Zobrazeno 1 - 10
of 565
pro vyhledávání: '"Keith A. Brown"'
Autor:
Kelsey L. Snapp, Benjamin Verdier, Aldair E. Gongora, Samuel Silverman, Adedire D. Adesiji, Elise F. Morgan, Timothy J. Lawton, Emily Whiting, Keith A. Brown
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Energy absorbing efficiency is a key determinant of a structure’s ability to provide mechanical protection and is defined by the amount of energy that can be absorbed prior to stresses increasing to a level that damages the system to be pr
Externí odkaz:
https://doaj.org/article/7aa34c5e75924b1c87cf1c9f33b16023
Publikováno v:
HardwareX, Vol 20, Iss , Pp e00601- (2024)
The automated soft matter indenter (ASMI) is a platform for rapidly performing mechanical characterization of samples with elastic moduli in the range 7 kPa to 67 MPa with a sample acquisition time between 1 and 10 min. It is a low-cost system based
Externí odkaz:
https://doaj.org/article/40e1084287af4d4085ca21db95ebf59f
Autor:
Adedire D. Adesiji, Keith A. Brown
Publikováno v:
AIP Advances, Vol 14, Iss 4, Pp 045306-045306-7 (2024)
The polar bear and several other Arctic mammals use fur composed of hollow-core fibers to survive in extremely cold environments. Here, we use finite element analysis to elucidate the role that the hollow core plays in regulating thermal transport. S
Externí odkaz:
https://doaj.org/article/ba4d65dfc94f4a26b973a3304ba9e623
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations such as parallel imaging, compressed sensing, and deep learning-
Externí odkaz:
https://doaj.org/article/5d3f77676e864a2f97a43f65e7d4e79b
Autor:
Qiaohao Liang, Aldair E. Gongora, Zekun Ren, Armi Tiihonen, Zhe Liu, Shijing Sun, James R. Deneault, Daniil Bash, Flore Mekki-Berrada, Saif A. Khan, Kedar Hippalgaonkar, Benji Maruyama, Keith A. Brown, John Fisher III, Tonio Buonassisi
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
Abstract Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range of experimental materials domains. In this work,
Externí odkaz:
https://doaj.org/article/bfc6d1e9f14b4b8bbc093f32c3360b8c
Autor:
Keith A. Brown
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-3 (2022)
Research and games both require the participant to make a series of choices. Active learning is a process borrowed from machine learning for algorithmically making choices that has become increasingly used to accelerate materials research. While this
Externí odkaz:
https://doaj.org/article/7a43f03cc201413d803185166bd63b0b
Publikováno v:
Polymers, Vol 15, Iss 17, p 3595 (2023)
Photoactuated pens have emerged as promising tools for expedient, mask-free, and versatile nanomanufacturing. However, the challenge of effectively controlling individual pens in large arrays for high-throughput patterning has been a significant hurd
Externí odkaz:
https://doaj.org/article/6de729de65fc44678e95c6b485a56dfa
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-7 (2021)
Atomic force microscopy (AFM) provides high resolution, but is limited to small areas. Here, the authors introduce a massively parallel AFM approach with >1000 probes in a cantilever-free probe architecture, and present an optical method for detectin
Externí odkaz:
https://doaj.org/article/bccd72b3b038477b86a10cffc2921a7f
Autor:
Keith A. Brown, Grace X. Gu
Publikováno v:
Advanced Intelligent Systems, Vol 3, Iss 12, Pp n/a-n/a (2021)
Externí odkaz:
https://doaj.org/article/6c11cb0cab8344baa546a0a8ea72fff8
Autor:
Aldair E. Gongora, Kelsey L. Snapp, Emily Whiting, Patrick Riley, Kristofer G. Reyes, Elise F. Morgan, Keith A. Brown
Publikováno v:
iScience, Vol 24, Iss 4, Pp 102262- (2021)
Summary: Autonomous experimentation (AE) accelerates research by combining automation and machine learning to perform experiments intelligently and rapidly in a sequential fashion. While AE systems are most needed to study properties that cannot be p
Externí odkaz:
https://doaj.org/article/fe4cdcd285994736a58c67f60e0615ef