Zobrazeno 1 - 10
of 477
pro vyhledávání: '"Hagan, Michael P"'
Autor:
Tyukodi, Botond, Hayakawa, Daichi, Hall, Douglas M., Rogers, W. Benjamin, Grason, Gregory M., Hagan, Michael F.
Recent advances in synthetic methods enable designing subunits that self-assemble into structures with well-defined sizes and architectures, but yields are frequently suppressed by the formation of off-target metastable structures. Increasing the com
Externí odkaz:
http://arxiv.org/abs/2411.03720
Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive embedded soft materials into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active ma
Externí odkaz:
http://arxiv.org/abs/2410.05555
Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states,
Externí odkaz:
http://arxiv.org/abs/2408.14596
Autor:
Nishiyama, Katsu, Berezney, John, Norton, Michael M., Aggarwal, Akshit, Ghosh, Saptorshi, Hagan, Michael F., Dogic, Zvonimir, Fraden, Seth
Living things enact control of non-equilibrium, dynamical structures through complex biochemical networks, accomplishing spatiotemporally-orchestrated physiological tasks such as cell division, motility, and embryogenesis. While the exact minimal mec
Externí odkaz:
http://arxiv.org/abs/2408.14414
We apply optimal control theory to a model of a polar active fluid (the Toner-Tu model), with the objective of driving the system into particular emergent dynamical behaviors or programming switching between states on demand. We use the effective sel
Externí odkaz:
http://arxiv.org/abs/2405.07942
Autor:
Trubiano, Anthony, Hagan, Michael F.
Computational modeling of assembly is challenging for many systems because their timescales vastly exceed those accessible to simulations. This article describes the MultiMSM, which is a general framework that uses Markov state models (MSMs) to enabl
Externí odkaz:
http://arxiv.org/abs/2405.02467
Autor:
Tran, Phu N., Ray, Sattvic, Lemma, Linnea, Li, Yunrui, Sweeney, Reef, Baskaran, Aparna, Dogic, Zvonimir, Hong, Pengyu, Hagan, Michael F.
Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks. It uses those features to estimate the inter-frame motions of objects at the pixel level. In this article, we evaluate the abi
Externí odkaz:
http://arxiv.org/abs/2404.15497
Autor:
Videbæk, Thomas E., Hayakawa, Daichi, Grason, Gregory M., Hagan, Michael F., Fraden, Seth, Rogers, W. Benjamin
Self-assembly is one of the prevalent strategies used by living systems to fabricate ensembles of precision nanometer-scale structures and devices. The push for analogous approaches to create synthetic nanomaterials has led to the development of a la
Externí odkaz:
http://arxiv.org/abs/2311.01383
Autor:
Wei, Wei-Shao, Trubiano, Anthony, Sigl, Christian, Paquay, Stefan, Dietz, Hendrik, Hagan, Michael F., Fraden, Seth
Publikováno v:
Proceedings of the National Academy of Sciences, 121(7), e2312775121 (2024)
Self-assembly of complex and functional materials remains a grand challenge in soft material science. Efficient assembly depends on a delicate balance between thermodynamic and kinetic effects, requiring fine-tuning affinities and concentrations of s
Externí odkaz:
http://arxiv.org/abs/2310.18790
Autor:
Li, Yunrui, Zarei, Zahra, Tran, Phu N., Wang, Yifei, Baskaran, Aparna, Fraden, Seth, Hagan, Michael F., Hong, Pengyu
Active nematics are dense systems of rodlike particles that consume energy to drive motion at the level of the individual particles. They exist in natural systems like biological tissues and artificial materials such as suspensions of self-propelled
Externí odkaz:
http://arxiv.org/abs/2310.12449