Results 191 to 200 of about 1,739,986 (280)

Assessing the Divergent Soil Phosphorus Recovery Strategies in Domesticated and Wild Crops. [PDF]

Plants (Basel)
Dixon MM, Vivanco JM.
europepmc   +1 more source

Phosphorus recovery from phosphorus-containing pond sludge

Environment International, 1988
openaire   +1 more source

Coprecipitation‐Enabled Scalable Synthesis of High‐Energy Density Polyanion‐Integrated Disordered Rocksalt Cathodes for Lithium‐Ion Batteries

Advanced Energy Materials, EarlyView.
A coprecipitation‐enabled solid‐state route enables scalable synthesis of the metastable polyanion‐integrated disordered rocksalt cathode, Li1.67Mn1.5P0.17O4, without mechanochemical phase formation or post‐synthesis pulverization. Coprecipitation establishes local Mn–P–O integration in the precursor, while eutectic LiOH/LiNO3‐assisted lithiation ...
Hsi Chen, Yung‐An Chen, Chen Chang, Frances M. Ross, Yimeng Huang, Ju Li   +5 more
wiley   +1 more source

Valorization of a Lanthanum-Modified Natural Feedstock for Phosphorus Recovery from Aqueous Solutions: Static and Dynamic Investigations. [PDF]

Materials (Basel)
Al-Nadabi H, Jellali S, Hamdi W, Al-Raeesi A, Al-Muqaimi F, Al-Tamimi A, Al-Sidairi A, Al-Hanai A, Al-Busaidi W, Al-Zeidi K, Al-Wardy M, Jeguirim M.   +11 more
europepmc   +1 more source

Chemical Rounding Suppresses Morphology‐Induced Interfacial Losses in Perovskite–Silicon Tandem Solar Cells

Advanced Energy Materials, EarlyView.
Chemical rounding transforms irregular submicron silicon textures into more favorable interfaces for perovskite–silicon tandems. Suppressed local epitaxial ordering improves bottom‐cell passivation, while the top‐cell stack exhibits a higher and more spatially uniform quasi‐Fermi‐level splitting, enabling monolithic tandem solar cells with an ...
Nan Sun, Binbin Xu, Gaosheng Huang, Yuehui Li, Karsten Bittkau, Eunseo Noh, Sercan Aslan, Andreas Lambertz, Sang Il Seok, Michael Saliba, Christoph J. Brabec, Thomas Kirchartz, Kaining Ding   +12 more
wiley   +1 more source

31P Solid‐State NMR‐Enabled Development of a Pt/Aluminum Tripolyphosphate Catalyst for Selective C─O Bond Hydrogenolysis of Phenols

Angewandte Chemie, EarlyView.
31P solid‐state nuclear magnetic resonance analysis revealed the presence of aluminum tripolyphosphate on the surface of a platinum/aluminum condensed phosphate mixture (ACPM) catalyst. This finding led to the development of a Pt/aluminum tripolyphosphate (Pt/ATPP) catalyst for the selective hydrogenolysis of phenols to arenes.
Kento Oshida, Akito Ai, Shinji Tanaka, Yuichiro Okuzumi, Yuga Ezoe, Takeyuki Nogami, Rin Seki, Hiroki Miura, Tetsuya Shishido, Akira Nakayama, Xiongjie Jin, Kyoko Nozaki   +11 more
wiley   +2 more sources

Synthesis of Lanthanum-Modified Natural Magnetite: Characterization and Valorization for Phosphorus Recovery from Aqueous Solutions. [PDF]

Materials (Basel)
Al-Nadabi H, Jellali S, Hamdi W, Al-Tamimi A, Al-Raeesi A, Al-Sidairi A, Al-Busaidi W, Al-Hanai A, Al-Zeidi K, Al-Wardy M, Jeguirim M.   +10 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Pilot-scale phosphorus recovery from mobile toilet wastewater in Bangkok, Thailand. [PDF]

Sci Rep
Neamhom T, Yakam P, Bathbumrung C, Tachavarong W, Kosaisavee V, Pinatha Y.   +5 more
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source