Tootfinder

ChemGen: Code Generation for Multispecies Chemical Kinetics in Computational Physics Simulations
Ryan F. Johnson, Eric J. Ching, Ethan S. Genter, Joshua E. Lipman, Andrew D. Kercher, Jay Arcities, Hai Wang
https://arxiv.org/abs/2510.10005

ChemGen: Code Generation for Multispecies Chemical Kinetics in Computational Physics Simulations
This paper introduces ChemGen, a software package that uses code generation to integrate multispecies thermodynamics and chemical kinetics into C+-based computational physics codes. ChemGen aims to make chemical kinetics more accessible in existing simulation frameworks and help bridge the gap between combustion modeling and computational physics. The package employs the concept of decorators which enable flexible C++ code generation to target established software ecosystems. ChemGen generates …

Fluidity and morphological stability of an amorphous thin film with radiation-induced defect kinetics
Tyler P. Evans, Eden Heyen
https://arxiv.org/abs/2510.10745 https://…

Fluidity and morphological stability of an amorphous thin film with radiation-induced defect kinetics
It is common to model ion-irradiated amorphous thin films as if they were highly viscous fluids. In such models, one is frequently concerned with the ion-enhanced fluidity, a measure of the ability of the free interface to relax surface energy. Motivated by usual fluid dynamics problems, the ion-enhanced fluidity is near-universally treated as a constant throughout the amorphous layer. However, for an irradiated thin film, the fluidity is ultimately caused by radiation-induced defect kinetics w…

Global Signals of the First Molecules from the Dark Ages in the Presence of Primordial Magnetic Fields
Yurii Kulinich, Bohdan Novosyadlyj, Maksym Tsizh, Nazar Fortuna
https://arxiv.org/abs/2510.10212

Global Signals of the First Molecules from the Dark Ages in the Presence of Primordial Magnetic Fields
We investigate how primordial magnetic fields (PMFs) affect the formation kinetics of the first molecules, H$_2$, HD, and HeH$^+$, as well as the populations of rovibrational levels and the global signals in the rovibrational transitions of H$_2$ and HD. We show that PMFs can significantly speed up the formation and destruction of the first molecules, leading to an increase in the number density of H$_2$ and HD molecules and a decrease in the number density of HeH$^+$ ion-molecules compared to …

Convective flux analysis on the instability of one-dimensional detonation
Yunfeng Liu
https://arxiv.org/abs/2509.10169 https://arxiv.org/pdf/2509.10169

Convective flux analysis on the instability of one-dimensional detonation
One-dimensional numerical simulations using the Euler equations and irreversible one-step Arrhenius kinetics are conducted to study the instability mechanism of a one-dimensional gaseous detonation. By increasing the activation energy, this study identifies the characteristics of stable detonation, periodic detonation, pulsating detonation, and detonation quenching. The key difference between this study and previous research is that it is the first quantitative analysis of convective flux, kine…

zERExtractor:An Automated Platform for Enzyme-Catalyzed Reaction Data Extraction from Scientific Literature
Rui Zhou, Haohui Ma, Tianle Xin, Lixin Zou, Qiuyue Hu, Hongxi Cheng, Mingzhi Lin, Jingjing Guo, Sheng Wang, Guoqing Zhang, Yanjie Wei, Liangzhen Zheng
https://arxiv.org/abs/2508.09995

zERExtractor:An Automated Platform for Enzyme-Catalyzed Reaction Data Extraction from Scientific Literature
The rapid expansion of enzyme kinetics literature has outpaced the curation capabilities of major biochemical databases, creating a substantial barrier to AI-driven modeling and knowledge discovery. We present zERExtractor, an automated and extensible platform for comprehensive extraction of enzyme-catalyzed reaction and activity data from scientific literature. zERExtractor features a unified, modular architecture that supports plug-and-play integration of state-of-the-art models, including la…

Linking GFAP Levels to Speech Anomalies in Acute Brain Injury: A Simulation Based Study
Shamaley Aravinthan, Bin Hu
https://arxiv.org/abs/2508.10130 https://

Linking GFAP Levels to Speech Anomalies in Acute Brain Injury: A Simulation Based Study
Background: Glial fibrillary acidic protein (GFAP) is a biomarker for intracerebral hemorrhage and traumatic brain injury, but its link to acute speech disruption is untested. Speech anomalies often emerge early after injury, enabling rapid triage. Methods: We simulated a cohort of 200 virtual patients stratified by lesion location, onset time, and severity. GFAP kinetics followed published trajectories; speech anomalies were generated from lesion-specific neurophysiological mappings. Ensembl…

