Condensed Matter · Physics & Astronomy
Soft Condensed Matter
The newest papers in Soft Condensed Matter that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
26 papers, from 31 August 2026 to 5 November 2026: 25 arXiv preprints and 1 OpenAlex record.
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Newest papers
Hydrodynamic interaction in Lattice Fokker Planck for dilute polymer dynamics
We extend the BGK-type kinetic model for polymer dumbbells and its lattice Boltzmann implementation by incorporating hydrodynamic interaction (HI) effects to accurately recover the slow-variable…Discrete Backbone Elasticity and Curvature-Dependent Torsion Statistics in Proteins
Coarse-grained models of protein conformational dynamics use $\mathrm{C}_α$ geometry to describe the probabilities of regular helices, ordered turns and disordered conformations.Noise-resilient collective order through temporal memory in self-propelled particles
Temporal memory can stabilise collective motion by filtering noisy local observations, but persistent information can also impede adaptation when the collective state changes.Variational Functional Neural Networks (vfNN)
We present a variational functional neural network (vfNN) algorithm that optimizes physically motivated continuum functionals in integral form (e.g., Lagrangian, Hamiltonian, or free energy) to find…Beyond Synthesis Conditions: Linking In-situ Growth Dynamics to Carbon Nanotube Forest Properties through Multimodal Machine Learning
Machine learning for chemical vapor deposition (CVD) of carbon nanotubes (CNTs) has largely mapped static synthesis conditions to final properties, implicitly treating these conditions as a complete…Canonic hemoglobin-oxygen equilibrium: Reassessing the role of cooperativity
Hemoglobin-oxygen equilibrium is normally studied within the grand canonical ensemble, which assumes that each hemoglobin is immersed in a reservoir of unbound oxygen molecules of the plasma.A variational phase-field theory of cohesive fracture at finite deformation
This paper formulates a kinematically and variationally consistent phase-field theory for cohesive fracture at finite deformation.Distilling Large-Scale Machine Learning Interatomic Potentials to Predict Long-Timescale Electrolyte Transport Properties
Accurately predicting the transport properties of liquid electrolytes is critical for next-generation battery design and requires force fields that are both quantum-mechanically accurate and fast…Hidden Phase Transition in Single-Polymer Stretching under Elongational Flow
Using machine learning, we identify a second transition in polymer chain stretching driven by planar elongational flow, beyond the well-known coil-stretch transition.Multistable nematic liquid crystal pores as reconfigurable optical vortex metasurfaces
Nematic liquid crystals confined in cylindrical pores adopt multiple stable director topologies --- radial, escaped, and arches --- each imprinting a distinct optical signature on transmitted…Renormalization for Robust Memory without Synchronization
Local error correction can preserve classical information against noise, but protection under synchronized updates need not survive when sites evolve at independent random times.Dynamical coarse-graining of neural-network training
Dynamical coarse-graining of neural networks gives macroscopic observables and enables training to be predicted, and controlled in a state space far smaller than the parameter space.Ideal interaction dynamics of defects and background fields in condensed matter
While defect dynamics in condensed matter systems is widely studied and several methods are available to track the defect position over time, the formulation of dynamical models for the coupled…Supercoiling Drives DNA-Protein Co-Condensation
The co-condensation of DNA and proteins plays an important role in genome compaction, including heterochromatin formation and chromosome segregation.Dynamical Batching: How Class-Cycling Training Shapes the Internal Structure of Neural Networks
We investigate whether cyclically varying the class composition of training batches can modify both the performance and the internal organization of neural networks.Vision-Guided Closed-Loop Autonomous Navigation of Light-Driven Janus Microbots
Artificial microbots capable of precise and autonomous navigation could provide versatile platforms for microscale transport, manipulation, and task execution in complex environments.The typical red cell makes too little vacuole material for coalescence to build the large vacuoles of pocked cells
Red blood cells carrying intracellular vacuoles, called pocked cells, are a sensitive marker of splenic function: about 0.5% of cells in healthy people, 20 to 70% after splenectomy.Autonomous thermodynamic cycles via robotic mobility and sensing
Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work.A structure-preserving neural density functional for the ions of a polymer electrolyte
Predicting the structure and response of inhomogeneous polymer electrolytes requires a description of ion correlations that retains molecular-scale accuracy while remaining transferable across…An all-transistor physical-learning transformer can be trained to perform in-context learning
Most systems trained by equilibrium propagation or coupled learning are in the same class as multi-layer perceptrons: while they may be universal function approximators, they struggle to learn…