Results 71 to 80 of about 384 (163)

Terahertz Volume Plasmon‐Polariton Modulation in All‐Dielectric Hyperbolic Metamaterials

Advanced Optical Materials, EarlyView.
THz volume plasmon‐polariton (VPP) propagation through plasmon‐based hyperbolic metamaterials, made of alternating layers of doped and undoped III‐V semiconductors. Abstract The development of plasmonics and related applications in the terahertz range faces limitations due to the intrinsic high electron density of the standard metals.
Stefano Campanaro, Luca Bursi, Stefano Curtarolo, Arrigo Calzolari   +3 more
wiley   +1 more source

ÐналÑз ÑÑнкÑÑÑ Ð½Ð¸Ñок Ñ ÑвоÑÐ¸Ñ Ð½Ð° ÑÑеÑеÑолÑÑÑаз, ÑÐºÐ¸Ñ Ð»ÑкÑвали за Ð´Ð¾Ð¿Ð¾Ð¼Ð¾Ð³Ð¾Ñ ÐµÐ½Ð´Ð¾ÑкопÑÑÐ½Ð¸Ñ Ð¼ÐµÑодÑв, залежно вÑд ÑеÑмÑнÑв пеÑебÑÐ²Ð°Ð½Ð½Ñ ÐºÐ¾Ð½ÐºÑеменÑÑв Ñ ÑеÑоводÑ

, 2015
Р. О. Білоруський, Ю. Б. Борис, В. В. Дмитріенко   +2 more
openalex   +2 more sources

Excitonic Landscapes in Monolayer Lateral Heterostructures Revealed by Unsupervised Machine Learning

Advanced Optical Materials, EarlyView.
Hyperspectral photoluminescence data from graded MoxW1 − xS2 alloys and monolayer MoS2–WS2 lateral heterostructures are analyzed using unsupervised machine learning. The combined use of PCA, t‐SNE, and DBSCAN uncovers distinct excitonic regions that trace how composition, strain, and defects modulate optical responses in these 2D materials.
Maninder Kaur, Nicolas T. Sandino, Jason P. Terry, Mahdi Ghafariasl, Yohannes Abate   +4 more
wiley   +1 more source

ÐлекÑÑодинамика и пÑинÑÐ¸Ð¿Ñ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ

, 2017
Виктор Сергеевич Макаров
openalex   +1 more source

Integration of Soft‐Robotics and Deep Learning to Assess the Coordinated Biosonar Emission and Reception Dynamics in Hipposiderid Bats

Advanced Robotics Research, EarlyView.
Combining a biomimetic soft‐robot with deep‐learning data analytics sheds light on a unique peripheral dynamics seen in the biosonar system of bats: Bats modulate their ultrasonic biosonar signals upon emission as well as reception with variable, yet highly coordinated motion patterns of their noseleaves and pinnae.
Shuxin Zhang, Ruihao Wang, Xiaoyan Yin, Luhui Yang, Rolf Müller   +4 more
wiley   +1 more source

Ðнализ влиÑÐ½Ð¸Ñ ÑезÑлÑÑаÑов деÑÑелÑноÑÑи доÑеÑÐ½Ð¸Ñ Ð¾ÑганизаÑий на показаÑели ÑинанÑовой оÑÑеÑноÑÑи Ñ Ð¾Ð»Ð´Ð¸Ð½Ð³Ð°

, 2017
Елизавета Вадимовна Попкова
openalex   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

ÐовÑÑÐ½Ñ Ð²Ð¿ÑÐ¾Ð²Ð°Ð´Ð¶ÐµÐ½Ð½Ñ Ð² педагогÑÑний пÑоÑÐµÑ Ð²Ð¸ÐºÐ»Ð°Ð´Ð°Ð½Ð½Ñ ÑадÑологÑÑ Ð½Ð° ÑÑеÑÑÐ¾Ð¼Ñ ÐºÑÑÑÑ Ð¼ÐµÐ´Ð¸Ñного ÑакÑлÑÑеÑÑ

, 2015
І. М. Леськів І. В. Жулкевич І. Й. Галайчук, Н. О. Загурська   +1 more
openalex   +2 more sources

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +1 more source

ÐоÑвÑд малоÑнвазивного лÑкÑÐ²Ð°Ð½Ð½Ñ Ð³Ð½Ñйно-деÑÑÑÑкÑÐ¸Ð²Ð½Ð¸Ñ Ð·Ð°ÑвоÑÑÐ²Ð°Ð½Ñ Ð½Ð¸Ñок Ñа паÑанеÑÑалÑÐ½Ð¾Ñ ÐºÐ»ÑÑковини

, 2015
А. В. Цепінь, А. І. Мисак, В. В. Твердохліб   +2 more
openalex   +2 more sources