Editorial Material
Chemistry, Physical
Hongli Zhu
Summary: The study demonstrates the pilot scale roll-to-roll synthesis of sulfonated poly(ether ether ketone) (SPEEK) membrane and the scaling up of zinc flow batteries (ZFBs) stack, showing a significant cost reduction from $500-1500 per square meter for Nafion membranes to $12 per square meter for SPEEK membranes. This cost reduction will drive the usage of flow battery systems in large-scale energy storage applications.
Article
Materials Science, Multidisciplinary
Tongzhao Gong, Yun Chen, Xing-Qiu Chen, Dianzhong Li, Guillaume Reinhart, Henri Nguyen-Thi, Jean -Marc Debierre
Summary: The effect of mutual misorientation between two equiaxed dendrites on the growth scaling law is investigated through phase-field simulations of Al-Cu alloy solidification. It is found that the growth kinetics of equiaxed dendrites changes when considering mutual grain misorientation, and the misorientation can be correlated linearly to the characteristic growth rate and primary dendritic arm length. The newly proposed scaling law, which takes the grain orientation into account, shows better agreement with experimental data compared to the previous scaling law that only considers face-to-face growth of two dendrites.
COMPUTATIONAL MATERIALS SCIENCE
(2023)
Article
Chemistry, Physical
Yuxuan Cosmi Lin, Zafer Mutlu, Gabriela Borin Barin, Yejin Hong, Juan Pablo Llinas, Akimitsu Narita, Hanuman Singh, Klaus Muellen, Pascal Ruffieux, Roman Fasel, Jeffrey Bokor
Summary: We propose a strategy to connect nanomaterial morphologies and device performance through a Monte Carlo device model, and apply it to understand the scaling trends of bottom-up synthesized armchair graphene nanoribbon (GNR) transistors. We systematically investigate the impacts of GNR spatial distributions and device geometries on device performance by comparing experimental data with the model. This study identifies challenges and opportunities for transistor technologies based on bottom-up synthesized GNRs, paving the way for further improvement of GNR device performance for future transistor technology nodes.
Article
Psychology, Biological
Sacha Altay, Marlene Schwartz, Anne-Sophie Hacquin, Aurelien Allard, Stefaan Blancke, Hugo Mercier
Summary: In a Registered Report, Altay et al. found that knowledge of the scientific consensus on GMOs reduces the gap between public opinion and scientists. They created a chatbot to emulate discussion and found that providing good arguments rebutting common counterarguments led to more positive attitudes towards GMOs. However, there was no evidence that an interactive chatbot is more persuasive than a list of arguments and counterarguments.
NATURE HUMAN BEHAVIOUR
(2022)
Article
Energy & Fuels
Xianbiao Bu, Kunqing Jiang, Xianlong Wang, Xiao Liu, Xianfeng Tan, Yanlong Kong, Lingbao Wang
Summary: Calcium carbonate precipitation is a common problem in geothermal industry. This study investigates the whole process of scaling and antiscaling, including analysis, simulation, equipment design, experiments, and evaluation. The results show that injecting inhibitors below the flashing point effectively solves the problem of calcium carbonate precipitation.
Article
Chemistry, Multidisciplinary
Runnan Zhou, Huiying Zhong, Peng Ye, Jianguang Wei, Dong Zhang, Lianbin Zhong, Tianyu Jiao
Summary: This study analyzed the impact of strong alkali-surfactant-polymer flooding on the core mineral composition and pore structure of heterogeneous reservoirs, finding that it reduces quartz and kaolinite content, generates new mineral compositions, and causes pore blockage leading to reduced permeability.
Article
Chemistry, Multidisciplinary
Runnan Zhou, Huiying Zhong, Peng Ye, Jianguang Wei, Dong Zhang, Lianbin Zhong, Tianyu Jiao
Summary: Most mature oilfields face difficulty in exploitation. Alkaline-surfactant-polymer (ASP) flooding is commonly used in Daqing Oilfield to enhance oil recovery. However, scaling issues hinder its large-scale application. This study investigates the damage and scaling mechanisms of strong alkali-surfactant-polymer (SASP) flooding in high clay mineral content reservoirs. The results show that SASP corrosion reduces quartz and kaolinite content while increasing the illite/montmorillonite mixed layer. Additionally, chlorite and secondary quartz generation occurs, and clay particles and sediment block pore throats, reducing core seepage capacity.
Article
Chemistry, Multidisciplinary
Leidy Rendon-Castrillon, Margarita Ramirez-Carmona, Carlos Ocampo-Lopez, Luis Gomez-Arroyave
Summary: The study developed a mathematical model combining experimental design and dimensional analysis to predict the scaling up of bioprocesses. Through correlation analysis and a non-linear model, dimensionless factors affecting system behavior were identified.
APPLIED SCIENCES-BASEL
(2021)
Editorial Material
Biochemical Research Methods
Lin Tang
Summary: Progressive Cactus allows reference-free multiple-genome alignment for massive datasets.
