In this paper, we achieved excellent variation control, endurance enhancement, and leakage reduction in zirconium (Zr)-doped hafnium oxide (Hf 1−x Zr x O 2 ) based ferroelectric films by the germination of large ferroelectric grains through extending the duration of rapid thermal annealing without increasing the temperature beyond 700 °C. The pivotal point of this work is to reduce electrical variations in ferroelectric capacitors, which we attribute to the random variation in ferroelectric and dielectric phases. The motivation for this research originally stemmed from Johnson− Mehl−Avrami−Kolmogorov's theory of nucleation, which predicts that a sufficient time is required for forming any particular phase during phase transformation. Instead of increasing the temperature beyond 700 °C, extending the duration of rapid thermal annealing allows uniform crystal to form, which agrees with the theory. A 10 nm thick Hf 1−x Zr x O 2 film (x = 0.2) has been fabricated. The duration and temperature of rapid thermal annealing (RTA) under a nitrogen (N 2 ) atmosphere at 1 atmospheric pressure (atm) is varied to observe its effect on crystal formation and the electrical properties of the devices. It was observed that very low temperature and short (30 s) duration annealing at 1 atm pressure cannot infuse ferroelectricity in Hf 1−x Zr x O 2 . Structural analysis clearly showed the formation of large and uniform ferroelectric domains with negligible impact on surface roughness upon extending the annealing duration up to 180 s. The device-to-device variation in terms of standard deviation of coercive voltage and peak capacitance are reduced from 400 to 17 mV and from 20 to 4 fF/cm 2 , respectively, by increasing the RTA duration at 700 °C. The devices have also displayed endurance above 1 million cycles and leakage current density below 10 pA/μm 2 . The simple physics-based process discussed here reduces the thermal budget required for Hf 1−x Zr x O 2 , mitigates the randomness in the domain distribution, and infuses deterministic switching. This improvement paves the way for implementing Hf 1−x Zr x O 2 -based, deeply scaled ferroelectric devices for memory and steep slope device applications.

In this paper, multiple-fin n- and p-channel HfZrO2 ferroelectric-FinFET devices are manufactured using a gate first process with post metalization annealing. The device transfer characteristics upon program and erase operations are measured and modeled. The drift in the transfer characteristics due to depolarization field and charge injection are captured using the shift in the threshold voltage along with time-dependent modeling of vertical field dependent mobility degradation parameters to develop a physical, computationally efficient, and accurate retention model for ferroelectric-FinFET devices. The modeled conductance is incorporated into deep neural network simulation platform CIMulator to analyze the role of conductance drift due to retention degradation, as well as the importance of the gap between high and low conductance states in improving the image recognition accuracy of neural networks.