Results 221 to 230 of about 2,112,128 (293)

Thermoreflectance Detection of Point Defects Resulting from Focused Ion Beam Milling

Advanced Engineering Materials, EarlyView.
Focused ion beam (FIB) milling is a common tool for nanoscale material processing, however irradiation damage, redeposition, and contamination can occur. We use several characterization tools to show FIB‐induced effects beyond 1 mm from the milled area.
Thomas W. Pfeifer, Eric R. Hoglund, Anton V. Ievlev, Patrick E. Hopkins   +3 more
wiley   +1 more source

Make it worth it: Effort-reward modulations on reinforcement-learning and prediction-error signaling across adolescence. [PDF]

Dev Cogn Neurosci
Kramer AW, Krabbendam L, Schaaf JV, Huizenga HM, Van Duijvenvoorde ACK.   +4 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Surprise!-Clarifying the link between insight and prediction error. [PDF]

Psychon Bull Rev
Becker M, Wang X, Cabeza R.
europepmc   +1 more source

Planar Solid‐State Nanopores Toward Scalable Nanofluidic Integration Based on CMOS Technology

Advanced Engineering Materials, EarlyView.
We present a scalable silicon‐based fabrication strategy for planar solid‐state nanopores to enable their integration with complex nanofluidic systems. Prototype devices demonstrate normal voltage‐current characteristics, good noise performance, and appreciable streaming currents. Our CMOS‐compatible fabrication process offers precise geometric control
Ngan Hoang Pham, Chenyu Wen, Mohammad Hadi Khaksaran, Won‐Yong Lee, Javier Cruz, Klas Hjort, Dongping Wu, Shi‐Li Zhang   +7 more
wiley   +1 more source

Dopamine prediction error signaling in a unique nigrostriatal circuit is critical for associative fear learning. [PDF]

Nat Commun
Zafiri D, Salinas-Hernández XI, De Biasi ES, Rebelo L, Duvarci S.   +4 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Unexpected Twists: Electrophysiological Correlates of Encoding and Retrieval of Events Eliciting Prediction Error. [PDF]

Psychophysiology
Turan G, Spiertz V, Bein O, Shing YL, Nolden S.   +4 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Prediction error determines how memories are organized in the brain. [PDF]

Elife
Kennedy NGW, Lee JC, Killcross S, Westbrook RF, Holmes NM.   +4 more
europepmc   +1 more source