Results 181 to 190 of about 29,867,150 (377)
An Iterative Method for Finding Stationary Values of a Function of Several Variables [PDF]
, 1962 M. J. D. Powell
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Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.By fabricating and covalently assembling gelatin methacryloyl (GelMA) porous microgels, a new class of granular hydrogel scaffolds with hierarchical porosity is developed. These scaffolds have a significantly higher void fraction than their counterparts made up of nonporous microgels, enhancing cell recruitment and tissue integration. This research may
Alexander Kedzierski +9 more
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An iterative method for computing the generalized inverse of an arbitrary matrix [PDF]
, 1965 Adi Ben-Israel
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Advanced Functional Materials, EarlyView.The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu +2 more
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Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia. [PDF]
PeerJ Comput Sci, 2020 Ali AQ +3 more
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AN ITERATIVE METHOD FOR SOLVING SYSTEMS OF LINEAR EQUATIONS
, 1951 Ana Laura de la Garza
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Advanced Functional Materials, EarlyView.Unravelling charge transport mechanisms in graphene nanosheet networks: by combining temperature‐dependent conductivity measurements with a Random Resistor Network model, this study identifies a transition from hopping‐dominated conduction to a band‐like transport mechanism.
Alessandro Grillo +9 more
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Time-Domain Approximation by Iterative Methods [PDF]
, 1966 L. McBride +2 more
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Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery
Advanced Functional Materials, EarlyView.This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer +10 more
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