most citedGuidelines for the optimization of hafnia-based ferroelectrics through superlattice engineering

1 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2026

Domain-wall-to-domain interconversion in a polar conducting oxide

Martin F. Sarott, Majid Ahmadi, Johanna van Gent González +13

Domain walls in ferroic crystals are topological defects with a symmetry distinct from the domain interior, allowing them to display functionalities that are otherwise forbidden in…

cond-mat.mtrl-sci2026

Computing at the Edge Enabled by Indoor Photovoltaics and Ferroelectrics

Robert L. Z. Hoye, Markus Hellenbrand, Nuno Estrócio +17

The exponential, pervasive rise of artificial intelligence (AI), hosted in large data centres, will test the limits of the underpinning infrastructure, including electricity and wa…

physics.app-ph2026★ 1 cited

20 ps Non-Destructive Read and 1 ns Write Operations at <5 V in Ferroelectric HfO2/ZrO2 Non-Volatile Memories

Alexandre Baigol, Ruben Hamming-Green, Paul Uriarte Vicandi +8

Achieving low-voltage, nanosecond multi-level programming and non-destructive read-out of ferroelectric non-volatile memories (NVM) is critical for analog in-memory computing archi…

cond-mat.mtrl-sci2025

Epitaxial Sr(Sn, Ge)TiO buffer layers for continuous strain engineering on SrTiO substrates

Ruben Hamming-Green, Ewout van der Veer, Beatriz Noheda

Epitaxial strain plays a key role in determining the structure and functionality of thin films, with the choice of substrate being traditionally used to control the magnitude of th…

cond-mat.mtrl-sci2025★ 1 cited

Guidelines for the optimization of hafnia-based ferroelectrics through superlattice engineering

Johanna van Gent, Binayak Mukherjee, Ewout van der Veer +5

Hafnia-based ferroelectrics are revolutionizing the data storage industry and the field of ferroelectrics, with improved materials and devices being reported monthly. However, full…

cond-mat.mtrl-sci2025

PdNeuRAM: forming-free, multi-bit Pd/HfO2 ReRAM for energy-efficient neuromorphic computing

Erbing Hua, Theofilos Spyrou, Majid Ahmadi +11

Memristor technology shows great promise for energy-efficient computing, yet it grapples with challenges like resistance drift and inherent variability. For filamentary Resistive R…