Results 211 to 220 of about 402,850 (292)

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

open access: yesAdvanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang   +5 more
wiley   +1 more source

An Efficient Biological Codon Recognition Reservoir Computing System Based on Low‐Energy Epitaxial Hf0.52Zr0.48O2 Ferroelectric Memristors

open access: yesAdvanced Science, EarlyView.
This work reports on epitaxially grown Hf0.52Zr0.48O2 ferroelectric memristors with high stability (high durability exceeding 108 cycles and a retention time exceeding 104 s for 16 states) and ultra‐low operating energy consumption (∼121 fJ). A memristor array‐based reservoir computing system is constructed and applied for the first time in the field ...
Ying Liu   +6 more
wiley   +1 more source

On fractal multiplicative derivatives and their applications

open access: yesRevista de la Unión Matemática Argentina
Daniel Alfonso Santiesteban   +1 more
openaire   +1 more source

Nanoscale Secondary Ion Mass Spectrometry for Quantifying Membrane Fouling: Fouling Layer Structure and Chemical Interaction

open access: yesAdvanced Science, EarlyView.
Nanoscale secondary ion mass spectrometry (Nano SIMS) is established as a powerful analytical tool to visualize and quantify the membrane fouling layers. ABSTRACT Membrane technology has garnered considerable attention for applications in wastewater treatment and resource recovery. Nevertheless, membrane fouling remains a major barrier, yet the lack of
Mengfei Wu   +4 more
wiley   +1 more source

Addressing biomedical complexity using the energy systems language. [PDF]

open access: yesFront Syst Biol
Surra F, Gonella F, Conte L, Romano A.
europepmc   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

open access: yesAdvanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang   +2 more
wiley   +1 more source

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