Results 191 to 200 of about 1,393,170 (285)

Photoswitching Conduction in Framework Materials

Advanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez, Stefan Hecht, Wolfgang Wenzel, Lars Heinke, Mariana Kozlowska   +4 more
wiley   +1 more source

Fermi Surface Nesting and Anomalous Hall Effect in Magnetically Frustrated Mn2PdIn

Advanced Functional Materials, EarlyView.
Mn2PdIn, a frustrated inverse Heusler alloy, showing electronic‐structure driven anomalous Hall effect with Weyl crossings, Fermi‐surface nesting and near‐zero magnetization ideal for low‐magnetization spintronics. Abstract Noncollinear magnets with near‐zero net magnetization and nontrivial bulk electronic topology hold significant promise for ...
Afsar Ahmed, Arnab Bhattacharya, Prashant Singh, Ajay Kumar, Tukai Singha, Anis Biswas, Yaroslav Mudryk, I. Das   +7 more
wiley   +1 more source

Influence of working memory overload on emotional processing and recognition memory: An fNIRS study. [PDF]

Mem Cognit
Moya C, Fuentes-Sánchez N, Martínez-Sáez MC, Ros L, Latorre JM.   +4 more
europepmc   +1 more source

Self‐Immolative Activatable Nanoassembly toward Immuno‐Photodynamic Therapy in TME

Advanced Functional Materials, EarlyView.
A quinone methide‐gated, self‐immolative, H2O2‐responsive nano‐photosensitizer (Pyz/PS) is developed for targeted immuno‐photodynamic therapy. Pyz/PS selectively activates within tumor microenvironments, restores photosensitizer activity, generates ROS, and depletes intracellular GSH, enhancing oxidative stress.
Jing Li, E Pang, Snehasish Debnath, Jia Hong, Aojun Qiu, Dongeun Kim, Goeun Kim, Minhuan Lan, Min‐Goo Lee, Qian‐Yong Cao, Jong Seung Kim   +10 more
wiley   +1 more source

Sequential dependencies in recognition memory are decision based. [PDF]

Q J Exp Psychol (Hove)
Dollois MA, Fiacconi CM.
europepmc   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Impairment of Spatial Working Memory but Preservation of Recognition Memory in Female Rats with Spontaneous Absence Seizures. [PDF]

Neurochem Res
Neuparth-Sottomayor M, Morais TP, Good M, Sebastião AM, Di Giovanni G, Crunelli V, Vaz SH.   +6 more
europepmc   +1 more source

Multicolor Optoelectronic Synapse Enabled by Photon‐Modulated Remote Doping in Solution‐Processed Van Der Waals Heterostructures

Advanced Functional Materials, EarlyView.
Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim, Hyunbin Kim, Gang Jin Cheon, Dohyun Lee, In Soo Kim, Uiyeon Won, Jongseok Lee, Sang Min Won, Joohoon Kang   +8 more
wiley   +1 more source

Targeting CA2 Perineuronal Nets Restores Recognition Memory and Theta Oscillations in Aged Mice. [PDF]

Aging Cell
Mehak SF, Shivakumar AB, Jijimon F, Gupta A, Pillai VG, Gangadharan G.   +5 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source