Monitoring of Fluid Transport in Low Temperature Water Electrolyzers and Fuel Cells: Emerging Technologies and Future Prospects
Zehua Dou, Laura Tropf, Tobias Lappan, Hannes Rox, Xuegeng Yang, Lars Buettner, David Weik, Harry Hoster, Kerstin Eckert, Juergen Czarske
https://arxiv.org/abs/2510.12542 …

Monitoring of Fluid Transport in Low Temperature Water Electrolyzers and Fuel Cells: Emerging Technologies and Future Prospects
Low temperature water electrolyzers (LTWEs) and low temperature hydrogen fuel cells (LTFCs) present a promising technological strategy for the productions and usages of green hydrogen energy towards a net-zero world. However, the interactions of gas/liquid (fluid) transport and the intrinsic reaction kinetics in LTWEs/LTFCs present one of the key hurdles hindering high production rate and high energy conversion efficiency. Addressing these limitations requires analytical tools that are capable …

An overview of PBPK and PopPK Models: Applications to Radiopharmaceutical Therapies for Analysis and Personalization
Deni Hardiansyah, Bisma Baron Patrianesha, Kuangyu Shi, Babak Saboury, Arman Rahmim, Gerhard Glatting
https://arxiv.org/abs/2509.09755

An overview of PBPK and PopPK Models: Applications to Radiopharmaceutical Therapies for Analysis and Personalization
This review discusses the current applications, advantages, and limitations of PBPK and PopPK models in radiopharmaceutical therapy (RPT). PBPK models simulate radiopharmaceutical kinetics by integrating prior physiological and drug parameter information, whereas PopPK models leverage population data to enhance individual dose estimation accuracy. Future directions include developing hybrid models, incorporating artificial intelligence, and establishing regulatory guidelines to promote their cl…

A Scalable AI Driven, IoT Integrated Cognitive Digital Twin for Multi-Modal Neuro-Oncological Prognostics and Tumor Kinetics Prediction using Enhanced Vision Transformer and XAI
Saptarshi Banerjee, Himadri Nath Saha, Utsho Banerjee, Rajarshi Karmakar, Jon Turdiev
https://arxiv.org/abs/2510.05123

A Scalable AI Driven, IoT Integrated Cognitive Digital Twin for Multi-Modal Neuro-Oncological Prognostics and Tumor Kinetics Prediction using Enhanced Vision Transformer and XAI
Neuro-oncological prognostics are now vital in modern clinical neuroscience because brain tumors pose significant challenges in detection and management. To tackle this issue, we propose a cognitive digital twin framework that combines real-time EEG signals from a wearable skullcap with structural MRI data for dynamic and personalized tumor monitoring. At the heart of this framework is an Enhanced Vision Transformer (ViT++) that includes innovative components like Patch-Level Attention Regulari…

Effect of crystallographic texture on dealloying kinetics and composition of nanoporous gold surface
Ezgi Hatipo\u{g}lu, Ayman A. El-Zoka, Yujun Zhao, Stanislav Mr\'az, Jochen M. Schneider, Baptiste Gault, Aparna Saksena
https://arxiv.org/abs/2510.05970

Effect of crystallographic texture on dealloying kinetics and composition of nanoporous gold surface
Nanoporous metals allow for tailoring composition and surface-to-volume ratio, both aspects critical for applications in catalysis. Here, Ag70Au30 (2 at. %) films with a face-centered cubic structure were deposited at 400°C, either {111}-textured or randomly oriented. Upon chemical dealloying, atom probe tomography of the nanoporous structure reveals that the textured film retains a up to 2.7 times higher Ag concentration within the ligaments compared to the randomly oriented film that exhibit…

Complex dynamics and pattern formation in a diffusive epidemic model with an infection-dependent recovery rate
Wael El Khateeb, Chanaka Kottegoda, Chunhua Shan
https://arxiv.org/abs/2509.09000

Complex dynamics and pattern formation in a diffusive epidemic model with an infection-dependent recovery rate
A diffusive epidemic model with an infection-dependent recovery rate is formulated in this paper. Multiple constant steady states and spatially homogeneous periodic solutions are first proven by bifur cation analysis of the reaction kinetics. It is shown that the model exhibits diffusion-driven instability, where the infected population acts as an activator and the susceptible population functions as an in hibitor. The faster movement of the susceptible class will induce the spatial and spa…

Kinetics of Barrier Crossing Events from Temperature Accelerated Sliced Sampling Simulations
Sameer Saurav, Debjit Das, Ramsha Javed, Nisanth N. Nair
https://arxiv.org/abs/2509.05068

