Results 151 to 160 of about 7,060,917 (288)

Fear Learning

, 2009
Paul W. Frankland, Sheena A. Josselyn
openaire   +1 more source

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

Advanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald, Hiroki Tomita, Giacomo Cotelli, Louka L. Brüll, Nanno G. de Rooij, Lucas R.L. Norg, Milo Clément, Reinder Coehoorn   +7 more
wiley   +1 more source

Linking functional and structural dendritic spine remodeling during fear learning and extinction in vivo. [PDF]

Sci Adv
Li X, Zheng Q, Wong KHK, Wong KKY, Lai CSW.   +4 more
europepmc   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Generalization of fear learning is shaped by inhibitory sensory processing in mice. [PDF]

Nat Commun
Bakir AK, Gaikwad AA, Efimova N, Clark KLL, Rosenthal MC, McGann JP.   +5 more
europepmc   +1 more source

Accelerated Materials Discovery Through In Situ X‐ray Diffraction: Solvothermal Formation of PdxMy (M═Si, Ge, Sn, Pb) Intermetallic Nanoparticles

Advanced Materials, EarlyView.
In situ PXRD data on solvothermal reactions accelerate materials discovery while simultaneously providing fundamental insights into complex crystal formation processes. Using PdxMy (M = Si, Ge, Sn, Pb) as an example, a general formation mechanism is identified, and specific synthesis strategies for ex situ preparation of SnPd2, Sn13Pd20, and SnPd ...
Anders Bæk Borup, Bo Brummerstedt Iversen   +1 more
wiley   +1 more source

Oxytocin attenuates fear learning via enhancing somatostatin interneuron-mediated local GABAergic inhibition in the prelimbic cortex. [PDF]

Sci Adv
Xu H, Li Y, Cui X, Zhang Y, Wu X, Zhuo SS, He M, Xiao L.   +7 more
europepmc   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health

Advanced Materials, EarlyView.
This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim, Seungwon Yoo, Tae Woog Kang, Yunuo Huang, Woon‐Hong Yeo   +4 more
wiley   +1 more source