43 papers
Atmospheric clustering explores how tiny particles in the air group together to form clouds, fog, and even influence our weather patterns. This fascinating intersection of physics and meteorology reveals the invisible dance of molecules that shapes everything from a gentle breeze to a massive storm system. Understanding these microscopic interactions is key to predicting climate change and improving air quality forecasts for communities worldwide.
On Gist.Science, we track every new preprint published in the atmospheric clustering category on arXiv. Our team processes each submission to provide both a clear, plain-language explanation and a detailed technical summary, ensuring that complex research is accessible to students, policymakers, and curious minds alike.
Below are the latest papers in atmospheric clustering, updated daily directly from the source.
This study challenges the prevailing paradigm of urban new particle formation by demonstrating that emerging amines from carbon capture processes, particularly diethanolamine and piperazine, can dominate nucleation pathways over dimethylamine in polluted urban environments, necessitating a revision of current atmospheric models to account for their growing role in future air quality and climate scenarios.
This study benchmarks five machine-learned interatomic potentials (SchNet, FieldSchNet, SO3Net, PaiNN, and MACE) for predicting molecular infrared spectra, finding that while all models achieve high accuracy on training data, the equivariant architectures (SO3Net, PaiNN, and MACE) demonstrate superior generalization to unseen systems, with PaiNN offering the best balance of efficiency and accuracy and MACE providing the highest spectral accuracy.
This paper demonstrates that tunable universal -wave interactions and weakly bound tetratomic states can be achieved in dipolar fermionic spin mixtures without compromising microwave shielding, thereby enabling stable, strongly interacting quantum phases and facilitating evaporative cooling.
The paper introduces SCULPT, an interactive web-based machine learning platform that utilizes advanced techniques like UMAP and adaptive confidence scoring to analyze high-dimensional multi-particle coincidence data from COLTRIMS experiments, thereby enabling efficient discovery of rare events and correlations in atomic and molecular physics.
This study combines spectroscopy and diatomic-in-molecule simulations to reveal that cesium atoms in cryogenic argon matrices occupy multiple trapping sites with distinct symmetries, leading to complex fluorescence, large Stokes shifts, and significant host-guest lattice reorganization.
The paper proposes a novel method to detect asteroid-mass Primordial Black Hole dark matter by observing a unique "gravitational spectral radio forest"—a symmetric splitting of the hydrogen 2P3/2 state into a 2 GHz bandwidth caused by tidal spacetime curvature in H II regions.
This paper presents an improved analytical emission model based on a secondary-emission-surface approach that accurately predicts the angular intensity distribution and flux properties of primary effusive sources across the full range of molecular flow, from transparent to opaque regimes, to guide the design of efficient sources for atomic and molecular physics experiments.
This study investigates the photoelectron circular dichroism (PECD) of the chiral molecule HFC and its heavy open-shell europium complex, demonstrating that PECD remains a practical and sensitive technique for resolving structural details like keto-enol tautomerism in large, complex organometallic systems despite theoretical modeling challenges.
This experimental study demonstrates that locally applied electric fields within a tip-enhanced photoluminescence nanocavity enable active control over collective bright and dark excitonic states in polyradical aggregates, revealing proportional Stark shifts, emission sharpening, and divergent behaviors that offer a pathway for engineering nanoscale optoelectronic devices.
This paper reports an improved Diatomic-In-Molecules (DIM) calculation for excited argon clusters that incorporates previously ignored strongly avoided crossings between 3p4s and 3p4p states to better understand the localization of excitation and the effect of diabatisation on cluster isomers.