Article
Chemistry, Physical
Ruihan Wu, Boyu Peng, Huanbin Li, Hanying Li
Summary: Organic heterojunctions composed of binary organic single crystals can exhibit superior electrical/optoelectrical performance as well as novel functions, but large-scale preparation remains a challenge. Possible solutions include two-step crystallization and one-step crystallization methods.
CHEMISTRY OF MATERIALS
(2021)
Article
History & Philosophy Of Science
Helen E. Longino
Summary: This paper discusses the need for pluralism when explaining behavior, proposing three different ways in which behavior can be conceptualized, leading to different types of research questions.
Article
Computer Science, Artificial Intelligence
Bin Gu, Zhiyuan Dang, Zhouyuan Huo, Cheng Deng, Heng Huang
Summary: This paper introduces a general sparse kernel learning formulation based on random feature approximation to tackle the challenge of big data era. A new large-scale sparse kernel learning algorithm (AsyDSSKL) is proposed using techniques of asynchronous parallel computation and doubly stochastic optimization. Experimental results demonstrate that AsyDSSKL has significant superiority in computational efficiency over existing kernel methods.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
News Item
Chemistry, Multidisciplinary
Jongmin Kim, Friedrich C. Simmel
Summary: DNA nanotechnology and synthetic biology aim to expand the range of dynamic behaviors exhibited by biomolecules. The programmability of synthetic transcriptional circuits has been improved to enable synthesis of dynamic biomolecular circuits with unmatched complexity.
Editorial Material
Optics
Daniel F. Santavicca
Summary: Superconducting nanowire single-photon detectors, known for their excellent performance, face challenges in developing large-format imaging arrays. However, a new approach utilizing sectioning a single nanowire has enabled an eightfold improvement in spatial resolution and the creation of a 1,024-pixel imager.
Article
Mechanics
Yong Han, Ling Zhou, Ling Bai, Weidong Shi, Ramesh Agarwal
Summary: Turbulence modeling is essential for accurate prediction of turbulent fluid motion, and a new one-equation Wray-Agarwal (WA) turbulence model has been developed to improve predictions for turbulent flows with large separation and curvature. Comparison with other commonly used turbulence models shows that the WA model gives the highest accuracy in predicting the complex three-dimensional turbulent characteristics of flow with large curvature in a U-bend.
Article
Plant Sciences
Frederic Baret, Simon Madec, Kamran Irfan, Jeremy Lopez, Alexis Comar, Matthieu Hemmerle, Dan Dutartre, Sebastien Praud, Marie Helene Tixier
JOURNAL OF EXPERIMENTAL BOTANY
(2018)
Article
Biochemical Research Methods
Jingyi Jiang, Alexis Comar, Philippe Burger, Pierre Bancal, Marie Weiss, Frederic Baret
Article
Biochemistry & Molecular Biology
Daniel Reynolds, Frederic Baret, Claude Welckere, Aaron Bostrom, Joshua Ball, Francesco Cellini, Argelia Lorence, Aakash Chawade, Mehdi Khafif, Koji Noshita, Mark Mueller-Linow, Ji Zhou, Francois Tardieu
Article
Environmental Sciences
A. Bablet, P. V. H. Vu, S. Jacquemoud, F. Viallefont-Robinet, S. Fabre, X. Briottet, M. Sadeghi, M. L. Whiting, F. Baret, J. Tian
REMOTE SENSING OF ENVIRONMENT
(2018)
Article
Environmental Sciences
Sylvain Jay, Frederic Baret, Dan Dutartre, Ghislain Malatesta, Stephanie Heno, Alexis Comar, Marie Weiss, Fabienne Maupas
REMOTE SENSING OF ENVIRONMENT
(2019)
Article
Agronomy
Simon Madec, Xiuliang Jin, Hao Lu, Benoit De Solan, Shouyang Liu, Florent Duyme, Emmanuelle Heritier, Frederic Baret
AGRICULTURAL AND FOREST METEOROLOGY
(2019)
Review
Geochemistry & Geophysics
Hongliang Fang, Frederic Baret, Stephen Plummer, Gabriela Schaepman-Strub
REVIEWS OF GEOPHYSICS
(2019)
Article
Plant Sciences
Shouyang Liu, Pierre Martre, Samuel Buis, Mariem Abichou, Bruno Andrieu, Frederic Baret
Article
Environmental Sciences
Giulia Tagliabue, Cinzia Panigada, Benjamin Dechant, Frederic Baret, Sergio Cogliati, Roberto Colombo, Mirco Migliavacca, Patrick Rademske, Anke Schickling, Dirk Schuttemeyer, Jochem Verrelst, Uwe Rascher, Youngryel Ryu, Micol Rossini
REMOTE SENSING OF ENVIRONMENT
(2019)
Article
Plant Sciences
Justin Blancon, Dan Dutartre, Marie-Helene Tixier, Marie Weiss, Alexis Comar, Sebastien Praud, Frederic Baret
FRONTIERS IN PLANT SCIENCE
(2019)
Article
Environmental Sciences
Jingyi Jiang, Marie Weiss, Shouyang Liu, Nadia Rochdi, Frederic Baret
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Agronomy
K. Velumani, R. Lopez-Lozano, S. Madec, W. Guo, J. Gillet, A. Comar, F. Baret
Summary: Early-stage plant density is a crucial trait for determining the fate of a genotype in specific environmental conditions and management practices. The use of high-resolution RGB images from UAVs can significantly improve plant detection and counting performance, especially when trained on high-resolution images. Additionally, training on a mixture of high- and low-resolution images can lead to good performances on both types of images.