Kinetics of Barrier Crossing Events from Temperature Accelerated Sliced Sampling Simulations
Temperature-accelerated sliced sampling (TASS) is a well-established enhanced sampling method that facilitates exhaustive exploration of high-dimensional collective variable (CV) space through directed sampling employing a combination of umbrella restraining biases, metadynamics biases, and temperature acceleration of CVs. In this work, we broaden the applicability of TASS by introducing a protocol for computing rate constants of barrier crossing events. The challenge addressed here is to recov…

Simulating dynamic bonding in soft materials
Tyla R. Holoman, B. P. Prajwal, Glen M. Hocky, Thomas M. Truskett
https://arxiv.org/abs/2510.08879 https://arx…

Simulating dynamic bonding in soft materials
Dynamic bonding is an essential feature of many soft materials. Molecular simulations have proven to be a powerful tool for modeling bonding kinetics and thermodynamics in these materials, providing insights into their properties that cannot be obtained by experiments alone. Here, we review recent advances in modeling dynamic bonding in soft matter via molecular dynamics, Monte Carlo, and hybrid simulation methods, highlighting outstanding challenges and future directions.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[7/13]:
- New Recipe for Semi-supervised Community Detection: Clique Annealing under Crystallization Kinetics
Ling Cheng, Jiashu Pu, Ruicheng Liang, Qian Shao, Hezhe Qiao, Feida Zhu

Design of DNA Strand Displacement Reactions
Kri\v{z}an Jurinovi\'c, Merry Mitra, Rakesh Mukherjee, Thomas E. Ouldridge
https://arxiv.org/abs/2510.09372 https://

Design of DNA Strand Displacement Reactions
DNA strand displacement (SD) reactions are central to the operation of many synthetic nucleic acid systems, including molecular circuits, sensors, and machines. Over the years, a broad set of design frameworks has emerged to accommodate various functional goals, initial configurations, and environmental conditions. Nevertheless, key challenges persist, particularly in reliably predicting reaction kinetics. This review examines recent approaches to SD reaction design, with emphasis on the proper…

Intermediate time scale in the first product formation time distribution of Michaelis-Menten kinetics with inhibitors
Arthur M. S. Carvalho, Gerson C. Duarte-Filho, Fernando A. N. Santos
https://arxiv.org/abs/2508.11645

Intermediate time scale in the first product formation time distribution of Michaelis-Menten kinetics with inhibitors
Michaelis-Menten kinetics is one of the most recognized models in enzyme kinetics, crucial for the understanding of biochemical reactions in several metabolic processes. In this study, we perform a stochastic analysis of the Michaelis-Menten kinetics with the introduction of inhibitory mechanisms, which significantly diversifies the study of the reaction. We apply the Fock space formalism to reformulate the master equation, transforming it into a Schrödinger-type equation. We investigate rever…

Capillary hysteresis induced by gap-resolved meniscus dynamics on Faraday instability in Hele-Shaw cells
Xingsheng Li, Jing Li, Xiaochen Li
https://arxiv.org/abs/2509.09475 http…

Capillary hysteresis induced by gap-resolved meniscus dynamics on Faraday instability in Hele-Shaw cells
Existing theoretical analyses on Faraday waves in Hele-Shaw cells typically adopt gap-averaged governing equations and rely on Hamraoui's model coming from molecular kinetics theory, thereby oversimplifying essential transverse information, such as contact line velocity and capillary hysteresis, and conflicting with the unsteady meniscus dynamics. In this paper, a gap-resolved approach is developed by directly modeling the transverse gap flow and the contact angle dynamics, which overcomes the …

Kinetics of the photochromic effect in oxygen-containing rare-earth hydrides
Dmitrii Moldarev, Tuan T. Tran, Max Wolff, Daniel Primetzhofer
https://arxiv.org/abs/2509.25887 http…

Kinetics of the photochromic effect in oxygen-containing rare-earth hydrides
The kinetics of the photochromic reaction of oxygen-containing rare-earth hydrides is commonly described by an exponential function assuming a single-step process. In this paper, we elaborate on the origin of the photochromic effect in oxygen-containing rare-earth metal hydrides, considering the kinetics of the reaction as a two-step process. We show that the fit to the experimental data is improved drastically when two processes that cause the photodarkening are assumed: a fast reaction rate-l…

Convex Pollution Control of Wastewater Treatment Systems
Joshua Taylor
https://arxiv.org/abs/2510.03918 https://arxiv.org/pdf/2510.03918

