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1. A Landau–Devonshire analysis of strain effects on ferroelectric Al _1−x Sc _x N

   https://doi.org/10.1063/5.0098979  

   Yazawa, Keisuke; Zakutayev, Andriy; Brennecka, Geoff L. (July 2022, Applied Physics Letters)

   We present a thermodynamic analysis of the recently discovered nitride ferroelectric materials using the classic Landau–Devonshire approach. Electrostrictive and dielectric stiffness coefficients of Al 1− x Sc x N with a wurtzite structure ( 6 mm) are determined using a free energy density function assuming a hexagonal parent phase (6/ mmm), with the first-order phase transition based on the dielectric stiffness relationships. The results of this analysis show that the strain sensitivity of the energy barrier is one order of magnitude larger than that of the spontaneous polarization in these wurtzite ferroelectrics, yet both are less sensitive to strain compared to classic perovskite ferroelectrics. These analysis results reported here explain experimentally reported sensitivity of the coercive field to elastic strain/stress in Al 1− x Sc x N films and would enable further thermodynamic analysis via phase field simulation and related methods. 

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2. From prediction to experimental realization of ferroelectric wurtzite Al1− x Gd x N alloys

   https://doi.org/10.1063/5.0251168  

   Lee, Cheng-Wei; Smaha, Rebecca W; Brennecka, Geoff L; Haegel, Nancy M; Gorai, Prashun; Yazawa, Keisuke (February 2025, APL Materials)

   AlN-based alloys find widespread application in high-power microelectronics, optoelectronics, and electromechanics. The realization of ferroelectricity in wurtzite AlN-based heterostructural alloys has opened up the possibility of directly integrating ferroelectrics with conventional microelectronics based on tetrahedral semiconductors, such as Si, SiC, and III–Vs, enabling compute-in-memory architectures, high-density data storage, and more. The discovery of AlN-based wurtzite ferroelectrics has been driven to date by chemical intuition and empirical explorations. Here, we demonstrate the computationally-guided discovery and experimental demonstration of new ferroelectric wurtzite Al1−xGdxN alloys. First-principles calculations indicate that the minimum energy pathway for switching changes from a collective to an individual switching process with a lower overall energy barrier, at a rare-earth fraction x with x > 0.10–0.15. Experimentally, ferroelectric switching is observed at room temperature in Al1−xGdxN films with x > 0.12, which strongly supports the switching mechanisms in wurtzite ferroelectrics proposed previously [Lee et al., Sci. Adv. 10, eadl0848 (2024)]. This is also the first demonstration of ferroelectricity in an AlN-based alloy with a magnetic rare-earth element, which could pave the way for additional functionalities such as multiferroicity and opto-ferroelectricity in this exciting class of AlN-based materials. 

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3. Machine learning–guided optimization of coercive field in Al _{1− x} Sc _x N thin films for nonvolatile memory

   https://doi.org/10.1111/jace.20347  

   Das, Shaon; Garg, Prachi; Mazumder, Baishakhi (April 2025, Journal of the American Ceramic Society)

   Abstract This study employs a data‐driven machine learning approach to investigate specific ferroelectric properties of Al_1−xSc_xN thin films, targeting their application in next‐generation nonvolatile memory (NVM) devices. This approach analyzes a vast design space, encompassing over a million data points, to predict a wide range of coercive field values that are crucial for optimizing Al_1−xSc_xN‐based NVM devices. We evaluated seven machine learning models to predict the coercive field across a range of conditions, identifying the random forest algorithm as the most accurate, with a testR²value of 0.88. The model utilized five key features: film thickness, measurement frequency, operating temperature, scandium concentration, and growth temperature to predict the design space. Our analysis spans 13 distinct scandium concentrations and 13 growth temperatures, encompassing thicknesses from 9–1000 nm, frequencies from 1 to 100 kHz, and operating temperatures from 273 to 700 K. The predictions revealed dominant coercive field values between 3.0 and 4.5 MV/cm, offering valuable insights for the precise engineering of Al_1−xSc_xN‐based NVM devices. This work underscores the potential of machine learning in guiding the development of advanced ferroelectric materials with tailored properties for enhanced device performance. 

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4. The more, the better: Al1− x (Mg,Hf)xN wurtzite ferroelectrics through co-alloying

   https://doi.org/10.1063/5.0289994  

   Bradford, Victoria M; Nguyen, Thi; Brennecka, Geoff L; Lee, Cheng-Wei; Gorai, Prashun (October 2025, Applied Physics Letters)

   Wurtzite ferroelectrics (FEs) are promising candidates for next-generation memory and computing devices due to their compatibility with semiconductor processing. However, their adoption is limited by large coercive electric fields (Ec), often approaching the dielectric breakdown field (Eb), raising concerns about energy efficiency and device reliability. The discovery of wurtzite FEs has also been constrained by a narrow chemical design space, with few known examples to date. Ferroelectricity in AlN-based alloys, particularly Al1−xMxN with trivalent M3+ cations, has been a focal point of recent work. Building on studies of co-alloyed AlN for enhanced piezoelectricity, we computationally investigate ferroelectricity in Al1−x(M1,M2)xN alloys, where M12+ and M24+ are non-trivalent cations. Using density functional theory, solid-state nudged elastic band method, and structural analysis, we predict switchable polarization in Al1−x(Mg,Hf)xN. Compared to the prototypical Al1−xScxN, this co-alloy exhibits a more rapid decrease in both the switching barrier and bandgap with increasing x, suggesting a simultaneous reduction in Ec and Eb. This reduction in Ec is attributed to enhanced structural distortions introduced by co-alloying. By using bandgap and distortion as design metrics, we identify several other promising M1–M2 combinations, and highlight Al1−x(Ca,Si)xN as a strong candidate for experimental validation. Our work introduces a co-alloying strategy to access new wurtzite FEs and expands the design space to include earth-abundant elements. 

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5. Intrinsic nanoscale ordering and strain–defect coupling in ferroelectric Al1 − xScxN

   https://doi.org/10.1063/5.0325478  

   Das, Shaon; Nguyen, Thai-Son; Savant, Chandrashekhar; Gothandapani, Karthick; Xing, Huili Grace; Jena, Debdeep; Mazumder, Baishakhi (April 2026, Applied Physics Letters)

   Al1−xScxN (AlScN) has emerged as a promising ferroelectric material for next-generation memory and logic devices; yet its performance remains limited by poor understanding of nanoscale structural instabilities. Here, we uncover intrinsic short-range chemical ordering and strain–defect coupling in molecular-beam-epitaxy grown Al0.66Sc0.34N using a combination of atom probe tomography and transmission electron microscopy. The heterostructure exhibits wurtzite structure with a sharp and clean AlScN/AlN interface with negligible interdiffusion. Frequency distribution and radial distribution analyses reveal statistically significant Sc–Sc enrichment and Sc–N depletion, indicating nanoscale clustering accompanied by local nitrogen deficiency. Corresponding lattice-spacing variations observed by inverse FFT mapping confirm strain variation correlated with Sc-rich domains. These results provide the first atom-by-atom experimental evidence of scandium clustering and its coupling to nitrogen-vacancy formation in the ferroelectric composition regime. These findings identify short-range ordering and strain–defect coupling as intrinsic structural features of ferroelectric AlScN, with important implications for polarization switching behavior and reliability. 

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