Results 31 to 40 of about 108,933 (194)

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

Towards a Coherent Theory of Physics and Mathematics [PDF]

, 2002
As an approach to a Theory of Everything a framework for developing a coherent theory of mathematics and physics together is described. The main characteristic of such a theory is discussed: the theory must be valid and and sufficiently strong, and it ...
Benioff, Paul
core   +2 more sources

Integrable lattice spin models from supersymmetric dualities

, 2017
Recently, there has been observed an interesting correspondence between supersymmetric quiver gauge theories with four supercharges and integrable lattice models of statistical mechanics such that the two-dimensional spin lattice is the quiver diagram ...
A. G. Izergin, A. Gadde, A. Giveon, A. Hanany, A. Kapustin, A. Kuniba, A. P. Kels, A. P. Kels, A. P. Kels, A. Y. Volkov, A. Yu. Volkov, A. Zamolodchikov, B. Sutherland, C. Romelsberger, C.-N. Yang, E. Friedman, E. H. Lieb, E. Ising, F. A. Dolan, F. A. H. Dolan, F. Benini, F. Benini, F. Benini, F. Benini, F. J. van de Bult, F. Nieri, G. E. Andrews, G. Felder, G. Gehlen von, H. Au-Yang, H. Au-Yang, H. Saleur, I. B. Gahramanov, I. Frenkel, I. Gahramanov, I. Gahramanov, I. Gahramanov, I. Gahramanov, I. Gahramanov, I. Gahramanov, I. Gahramanov, I. Gahramanov, Ilmar Gahramanov, J. B. McGuire, J. Bhattacharya, J. H. H. Perk, J. H. Perk, J. Kinney, J. Nian, J. Terning, J. Teschner, J. V. Stokman, J. Yagi, J. Yagi, J. Yagi, K. A. Intriligator, K. Hasegawa, K. Hosomichi, K. Maruyoshi, L. A. Takhtadzhan, L. D. Faddeev, L. D. Faddeev, L. D. Faddeev, L. Onsager, M. Gaudin, M. J. Strassler, M. J. Strassler, M. Jimbo, M. Kashiwara, M. P. Bellon, M. Yamazaki, M. Yamazaki, M. Yamazaki, M. Yamazaki, M. Yamazaki, N. A. Nekrasov, N. A. Nekrasov, N. Doroud, N. Hama, N. Seiberg, O. Aharony, O. Aharony, P. A. Pearce, P. A. Pearce, P. P. Kulish, P. P. Kulish, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, R. J. Baxter, S. E. Derkachov, S. E. Derkachov, S. Elitzur, S. Elitzur, S. Fomin, S. Kim, S. N. M. Ruijsenaars, Shahriyar Jafarzade, T. Deguchi, V. A. Fateev, V. P. Spiridonov, V. P. Spiridonov, V. P. Spiridonov, V. P. Spiridonov, V. P. Spiridonov, V. P. Spiridonov, V. P. Spiridonov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, V. V. Bazhanov, Y. Imamura, Y. Imamura, Y. Imamura, Yu. G. Stroganov, Yu. G. Stroganov   +124 more
core   +1 more source

Golden‐Ratio–Guided Aperiodic Architected Metamaterials with Simultaneously Enhanced Strength and Toughness

Advanced Functional Materials, EarlyView.
Guided by the golden ratio, a class of aperiodic architected metamaterials is introduced to address the intrinsic trade‐off between strength and toughness. By unifying local geometric heterogeneity with global order, the golden‐ratio‐guided aperiodic architecture promotes spatial delocalization of damage tolerence regions, leading to more tortuous ...
Junjie Deng, Xinxin Wang, Ruochao Zhao, Zhendong Li, Kai Liu, Ke Yuan, Jia An, Xinwei Li, Chee Kai Chua, Zhonggang Wang   +9 more
wiley   +1 more source

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Advanced Functional Materials, EarlyView.
In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang, Rohan Dhall, Matthew M. Schneider, Cun Li, Chengyu Song, Sundar Kunwar, Hongyi Dou, Natanii R. Yazzie, Henry Tran, Daniel Appuing, Jim Ciston, Nicholas G. Cucciniello, Pinku Roy, Michael T. Pettes, John Watt, Winson Kuo, Haiyan Wang, Ye Cao, Rodney J. McCabe, Aiping Chen   +19 more
wiley   +1 more source

Three‐dimensional Antimony Sulfide Based Flat Optics

Advanced Functional Materials, EarlyView.
This work presents the development of a grayscale electron beam lithography (g‐EBL) method for fabricating antimony trisulfide (Sb2S3) nanostructures with customizable 3D profiles. The refractive index of g‐EBL patterned Sb2S3 is determined based on the synergy of genetic algorithm and transfer matrix method.
Wei Wang, Uwe Hübner, Anne Gärtner, Tao Chen, Joseph Köbel, Franka Jahn, Daniel Repp, Abhrodeep Dey, Henrik Schneidwind, Andrea Dellith, Jan Dellith, Torsten Wieduwilt, Matthias Zeisberger, Tanveer Ahmed Shaik, Astrid Bingel, Markus A. Schmidt, Jer‐Shing Huang, Ulf Peschel, Volker Deckert   +18 more
wiley   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +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

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source

Ceramic Particle‐Reinforced Medium‐Entropy Alloys With Outstanding Mechanical Properties Prepared by Novel Micro‐LPBF

Advanced Functional Materials, EarlyView.
An innovative medium entropy alloy (MEA) composite material was fabricated via micro laser powder bed fusion (μ‐LPBF) with appropriate nano‐ceramic particles doping and exhibited markedly improved overall performance, including synergistically enhanced strength and ductility, increased hardness and compressive strength, improved wear resistance and ...
Zhonglin Shen, Mingwang Fu
wiley   +1 more source