Results 61 to 70 of about 4,035,149 (299)
a. Ecological footprint per capita. b. Ecological carrying capacity per capita.
Wenjun Chen (176385) +2 more
core +1 more source
Photo‐Degradable Polyester Networks and Multi‐Photon Printed Objects Based on Cyclic Ketene Acetals
The current work introduces a photoreversible polyester network derived from radical ring‐opening polymerization of cyclic ketene acetals. It combines photoreversible cross‐linking with initiator‐free multi‐photon printing. Reversible network formation, tunable mechanical properties, and selective degradation highlight its potential as a versatile ...
Till Meissner +5 more
wiley +1 more source
Evaluation of Ecological Carrying Capacity of Henan Province under the Sustainable Development [PDF]
Based on the overview of social economy of Henan Province, I probe into the concept and evaluation of ecological carrying capacity. By using the ecological footprint analysis and the data of various kinds of land supply of Henan Province from 2000 to ...
Jiang, Xiao-ping
core +1 more source
Biodegradable 3D‐Printable and Coatable Antifouling Composites for Marine Applications
Marine biofouling damages submerged surfaces and raises greenhouse gas emissions. Biodegradable antifouling biocomposites were developed by hot‐mixing beeswax, Tween 80, and calcium stearate or stearic acid. Adjusting the component ratio enables processing via hot‐pressing, 3D‐printing, or dip‐coating.
Gabriele Corigliano +17 more
wiley +1 more source
Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
This file contains the survey dataset and associated study instruments as reported in the publication by Duda et al, titled 'An evaluation of capacity strengthening within an international conservation agriculture research ...
Capacity Research, Centre for
core +1 more source
Stacked nanoflake assembly (SNA) membranes can oscillate autonomously, offering opportunities for soft actuation and energy harvesting. This work uncovers the physical mechanism behind the sustained oscillation of SNA membranes in gradient humidity and identifies three governing dimensionless parameters, enabling rational design for optimizing SNA ...
Zijing Zhang +5 more
wiley +1 more source
Analysis of Ecological Footprint of Guizhou Province in Recent Years
To quantitatively evaluate the state of ecological sustainable development in Guizhou,the ecological footprint analysis method was used to calculate and analyze the ecological footprints of Guizhou from 2007to2011 with the data from the statistical ...
LI Li, SU Wei-ci, LIU Can
doaj
This work introduces sustainable PLA/graphene oxide bioelectronic interfaces featuring electrodes with tunable conductivity and strong electrocatalytic performance. These platforms were used to implement a new method for tuning astrocyte Ca2+ signaling and for the efficient detection of key biomarkers.
Alessandra Scidà +15 more
wiley +1 more source

