Results 181 to 190 of about 162,670 (276)

Protocol for monitoring the growth of Solanum betaceum non-embryogenic callus using electrochemical impedance spectroscopy. [PDF]

STAR Protoc
Caeiro A, Canhoto J, Rocha PRF.
europepmc   +1 more source

Powering the Future: A Cobalt‐Based Catalyst for Longer‐Lasting Zinc–Air Batteries

Advanced Functional Materials, EarlyView.
A novel N‐doped graphitic shell‐encapsulated Co catalyst reveals superior bifunctional ORR/OER activity in alkaline media, empowering outstanding liquid and quasi‐solid‐state ZAB activity. The system delivers long‐term durability, a peak power density of 127 mW cm−2 and successfully powers an LED and a mini fan.
Manami Banerjee, Peng Ren, Greesh Kumar, Lucie Lindenbeck, Byoung Joon Park, Anna Rokicińska, Piotr Kuśtrowski, Adam Slabon, Francesco Ciucci, Ramendra Sundar Dey, Shoubhik Das   +10 more
wiley   +1 more source

Rate and mechanism of thiolate deligation in Au₂₅ nanoclusters <i>via in operando</i> electrochemical impedance spectroscopy. [PDF]

Chem Sci
Liu EZ, Parker SD, Tietje-Mckinney DP, Orozco M, Hayton TW, Sepunaru L.   +5 more
europepmc   +1 more source

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe2O3 → Fe3O4 → FeO Transformation

Advanced Functional Materials, EarlyView.
In situ TEM uncovers the atomic‐scale mechanisms underlying hydrogen‐driven γ‐Fe2O3→Fe3O4→FeO reduction. In γ‐Fe2O3, oxygen vacancies cluster around intrinsic Fe vacancies, leading to nanopore formation, whereas in Fe3O4, vacancy aggregation is suppressed, preserving a dense structure.
Yupeng Wu, Dongxiang Wu, Wenhui Zhu, Xiaobo Chen, Zhikang Zhou, Zhilu Liang, Shuonan Ye, Meng Li, Xiao Tong, Kim Kisslinger, Sooyeon Hwang, Dmitri Zakharov, Renu Sharma, Judith C. Yang, Guangwen Zhou   +14 more
wiley   +1 more source

Capacitive Coulometric Readout of Polyaniline Membrane-Based pH Sensors in Combination with Cyclic Voltammetry and Electrochemical Impedance Spectroscopy. [PDF]

Membranes (Basel)
Han T, Song T, Han D, Niu L.
europepmc   +1 more source

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

Advanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon, Soeun Park, Yeong Kwon Kim, Juhwan Baek, Ki Han Kim, Seongil Yun, Hyeonchang Son, Jeongeun Choi, Byung Chul Jang, Dong‐Ho Kang   +9 more
wiley   +1 more source

Metal-Mediated Il-8 Binding to Heparan Sulfate Evaluated by Electrochemical Impedance Spectroscopy. [PDF]

Chemistry
Shitrit A, Alshanski I, Mor K, Rademann J, Kikkeri R, Hurevich M, Yitzchaik S.   +6 more
europepmc   +1 more source

Trap‐Modified Inverted Organic Photodetectors via Layer‐by‐Layer Processing with Poly(N‐vinylcarbazole) Additives

Advanced Functional Materials, EarlyView.
Trap state engineering in inverted organic photodetectors (OPDs) is achieved via combined layer‐by‐layer (LbL) processing and poly(N‐vinylcarbazole) (PVK) incorporation. LbL reduces the trap density while PVK additives gradually shift trap states from shallow band‐edge to deep mid‐gap levels, tailoring the energy distribution.
Jingwei Yi, Yi Yang, Yusen Pei, Apurva Gadikar, Vahid Mahdikhah, Myratgeldi Kotyrov, Seung Hyun Kim, Kenan Gundogdu, Wei You, Harald Ade, Franky So   +10 more
wiley   +1 more source

Simultaneous and sensitive detection of <i>Mycobacterium tuberculosis</i> and SARS-CoV-2 antigens employing an electrochemical impedance spectroscopy aptasensor. [PDF]

Front Bioeng Biotechnol
Zhumabekova Z, Elebessov T, Pham TT, Kanayeva D.   +3 more
europepmc   +1 more source

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

Advanced 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, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source