From Anisotropic Molecules and Particles to Small-Scale Actuators and Robots: An Account of Polymerized Liquid Crystals
Bibliographic record
Abstract
Conspectus Untethered small-scale (milli-, micro-, and nano-) soft robots promise minimally invasive and targeted medical procedures in tiny, flooded, and confined environments like inside the human body. Despite such potentials, small-scale robots have not yet found their way to real-world applications. This can be mainly attributed to the fundamental and technical challenges in the fabrication, powering, navigation, imaging, and closed-loop control of robots at submillimiter scales. Pertinent to this Account, the selection of building block materials of small-scale robots also poses a challenge that is directly related to their fabrication and function. Early work in microrobotics focused on the mechanism of locomotion in fluids with low Reynolds number ( Re ≪ 1), which was mainly inspired by the motility of cells and microorganisms. Looking closely at the motile cells and microorganisms, one can find both order and anisotropy within their microstructure, driving out-of-equilibrium asymmetric deformations of their soft bodies and appendages like cilia and flagella, resulting in locomotion and function in environments with low Re number. Microroboticists aim to mimic microorganisms’ locomotion and function in developing mobile small-scale robots. It is known that soft, ordered, and anisotropic microstructures of microorganisms are examples of liquid crystalline systems. With this in mind, we believe that liquid crystals are underutilized in the design of small-scale robots, even though they have remarkable similarities to biological materials and constructs. In this Account, we have shed light on the role liquid crystals have played and can play in the design of small-scale robots. For this, we have first elaborated on the fundamentals of liquid crystals, which include a discussion of the various types of liquid crystals and their characteristics, their mesophase behavior, and their anisotropic properties. Then, we have discussed the applicability of anisotropic elastic networks of liquid crystals in the design of actuators which must satisfy all four programming pillars, including elasticity, alignment, responsiveness, and initial geometry. We have highlighted landmark reports where anisotropic elastic networks of liquid crystals, such as liquid crystal elastomers (LCEs), networks (LCNs), and hydrogels, are utilized as structural materials in the design of soft, small-scale actuators and robots. We point out the prevalence of the nematic phase and thermotropic liquid crystals utilized in these constructs over other mesophases and liquid crystal types as part of our discussion on the pros and cons of liquid crystals for microrobotics research. Finally, paths forward for the widespread applicability of liquid crystal microrobotics are envisaged. Specifically, the potential of soft robots constructed from elastic networks of chromonic and micellar lyotropic liquid crystals provides a substantial, yet daunting, opportunity for research. Furthermore, miniaturizing these constructs through innovative, combinatorial alignment–fabrication strategies on the microscale could realize liquid crystal soft robots suitable for biomedical applications, unlike those made from thermotropic liquid crystals. Additionally, programming alignment in alternative mesophases, such as smectic, may portray new research avenues in this emerging technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".