Article
Agronomy
Wenjuan Li, Alexis Comar, Marie Weiss, Sylvain Jay, Gallian Colombeau, Raul Lopez-Lozano, Simon Madec, Frederic Baret
Summary: A new image acquisition configuration is proposed based on two focal length optics, reducing the time required to cover the same area by half by adding a 4.2 mm focal length optics to the standard 8 mm optics of the multispectral camera.
Article
Agronomy
Mario Serouart, Simon Madec, Etienne David, Kaaviya Velumani, Raul Lopez Lozano, Marie Weiss, Frederic Baret
Summary: This study presents a method for pixel segmentation of high-resolution RGB images into vegetation classes. The method achieves accurate segmentation of the images into background, green, and senescent vegetation classes. However, some confusion is observed between the background and senescent vegetation, especially in dark and bright regions. The study also finds that the SVM method provides more precise delineation of the green and senescent patches compared to the convolutional nature of U-net.
Article
Plant Sciences
Shouyang Liu, Frederic Baret, Mariem Abichou, Loic Manceau, Bruno Andrieu, Marie Weiss, Pierre Martre
Summary: This study analyzed the canopy light interception models of 26 wheat agricultural models and found that current models have not been evaluated with experimental data. Through field experiments, the K-ell(C) model was found to outperform current approaches under most lighting conditions, and the uncertainty in wheat growth and final yield due to light models could be as high as 45%. Therefore, there is a call for an overhaul of light interception models in crop growth models.
Article
Computer Science, Interdisciplinary Applications
Yapo Abole Serge Innocent Oboue, Yunfeng Chen, Sergey Fomel, Wei Zhong, Yangkang Chen
Summary: Strong noise can disrupt the recorded seismic waves and negatively impact subsequent seismological processes. To improve the signal-to-noise ratio (S/N) of seismological data, we introduce MATamf, an open-source MATLAB code package based on an advanced median filter (AMF) that simultaneously attenuates various types of noise and improves S/N. Experimental results demonstrate the usefulness and advantages of the proposed AMF workflow in enhancing the S/N of a wide range of seismological applications.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Upkar Singh, P. N. Vinayachandran, Vijay Natarajan
Summary: The Bay of Bengal maintains its salinity distribution due to the cyclic flow of high salinity water and the mixing with freshwater. This paper introduces an advection-based feature definition and algorithms to track the movement of high salinity water, validated through comparison with observed data.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Bijal Chudasama, Nikolas Ovaskainen, Jonne Tamminen, Nicklas Nordback, Jon Engstro, Ismo Aaltonen
Summary: This contribution presents a novel U-Net convolutional neural network (CNN)-based workflow for automated mapping of bedrock fracture traces from aerial photographs acquired by unmanned aerial vehicles (UAV). The workflow includes training a U-Net CNN using a small subset of photographs with manually traced fractures, semantic segmentation of input images, pixel-wise identification of fracture traces, ridge detection algorithm and vectorization. The results show the effectiveness and accuracy of the workflow in automated mapping of bedrock fracture traces.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Ruizhen Wang, Siyang Wan, Weitao Chen, Xuwen Qin, Guo Zhang, Lizhe Wang
Summary: This paper proposes a novel framework to generate a finer soil strength map based on RCI, which uses ensemble learning models to obtain USCS soil classification and predict soil moisture, in order to improve the resolution and reliability of existing soil strength maps.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhanlong Chen, Xiaochuan Ma, Houpu Li, Xuwei Xu, Xiaoyi Han
Summary: Simulated terrains are important for landform and terrain research, disaster prediction, rescue and disaster relief, and national security. This study proposes a deep learning method, IGPN, that integrates global information and pattern features of the local terrain to generate accurate simulated terrains quickly.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Daniele Secci, Vanessa A. Godoy, J. Jaime Gomez-Hernandez
Summary: Neural networks excel in various machine learning applications, but lack physical interpretability and constraints, limiting their accuracy and reliability in predicting complex physical systems' behavior. Physics-Informed Neural Networks (PINNs) integrate neural networks with physical laws, providing an effective tool for solving physical problems. This article explores recent developments in PINNs, emphasizing their application in solving unconfined groundwater flow, and discusses challenges and opportunities in this field.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Renguang Zuo, Ying Xu
Summary: This study proposes a hybrid deep learning model consisting of a one-dimensional convolutional neural network (1DCNN) and a graph convolutional network (GCN) to extract joint spectrum-spatial features from geochemical survey data for mineral exploration. The physically constrained hybrid model performs better in geochemical anomaly recognition compared to other models.
COMPUTERS & GEOSCIENCES
(2024)
