Lars Bernhard Schöne
Aschaffenburg University of Applied Sciences
7 Papers
Lars Bernhard Schöne is an academic researcher from Aschaffenburg University of Applied Sciences. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 3, co-authored 7 publications. Previous affiliations of Lars Bernhard Schöne include Ocean University of China.
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Papers
Shape-controlled fabrication of cost-effective, scalable and anti-biofouling hydrogel foams for solar-powered clean water production
TL;DR: In this article , 3D hydrogel foams based on biopolymer composites are developed via a controlled foaming − gelation technique and applied to a monolithic interfacial steam generator.
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Fabrication of Monopile Polymer Foams via Rotating Gas Foaming: Hybrid Applications in Solar‐Powered Interfacial Evaporation and Water Remediation
TL;DR: In this article , a series of closed-cell 3D polymer foams is developed via a rotating gas-foaming technique, resulting in controlled shapes and heights, ultralight weight, efficient water diffusion, and optimized solar and environmental energy input.
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Ti-6Al-4V alloy strengthening via instantaneous phase transformation induced by electropulsing
TL;DR: In this paper , a simple process route based on electropulsing was proposed to strengthen the widely used Ti-6Al-4V alloy, which exhibited excellent mechanical properties (UTS = 1358 MPa, YS = 1280 MPa and EL = 13.7%).
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Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion
Scott D. Bridgham,Lifen Jiang,Avni Malhotra,Dong Ryeol Ryu,Milenko Vescovi,Ellis Ye Yuan,Lars Bernhard Schöne,Marc S. Levine,Jing Zheng,Oliver Cromwell,THOMAS F. MATHEWS,Raquel Barrena,None Stuart Burrows,Aihua Liu,Pallavi Dubey,Jonas T. Kaplan +15 more
TL;DR: In this paper , the ebullition bubble growth volume threshold approach (EBG) and modified Ebullition concentration threshold approach were used to simulate peatland CH4 emissions.
A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS
Kaixu Bai,Qiyun Guo,Sarfraz Ahmed Dakhan,Alperen Can,Jadelyn Abbott,Ruth MacLean,Lars Bernhard Schöne,Chun-Quan Zhang,Jolien Grandia,Aisha Abdel Hady,Sidney Waldron,DEAN RICKLES,Gerhard Schmidtke,Abdullah Al-Ghathami,Susanne Soretz +14 more
- 05 May 2022
TL;DR: Guo et al. as mentioned in this paper used a machine learning model to predict the PBLH bias at other grids across the globe with parameters acquired or derived from ERA5 and GLDAS.
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