[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)]
No author records on this work.
Designing complex, dynamic yet multi-functional materials and devices is challenging because the design spaces for these materials have numerous interdependent and often conflicting constraints. Taking inspiration from advances in artificial intelligence and their applications in material discovery, we propose a computational method for designing metamorphic DNA-co-polymerized hydrogel structures. The method consists of a coarse-grained simulation and a deep learning-guided optimization system for exploring the immense design space of these structures. Here, we develop a simple numeric simulation of DNA-co-polymerized hydrogel shape change and seek to find designs for structured hydrogels that can fold into the shapes of different Arabic numerals in different actuation states. We train a convolutional neural network to classify and score the geometric outputs of the coarse-grained simulation to provide autonomous feedback for design optimization. We then construct a genetic algorithm that generates and selects large batches of material designs that compete with one another to evolve and converge on optimal objective-matching designs. We show that we are able to explore the large design space and learn important parameters and traits. We identify vital relationships between the material scale size and the range of shape change that can be achieved by individual domains and we elucidate trade-offs between different design parameters. Finally, we discover material designs capable of transforming into multiple different digits in different actuation states.
Citation edge evidence
- HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Semi-Supervised Classification with Graph Convolutional Networks→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Attention Is All You Need→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Adversarial Discriminative Domain Adaptation→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- [No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- An overview of gradient descent optimization algorithms→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- mixup: Beyond Empirical Risk Minimization→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Neural Architectures for Named Entity Recognition→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Mode…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochast…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Gaussian Error Linear Units (GELUs)→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- SciBERT: A Pretrained Language Model for Scientific Text→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Affordance-Compiled Intelligence: Observable-Only Cognitive Impedance Matching for No-Met…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- An Introduction to Deep Learning for the Physical Layer→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Heterogeneous Graph Attention Network→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Domain randomization for transferring deep neural networks from simulation to the real wo…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- LoRA Fine-Tuning of a 3B Code LLM for Algorithmic Efficiency→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- In-Kernel Aggregation and Broadcast Acceleration for Distributed Communication→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Optimization as a Model for Few-Shot Learning→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Addressing Function Approximation Error in Actor-Critic Methods→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- LXMERT: Learning Cross-Modality Encoder Representations from Transformers→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Automatic differentiation in machine learning: a survey→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Supervised Learning of Universal Sentence Representations from Natural\n Language Inferen…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep…→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Soft Actor-Critic Algorithms and Applications→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Federated Learning with Non-IID Data→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Deep Contextualized Word Representations→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks→Optimization as a Model for Few-Shot LearningLegacy edge — source detail unavailable
- Attention Is All You Need→Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…Legacy edge — source detail unavailable
- Optimization as a Model for Few-Shot Learning→Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…Legacy edge — source detail unavailable
- Deep Contextualized Word Representations→Neural Architectures for Named Entity RecognitionLegacy edge — source detail unavailable
- Addressing Function Approximation Error in Actor-Critic Methods→Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochast…Legacy edge — source detail unavailable
- Soft Actor-Critic Algorithms and Applications→Addressing Function Approximation Error in Actor-Critic MethodsLegacy edge — source detail unavailable
- Heterogeneous Graph Attention Network→Semi-Supervised Classification with Graph Convolutional NetworksLegacy edge — source detail unavailable
- Maximum Classifier Discrepancy for Unsupervised Domain Adaptation→Adversarial Discriminative Domain AdaptationLegacy edge — source detail unavailable
- End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF→Neural Architectures for Named Entity RecognitionLegacy edge — source detail unavailable
- [No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]→Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksLegacy edge — source detail unavailable
- [No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]→Optimization as a Model for Few-Shot LearningLegacy edge — source detail unavailable
- Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …→Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep LearningLegacy edge — source detail unavailable
- HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…→Gaussian Error Linear Units (GELUs)Legacy edge — source detail unavailable
- LXMERT: Learning Cross-Modality Encoder Representations from Transformers→Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…Legacy edge — source detail unavailable
- SciBERT: A Pretrained Language Model for Scientific Text→Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…Legacy edge — source detail unavailable
- FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→mixup: Beyond Empirical Risk MinimizationLegacy edge — source detail unavailable
- FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …Legacy edge — source detail unavailable
- In-Kernel Aggregation and Broadcast Acceleration for Distributed Communication→Gaussian Error Linear Units (GELUs)Legacy edge — source detail unavailable
- In-Kernel Aggregation and Broadcast Acceleration for Distributed Communication→HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…Legacy edge — source detail unavailable
- Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing→HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…Legacy edge — source detail unavailable
- Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing→SciBERT: A Pretrained Language Model for Scientific TextLegacy edge — source detail unavailable
- LoRA Fine-Tuning of a 3B Code LLM for Algorithmic Efficiency→HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…Legacy edge — source detail unavailable
What cites it, inside the corpus
Links
Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record
Topics
| Stochastic Gradient Optimization Techniques | Computer Science |
| Advanced Optimization Algorithms Research | Mathematics |
| Machine Learning and ELM | Computer Science |
Is this record sound?
suspect
Several fields of this record are missing or contradict each other. Treat its figures with suspicion — it is shown unaltered because correcting a source's record silently is worse than showing you the problem.
- weakensThe source lists no authors for this work at all, so there is nobody to attribute it to and it appears on no author page.
- weakensNo references are recorded despite 50,396 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
- weakensThe DOI names 2021 but the record dates this to 2,015. One of the two is about a different paper.
- weakensThe source record carries no title.
Provenance
sha256 7e3d99a592f7f61f…