Results 191 to 200 of about 7,662,913 (346)

High‐Yield Synthesis of Fe‐NC Electrocatalysts Using Mg2+ Templating and Schiff‐Base Porous Organic Polymers

open access: yesAdvanced Functional Materials, EarlyView.
Fe─NC porous oxygen reduction electrocatalysts are prepared employing a 2,4,6‐Triaminopyrimidine‐based porous organic polymer, a Mg2+ Lewis acid, and a low‐temperature cation exchange protocol. Using the polymer precursor achieves high pyrolysis yields and results in atomically dispersed FeNx sites. The resulting catalysts feature hierarchical porosity
Eliot Petitdemange   +11 more
wiley   +1 more source

ENHANCING LOCAL-SEARCH BASED SAT SOLVERS WITH LEARNING CAPABILITY

open access: gold, 2010
Ole‐Christoffer Granmo   +1 more
openalex   +1 more source

Single Solid‐State Ion Channels as Potentiometric Nanosensors

open access: yesAdvanced Functional Materials, EarlyView.
Single gold nanopores functionalized with mixed self‐assembled monolayers act as solid‐state ion channels for direct, selective potentiometric sensing of inorganic ions (Ag⁺). The design overcomes key miniaturization barriers of conventional ion‐selective electrodes by combining low resistivity with suppressed loss of active components, enabling robust
Gergely T. Solymosi   +4 more
wiley   +1 more source

Building structure into local search for SAT

open access: green, 2007
Duc Nghia Pham   +2 more
openalex   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

open access: yesAdvanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo   +4 more
wiley   +1 more source

A local search template (extended abstract)

open access: green, 1992
Rjm Rob Vaessens   +2 more
openalex   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

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