Convex Pollution Control of Wastewater Treatment Systems
We design a model-predictive controller for managing the actuators in sewer networks. It minimizes flooding and combined-sewer overflow during rain and pollution at other times. To make the problem tractable, we use a convex relaxation of the microbial growth kinetics and a physically motivated linearization of the mass flow bilinearities. With these approximations, the trajectory optimization in each control period is a second-order cone program. In simulation, the controller releases roughly …

A Full-Atmosphere Model of Jupiter
Anton\'in Kn\'i\v{z}ek, Paul B. Rimmer, Martin Ferus
https://arxiv.org/abs/2509.04034 https://arxiv.org/pdf/2509…

A Full-Atmosphere Model of Jupiter
This paper presents a combined 1D photochemical-thermochemical kinetics model of Jupiter's deeper atmosphere, troposphere and stratosphere. The model covers atmospheric pressure range from $1.1 \times 10^{3}$ bar to $7.4 \times 10^{-11}$ bar and is the first model that incorporates sulfur chemistry when spanning an atmospheric region of this extent. This model incorporates a new version of the STAND reaction network with updated NH4SH chemistry, and updated Antoine equation parameters for NH4SH…

Self-similar kinetics for gravitational Bose-Einstein condensation
A. S. Dmitriev, D. G. Levkov, A. G. Panin, I. I. Tkachev
https://arxiv.org/abs/2509.02694 https://

Self-similar kinetics for gravitational Bose-Einstein condensation
We study an overpopulated gas of gravitationally interacting bosons surrounding a droplet of Bose-Einstein condensate - Bose star. We argue that kinetic evolution of this gas approaches with time a self-similar attractor solution to the kinetic equation. If the scale symmetry of the equation is broken by external conditions, the attractor solution exists, remains approximately self-similar, but has slowly drifting scaling dimension. The latter new regime of adiabatic self-similarity can determi…

Disentangling the Effects of Simultaneous Environmental Variables on Perovskite Synthesis and Device Performance via Interpretable Machine Learning
Tianran Liu, Nicky Evans, Kangyu Ji, Ronaldo Lee, Aaron Zhu, Vinn Nguyen, James Serdy, Elizabeth Wall, Yongli Lu, Florian A. Formica, Moungi G. Bawendi, Quinn C. Burlingame, Yueh-Lin Loo, Vladimir Bulovic, Tonio Buonassisi

Disentangling the Effects of Simultaneous Environmental Variables on Perovskite Synthesis and Device Performance via Interpretable Machine Learning
Despite the rapid rise in perovskite solar cell efficiency, poor reproducibility remains a major barrier to commercialization. Film crystallization and device performance are highly sensitive to environmental factors during fabrication, yet their complex interactions are not well understood. In this work, we present a systematic framework to investigate the influence of both individual and coupled environmental variables on device efficiency and crystallization kinetics. We developed an integra…

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion
Mahmood Mousavi, Caleb Caldwell, Jacob Baltes, Muteb Aljasem, Bok Jik Lee
https://arxiv.org/abs/2509.08094

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion
Achieving clean combustion systems is crucial in terms of solving environmental impacts, decarbonization needs and sustainability matters. Traditional combustion modeling techniques via computational fluid dynamics with accurate chemical kinetics face obstacles in computational cost and accurate representation of turbulence-chemistry interactions. Physically Informed Neural Networks (PINNs) as a new framework, merges physical laws with data-driven learning and shows great potential as an altern…

Collision operator for electron runaway in cold weakly-ionized plasmas
Yeongsun Lee, Pavel Aleynikov, Peter de Vries, Jong-Kyu Park, Yong-Su Na
https://arxiv.org/abs/2509.03092 …

Collision operator for electron runaway in cold weakly-ionized plasmas
In cold weakly-ionized plasmas, Dreicer generation mechanism can be non-diffusive as demonstrated in [Y. Lee et. al. Phys. Rev. Lett. 133 17 175102 (2024)]. By expanding the previous letter, we present the detailed description of a proper collision operator to precisely account for the non-diffusive electron kinetics. The operator appropriately combines the Fokker-Planck operator and Boltzmann operator where free-bound collision cross sections are valid in low energy region. The proposed operat…

Particle-based simulation of non-elementary bimolecular kinetics
Taylor Kearney, Mark B. Flegg
https://arxiv.org/abs/2508.10909 https://arxiv.org/pdf/2508.…

Particle-based simulation of non-elementary bimolecular kinetics
Particle-based simulations are an essential tool for the study of biochemical systems for scales between molecular/Brownian dynamics and the reaction-diffusion master equation. These simulations utilise proximity-based reaction conditions and are typically limited to elementary (mass-action) kinetics. We present a novel framework for directly simulating non-elementary bimolecular kinetics in a particle-based framework. By mimicking the behaviour of a third implicit reactant, we adapt non-elemen…

