ArticleMatter2025
Autonomous Discovery of Functional Random Heteropolymer Blends through Evolutionary Formulation Optimization.
Article in Matter, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Self-driving lab for the data-driven design of single-chain polymer nanoparticles.Cell press blue · 2026Article
- Tuning Polyacrylate Composition to Recognize and Modulate Fluorescent Proteins.Angewandte Chemie (International ed. in English) · 2026Article
- Computational design of functional random heteropolymers through atomistic simulations.PloS one · 2026Article
- Multimerization interactions between protein-inspired single-chain random heteropolymers.PloS one · 2026Article
- Seeking Precise Protein-like Functions from Random Heteropolymer Ensemble and through Dimensionality Reduction.ACS central science · 2025Review
- Optimization of robotic liquid handling as a capacitated vehicle routing problem.Digital discovery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
While developing new polymers typically requires years of investigation, blending existing polymers offers a cost-effective strategy to create new materials. However, developing functional polymer blends is often a slow and challenging process due to their vast design space, the non-additive nature of polymer properties, and limited fundamental understanding to guide the optimization. Here, we report an autonomous platform that addresses these challenges by integrating high-throughput blending, real-time data acquisition, and an evolutionary algorithm for composition optimization. This approach enables rapid exploration of complex combinatorial blending spaces of random heteropolymers (RHPs). With enzyme thermal stability as a model objective, this system discovered random heteropolymer blends (RHPBs) that outperform all constituents. Retrospective analysis reveals segment-level interactions correlated with the performance. This work highlights the opportunity for materials discovery within the RHP and RHPB space and the immense potential of leveraging autonomous discovery platforms to accelerate the discovery of polymers with emergent properties.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.