Advancing material property prediction: using physics-informed machine learning models for viscosity.

In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based models is challenging. Data-driven machine learning (ML) also poses challenges in constructing ML models, especially in the material science domain where data is limited. To address this, we integrate physics-informed descriptors from molecular dynamics (MD) simulations to enhance the accuracy and interpretability of ML models.

Complex regional pain syndrome following vascular access creation for hemodialysis.

Pain and swelling of a limb following creation of arterio-venous fistula (AVF) are often attributable to vascular disorders like venous hypertension or limb ischaemia. Here we report the case of a 70-years old man who developed pain and swelling of upper limb distal to the AVF during second post-operative week due to a complex regional pain syndrome (CRPS). CRPS is characterized by pain that is disproportionate to the invoking injury, autonomic dysfunction, trophic changes and functional impairment of affected limb.

Active Learning Accelerates Design and Optimization of Hole-Transporting Materials for Organic Electronics.

Data-driven methods are receiving increasing attention to accelerate materials design and discovery for organic light-emitting diodes (OLEDs). Machine learning (ML) has enabled high-throughput screening of materials properties to suggest new candidates for organic electronics. However, building reliable predictive ML models requires creating and managing a high volume of data that adequately address the complexity of materials' chemical space.

Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers.

Solubility parameter models are widely used to select suitable solvents/nonsolvents for polymers in a variety of processing and engineering applications. In this study, we focus on two well-established models, namely, the Hildebrand and Hansen solubility parameter models. Both models are built on the basis of the notion of "like dissolves like" and identify a liquid as a good solvent for a polymer if the solubility parameters of the liquid and the polymer are close to each other.

Ferroelectricity, Antiferroelectricity, and Ultrathin 2D Electron/Hole Gas in Multifunctional Monolayer MXene.

The presence of ferroelectric polarization in 2D materials is extremely rare due to the effect of the surface depolarizing field. Here, we use first-principles calculations to show the largest out-of-plane polarization observed in a monolayer in functionalized MXenes (ScCO). The switching of polarization in this new class of ferroelectric materials occurs through a previously unknown intermediate antiferroelectric structure, thus establishing three states for applications in low-dimensional nonvolatile memory.

Consequences of axon guidance defects on the development of retinotopic receptive fields in the mouse colliculus.

Gradients of molecular factors pattern the developing retina and superior colliculus (SC) and guide retinal ganglion cell (RGC) axons to their appropriate central target perinatally. During and subsequent to this period, spontaneous waves of action potentials sweep across the retina, providing an instructive topographic signal based on the correlations of firing patterns of neighbouring RGCs. How these activity-independent and activity-dependent factors interact during retinotopic map formation remains unclear.

Developmental homeostasis of mouse retinocollicular synapses.

Spontaneous retinal waves during development are thought to provide an instructive signal for precise retinotopic mapping by correlating the activity of neighboring retinal ganglion cells. In mutant mice (beta2-/-) that lack correlated waves, retinocollicular map refinement is impaired. In vivo recordings reveal that neurons in the superior colliculus of beta2-/- mice have large receptive fields and low peak visual responses, resulting in a conservation of total integrated response.

Evidence for an instructive role of retinal activity in retinotopic map refinement in the superior colliculus of the mouse.

Although it is widely accepted that molecular mechanisms play an important role in the initial establishment of retinotopic maps, it has also long been argued that activity-dependent factors act in concert with molecular mechanisms to refine topographic maps. Evidence of a role for retinal activity in retinotopic map refinement in mammals is limited, and nothing is known about the effect of spontaneous retinal activity on the development of receptive fields in the superior colliculus. Using anatomical and physiological methods with two genetically manipulated mouse models and pharmacological interventions in wild-type mice, we show that spontaneous retinal waves instruct retinotopic map refinement in the superior colliculus of the mouse.