Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Jiazhen He"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract How many near-neighbors does a molecule have? This fundamental question in chemistry is crucial for molecular optimization problems under the similarity principle assumption. Generative models can sample molecules from a vast chemical space
Externí odkaz:
https://doaj.org/article/33626a8e13b440e18e005f3c5b5ffc4c
Autor:
Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-15 (2024)
Abstract Designing compounds with a range of desirable properties is a fundamental challenge in drug discovery. In pre-clinical early drug discovery, novel compounds are often designed based on an already existing promising starting compound through
Externí odkaz:
https://doaj.org/article/e73ae601958648b29407a92e9414254a
Autor:
Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin, Ola Engkvist
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-16 (2024)
Abstract REINVENT 4 is a modern open-source generative AI framework for the design of small molecules. The software utilizes recurrent neural networks and transformer architectures to drive molecule generation. These generators are seamlessly embedde
Externí odkaz:
https://doaj.org/article/0bb4fcc6450445e78460e6559e9fdbfc
Publikováno v:
Case Studies in Thermal Engineering, Vol 58, Iss , Pp 104404- (2024)
Operators in thermal hazardous environments are more susceptible to burns during physical motion due to the potential deformation of thermal protective clothing. To study the influence of fabric deformation on heat transfer, a model of a three-layer
Externí odkaz:
https://doaj.org/article/d4218c482c404d3a8e5e874a9933c9b2
Autor:
Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-12 (2023)
Abstract Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for generating compound pairs to train Si
Externí odkaz:
https://doaj.org/article/10381a29e0844082b6416bac76c4e32a
Publikováno v:
Materials, Vol 17, Iss 11, p 2563 (2024)
Amidst the rapid advancements in the fields of photovoltaics and optoelectronic devices, CsPbBr3 nanosheets (NSs) have emerged as a focal point of research due to their exceptional optical and electronic properties. This work explores the application
Externí odkaz:
https://doaj.org/article/360f5f4b2d054f8f80c4881792ceadfa
Autor:
Jiazhen He, Hang Li, Chengqi Liu, Xiaoqian Wang, Qi Zhang, Jinfeng Liu, Mingwei Wang, Yong Liu
Publikováno v:
Materials, Vol 17, Iss 10, p 2173 (2024)
Metal halide perovskite semiconductors have emerged as promising materials for various optoelectronic applications due to their unique crystal structure and outstanding properties. Among different forms, perovskite nanowires (NWs) offer distinct adva
Externí odkaz:
https://doaj.org/article/12772da8c5bb47a9bd5e835c55600f7c
Autor:
Hang Li, Jiazhen He, Xiaoqian Wang, Qi Liu, Xuemin Luo, Mingwei Wang, Jinfeng Liu, Chengqi Liu, Yong Liu
Publikováno v:
Materials, Vol 17, Iss 7, p 1607 (2024)
As a direct band gap semiconductor, perovskite has the advantages of high carrier mobility, long charge diffusion distance, high defect tolerance and low-cost solution preparation technology. Compared with traditional metal halide perovskites, which
Externí odkaz:
https://doaj.org/article/b6a688b3d80144e0a870926e4877a5c7
Autor:
Karolina Kwapien, Eva Nittinger, Jiazhen He, Christian Margreitter, Alexey Voronov, Christian Tyrchan
Publikováno v:
ACS Omega, Vol 7, Iss 30, Pp 26573-26581 (2022)
Externí odkaz:
https://doaj.org/article/4b37582a47ca4c40be452cd25aae695e
Autor:
Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist
Publikováno v:
Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-14 (2022)
Abstract Molecular optimization aims to improve the drug profile of a starting molecule. It is a fundamental problem in drug discovery but challenging due to (i) the requirement of simultaneous optimization of multiple properties and (ii) the large c
Externí odkaz:
https://doaj.org/article/305c5561153a4e0a8b809bbb8268b7d8