Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ivan Jayapurna"'
Autor:
Zhiyuan Ruan, Shuni Li, Alexandra Grigoropoulos, Hossein Amiri, Shayna L. Hilburg, Haotian Chen, Ivan Jayapurna, Tao Jiang, Zhaoyi Gu, Alfredo Alexander-Katz, Carlos Bustamante, Haiyan Huang, Ting Xu
Publikováno v:
Nature. 615:251-258
Publikováno v:
Biomacromolecules, vol 24, iss 2
Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent
Publikováno v:
Macromolecules. 54:1006-1016
The polymer chain architecture is an important factor determining the phase behavior of nanoparticle (NP) assembly in polymer matrices. Block copolymers (BCPs) containing a random copolymer (RCP) block present a convenient variation on traditional BC
Autor:
Kyle Zolkin, Ivan Jayapurna, Christopher DelRe, Ting Xu, Boyce S. Chang, Ariel Wang, Aaron Hall
Publikováno v:
Advanced materials (Deerfield Beach, Fla.). 33(49)
Embedding catalysts inside of plastics affords accelerated chemical modification with programmable latency and pathways. Nanoscopically embedded enzymes can lead to near complete degradation of polyesters via chain-end mediated processive depolymeriz
Autor:
Junpyo Kwon, Christopher DelRe, Philjun Kang, Aaron Hall, Daniel Arnold, Ivan Jayapurna, Le Ma, Matthew Michalek, Robert O. Ritchie, Ting Xu
Publikováno v:
Advanced Materials. 34:2202177
Electronic waste carries energetic costs and an environmental burden rivaling that of plastic waste due to the rarity and toxicity of the heavy-metal components. Recyclable conductive composites are introduced for printed circuits formulated with pol
Autor:
Christopher, DelRe, Yufeng, Jiang, Philjun, Kang, Junpyo, Kwon, Aaron, Hall, Ivan, Jayapurna, Zhiyuan, Ruan, Le, Ma, Kyle, Zolkin, Tim, Li, Corinne D, Scown, Robert O, Ritchie, Thomas P, Russell, Ting, Xu
Publikováno v:
Nature. 592(7855)
Successfully interfacing enzymes and biomachinery with polymers affords on-demand modification and/or programmable degradation during the manufacture, utilization and disposal of plastics, but requires controlled biocatalysis in solid matrices with m
Autor:
Andrew Favor, Ivan Jayapurna
This study analyzes and adds to the Low-N protein engineering with data-efficient deep learning work done by Biswas et al. We provide a complete, open-source, end-to-end re-implementation of the in silico protein engineering pipeline with improved co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d41a1410a0087b5118e73dc6a892bda
https://doi.org/10.22541/au.159683529.96283070
https://doi.org/10.22541/au.159683529.96283070