to isolate the role of Γ, showing that increasing Γ broadens peaks and reduces intensity while conserving the overall area. This provides a theoretical basis for interpreting broadening as a signature of structural disorder. The approach is then extended to synthetic multi-peak spectra, demonstrating how overlapping Lorentzian components approximate the complexity of GST Raman features. The comparisons with existing experimental Raman spectra signify that narrow Γ values are related to crystalline states, while broader Γ values are associated with amorphous or mixed states. Statistical fitting (R², reduced χ²) benchmarks Lorentzian models against Gaussian and Voigt alternatives. The novelty of the study lies in the quantitative linking of Γ variations to the degree of crystallinity and disorder in PCM materials. This method facilitates a comprehensive analysis of spectral fluctuations during phase transitions by simulating a broad spectrum of Γ values and connecting them with experimental results. The results demonstrate that even slight modifications in Γ serve as sensitive markers of material condition, exceeding traditional peak position or intensity assessments. This study enhances Raman spectroscopy by including a MATLAB simulation-assisted method for monitoring phase transitions in phase change materials (PCM). This methodology can be utilized for various chalcogenide memories, facilitating the advancement of swifter and more efficient phase change memory technologies.“

R&D: Comprehensive Review of Phase Change Memory for Neuromorphic Computing, Advancements, Challenges, and Future Directions

PCM promises significant benefits, key challenges such as resistance drift, endurance limits, and thermal crosstalk must be addressed.

Energy Storage has published an article written by Vikas Bhatnagar, and Adesh Kumar, Department of Electrical and Electronics Engineering, School of Advanced Engineering, UPES, Dehradun, India.

Abstract: “The human brain functions as a highly efficient control center, inspiring the field of neuromorphic computing, which seeks to replicate its structure and behavior through hardware systems. Neuromorphic computing integrates processing and memory functions using artificial neurons and synapses designed with electronic circuits, enabling parallel, energy-efficient data handling. One of the leading technologies supporting this paradigm is phase change memory (PCM), a non-volatile memory that stores data through reversible transitions between amorphous (high resistance) and crystalline (low resistance) states of chalcogenide materials, particularly Ge₂Sb₂Te₅ (GST225). PCM exhibits fast read/write speeds, excellent data retention, and scalability, making it ideal for neuromorphic architectures. This review highlights recent advancements in PCM for neuromorphic computing, including innovations in doping strategies and device engineering. Notable developments include arsenic-doped ovonic threshold switches (OTS) for enhanced selector performance, monolayer Sb₂Te₃ for atomic-scale devices, and heater-all-around (HAA) 3D architectures for reduced energy consumption. Integration with machine learning tools enables precise atomistic modeling, accelerating material and device optimization. Furthermore, emerging variants like ovonic unified memory (OUM) and interfacial PCM (IPCM) offer unique performance advantages. While PCM promises significant benefits, key challenges such as resistance drift, endurance limits, and thermal crosstalk must be addressed. The global neuromorphic computing market is poised for exponential growth, driven by innovations in materials, algorithms, and architectures. The PCM and neuromorphic computing represent a transformative leap toward intelligent, adaptive, and energy-efficient computing systems.“

R&D: Enhanced Thermal Stability of Single Element Sb Phase-change Materials by Rare Earth

This research details the production of Sb-Yb composite films utilizing magnetron sputtering techniques, along with an in-depth analysis of their crystallization processes.

Vacuum has published an article written by Zhongwang Song, Weifeng Gu, Yinxuan Ni, Laboratory of Infrared Materials and Devices, The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, 315211, China, and Guoxiang Wang, Laboratory of Infrared Materials and Devices, The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, 315211, China, and Zhejiang Key Laboratory of Advanced Optical Functional Materials and Devices, China.

Abstract: “Sb-based single-element phase-change memory exhibits exceptional potential for next-generation phase-change memory (PCM) applications, owing to its fast phase transition capability and remarkably low resistance drift coefficient. However, it is significantly hindered by its inadequate thermal stability, making it susceptible to spontaneous crystallization at ambient temperature. This research details the production of Sb-Yb composite films utilizing magnetron sputtering techniques, along with an in-depth analysis of their crystallization processes. The Sb-based composite film exhibits high crystallization temperature (120 °C), the Growth-dominated crystallization mode (n_avg = 0.96), low resistance drift (0.015), and enhanced optical bandgap (0.91 eV). These advancements are attributed to a unique crystalline-amorphous nanocomposite structure, where Sb nanograins (10–20 nm) are encapsulated by an amorphous Sb-Yb phase. The amorphous Yb-Sb matrix refines grain size and suppresses excessive growth of Sb nanograins, thereby significantly enhancing the structural thermal stability. This nanocomposite architecture significantly enhances thermal stability in Sb-based PCMs while exhibiting extremely low resistance drift and maintaining the growth-type crystallization mechanism, effectively overcoming the limitations of pure Sb and traditional Ge₂Sb₂Te₅ (GST) materials.“