Home ›
Entities
› academia
› Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals
Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals
Research article (Computer Methods in Applied Mechanics and Engineering, 2023) · cited 64× · AI/ML
Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals
Summary
Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals is a scholarly article[1].
Key Facts
Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals. Retrieved May 24, 2026, from https://4ort.xyz/entity/phase-field-deeponet-physics-informed-deep-operator-neural-network-for-fast-simulations-of-pattern-formation-governed-by
MLA“Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/phase-field-deeponet-physics-informed-deep-operator-neural-network-for-fast-simulations-of-pattern-formation-governed-by.
BibTeX@misc{4ortxyz_phase-field-deeponet-physics-informed-deep-operator-neural-network-for-fast-simulations-of-pattern-formation-governed-by_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals}}, year = {2026}, url = {https://4ort.xyz/entity/phase-field-deeponet-physics-informed-deep-operator-neural-network-for-fast-simulations-of-pattern-formation-governed-by}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Phase-Field DeepONet: Physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals — https://4ort.xyz/entity/phase-field-deeponet-physics-informed-deep-operator-neural-network-for-fast-simulations-of-pattern-formation-governed-by (retrieved 2026-05-24)
