An official website of the United States government
Nearly thirty years after its inception, the field of DNA-programmed colloidal self-assembly has begun to realize its initial promise. In this review, we summarize recent developments in designing effective interactions and understanding the dynamic self-assembly pathways of DNA-coated nanoparticles and microparticles, as well as how these advances have propelled tremendous progress in crystal engineering. We also highlight exciting new directions showing that new classes of subunits combining nanoparticles with DNA origami can be used to engineer novel multicomponent assemblies, including structures with self-limiting, finite sizes. We conclude by providing an outlook on how recent theoretical advances focusing on the kinetics of self-assembly could usher in new materials-design opportunities, like the possibility of retrieving multiple distinct target structures from a single suspension or accessing new classes of materials that are stabilized by energy dissipation, mimicking self-assembly in living systems.
more »
« less
Finiteness for self-dual classes in integral variations of Hodge structure
We generalize the finiteness theorem for the locus of Hodge classes withfixed self-intersection number, due to Cattani, Deligne, and Kaplan, from Hodgeclasses to self-dual classes. The proof uses the definability of periodmappings in the o-minimal structure $$\mathbb{R}_{\mathrm{an},\exp}$$.
more »
« less
- Award ID(s):
- 2131688
- PAR ID:
- 10445646
- Date Published:
- Journal Name:
- Épijournal de Géométrie Algébrique
- Volume:
- Special volume in honour of...
- ISSN:
- 2491-6765
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Self‐folding broadly refers to the assembly of 3D structures by bending, curving, and folding without the need for manual or mechanized intervention. Self‐folding is scientifically interesting because self‐folded structures, from plant leaves to gut villi to cerebral gyri, abound in nature. From an engineering perspective, self‐folding of sub‐millimeter‐sized structures addresses major hurdles in nano‐ and micro‐manufacturing. This review focuses on self‐folding using surface tension or capillary forces derived from the minimization of liquid interfacial area. Due to favorable downscaling with length, at small scales capillary forces become extremely large relative to forces that scale with volume, such as gravity or inertia, and to forces that scale with area, such as elasticity. The major demonstrated classes of capillary force assisted self‐folding are discussed. These classes include the use of rigid or soft and micro‐ or nano‐patterned precursors that are assembled using a variety of liquids such as water, molten polymers, and liquid metals. The authors outline the underlying physics and highlight important design considerations that maximize rigidity, strength, and yield of the assembled structures. They also discuss applications of capillary self‐folding structures in engineering and medicine. Finally, the authors conclude by summarizing standing challenges and describing future trends.more » « less
-
null (Ed.)The Achievement Goal Framework describes students’ goal orientations as: task-based, focusing on the successful completion of the task; self-based, evaluating performance relative to one's own past performance; or other-based, evaluating performance relative to the performance of others. Goal orientations have been used to explain student success in a range of educational settings, but have not been used in post-secondary chemistry. This study describes the goal orientations of General Chemistry students and explores the relationship of goal orientations to success in the course. On average, students report higher task and self orientations than other orientation. Task orientation had a positive relationship with exam performance and self orientation had a negative relationship with exam performance. Clustering students showed that for the majority of students task and self orientations moved concurrently and students with low preference across the three orientations also performed lowest on exams. Finally, students in classes using Flipped-Peer Led Team Learning, a pedagogy designed to bring active learning to a large lecture class, showed higher task orientation than those in classes with lecture-based instruction.more » « less
-
Abstract Although research has touted the value of making in educational settings, scant work has been done in formal school contexts utilizing quantitative methods. This could be attributed to the various challenges in integrating making in school settings. To fill in the gap, this study presents an approach to integrate making into science classes at the 3rd to 5th grade levels in a U.S. public school for four consecutive years (2015–2019). We examined the effect of the program on students’ self-beliefs (self-efficacy, motivation, and self-concept) using a longitudinal quasi-experimental design. We also examined the effect of making on students’ knowledge and skills using state testing data. Results suggest that when averaged across post school year surveys, students in maker classes (vs. control) reported higher self-efficacy beliefs in science and making as well as more interests in STEM-related careers. Moreover, over two school years, we observed that students in the control group experienced declines on some of our variables while our maker students did not. Data thereby speaks to the potential value and promise of integrating making into formal school settings. Practical implications are discussed.more » « less
-
null (Ed.)Hierarchical multi-label text classification (HMTC) aims to tag each document with a set of classes from a class hierarchy. Most existing HMTC methods train classifiers using massive human-labeled documents, which are often too costly to obtain in real-world applications. In this paper, we explore to conduct HMTC based on only class surface names as supervision signals. We observe that to perform HMTC, human experts typically first pinpoint a few most essential classes for the document as its “core classes”, and then check core classes’ ancestor classes to ensure the coverage. To mimic human experts, we propose a novel HMTC framework, named TaxoClass. Specifically, TaxoClass (1) calculates document-class similarities using a textual entailment model, (2) identifies a document’s core classes and utilizes confident core classes to train a taxonomyenhanced classifier, and (3) generalizes the classifier via multi-label self-training. Our experiments on two challenging datasets show TaxoClass can achieve around 0.71 Example- F1 using only class names, outperforming the best previous method by 25%.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.46298/epiga.2023.specialvolumeinhonourofclairevoisin.9626
