DOI,IST REx ID,Research Group,Title of publication
10.1063/5.0304731,21408,"CaGo,GradSch",Simultaneous optimization of assembly time and yield in programmable self-assembly
10.1063/5.0325170,21748,AnSa,Cracking donuts and sorting lipids: Geometry controls archaeal membrane stability and lipid organization
10.1063/5.0313352,21840,MiLe,"Electron–electrolyte coupling in AC transport through nanofluidic channels"
10.1063/5.0316886,21381,BiCh,Long-range electrostatics for machine learning interatomic potentials is easier than we thought
10.1063/5.0253451,19276,MiLe,Environment-limited transfer of angular momentum in Bose liquids
10.1063/5.0241949,19279,EdHa,Ionic association and Wien effect in 2D confined electrolytes
10.1063/5.0271155,19880,MiLe,Quantum transport in the presence of a chiral molecular potential
10.1063/5.0257558,19595,AlBr,"How local is “local”? Deep learning reveals locality of the induced magnetic field of polycyclic aromatic hydrocarbons"
10.1063/5.0217232,17278,"BiCh,GradSch",Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures
10.1063/5.0188215,15024,EdHa,Correlation-induced viscous dissipation in concentrated electrolytes
10.1063/5.0226954,18174,GradSch,"Fingerprints of ordered self-assembled structures in the liquid phase of a hard-core, square-shoulder system"
10.1063/5.0134271,12705,AnSa,"Structure and elasticity of model disordered, polydisperse, and defect-free polymer networks"
10.1063/5.0135893,12831,MiLe,Variational theory of angulons and their rotational spectroscopy
10.1063/5.0165806,14321,MiLe,Achiral dipoles on a ferromagnet can affect its magnetization direction
10.1063/5.0146711,12912,BiCh,Computing chemical potentials of adsorbed or confined fluids
10.1063/5.0173341,14603,BiCh,A streamlined molecular-dynamics workflow for computing solubilities of molecular and ionic crystals
10.1063/5.0087769,11400,AnSa,Controlling cluster size in 2D phase-separating binary mixtures with specific interactions
10.1063/5.0079844,10827,BiCh,"High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential"
10.1063/5.0107059,12249,BiCh,Computing chemical potentials of solutions from structure factors
10.1063/5.0005194,7956,MiLe,Shear-induced ordering in systems with competing interactions: A machine learning study