Pulsed-laser induced gold microparticle fragmentation by thermal strain
Yogesh Pokhrel, Meike Tack, Sven Reichenberger, Matteo Levantino, Anton Plech
https://arxiv.org/abs/2510.02011

Pulsed-laser induced gold microparticle fragmentation by thermal strain
Laser fragmentation of suspended microparticles is an upcoming alternative to laser ablation in liquid (LAL) that allows to streamline the the delivery process and optimize the irradiation conditions for best efficiency. Yet, the structural basis of this process is not well understood to date. Herein we employed ultrafast x-ray scattering upon picosecond laser excitation of a gold microparticle suspension in order to understand the thermal kinetics as well as structure evolution after fragmenta…

Simultaneous optimization of assembly time and yield in programmable self-assembly
Maximilian C. H\"ubl, Carl P. Goodrich
https://arxiv.org/abs/2510.07876 https://

Simultaneous optimization of assembly time and yield in programmable self-assembly
Rational design strategies for self-assembly require a detailed understanding of both the equilibrium state and the assembly kinetics. While the former is starting to be well understood, the latter remains a major theoretical challenge, especially in programmable systems and the so-called semiaddressable regime, where binding is often nondeterministic and the formation of off-target structures negatively influences the assembly. Here, we show that it is possible to simultaneously sculpt the ass…

Electrode Potential Dependent Differential Capacitance in Electrocatalysis: a Novel, Ab Initio Computational Approach
M\'arton Guba, Tibor H\"oltzl
https://arxiv.org/abs/2509.02318

Electrode Potential Dependent Differential Capacitance in Electrocatalysis: a Novel, Ab Initio Computational Approach
As interest in nanomaterials grows, ab initio simulations play a crucial role in designing electrochemical catalysts. Electrochemical reactions depend on electrode potential, highlighting the importance of the grand canonical representation, especially when integrated with Density Functional Theory. The Grand Canonical Potential - Kinetics (GCP-K) method is a valuable approach for determining electrocatalytic reaction mechanisms and kinetics rooted in quantum mechanics, relying on assumptions o…

Learning Reaction-Diffusion Kinetics from Mechanical Information
Royal C. Ihuaenyi, Hongbo Zhao, Ruqing Fang, Ruobing Bai, Martin Z. Bazant, Juner Zhu
https://arxiv.org/abs/2508.17523

Learning Reaction-Diffusion Kinetics from Mechanical Information
A central challenge in materials science is characterizing chemical processes that are elusive to direct measurement, particularly in functional materials operating under realistic conditions. Here, we demonstrate that mechanical strain fields contain sufficient information to reconstruct hidden chemical kinetics in coupled chemomechanical systems. Our partial differential equation-constrained learning framework decodes concentration-dependent diffusion kinetics, thermodynamic driving forces, a…

Robustness of Solutions of the Quantum Kinetic Equations in the Presence of Matter Density Fluctuations
Shashank Shalgar, Mariam Gogilashvili
https://arxiv.org/abs/2508.15747 ht…

Robustness of Solutions of the Quantum Kinetic Equations in the Presence of Matter Density Fluctuations
We investigate the role of fluctuations in the matter density on neutrino flavor evolution by studying their effects on the collision terms in the spherically symmetric quantum kinetics equations (QKEs). We solve the QKEs with varying radial resolution ($r_{\mathrm{bins}} = 150 \, , 1500 \, , 15000$) to assess numerical convergence in angular distributions, number densities, and energy spectra for four neutrino flavors ($ν_e$, $\barν_e$, $ν_x$, $\barν_x$). Our results demonstrate that the s…

The role of the solid-melt interface in accelerating the self-catalyzed growth kinetics of III-V semiconductors
Zhucong Xi, Abby Liu, Xiaobo Chen, Meng Li, Dmitri N. Zakharov, Judith C. Yang, Rachel S. Goldman, Liang Qi
https://arxiv.org/abs/2509.24206

The role of the solid-melt interface in accelerating the self-catalyzed growth kinetics of III-V semiconductors
Solid-melt interfaces play a pivotal role in governing crystal growth and metal-mediated epitaxy of gallium nitride (GaN) and other semiconductor materials. Using atomistic simulations based on machine-learning interatomic potentials (MLIPs), we uncover that multiple layers of Ga atoms at the GaN-Ga melt interface form structurally ordered and electronically charged configurations that are critical for the growth kinetics of GaN. These ordered layers modulate the free energy landscape (FEL) for…

A General Molecular-Scale Dynamic Memristor Model Based on Non-equilibrium Charge Transport Kinetics and Its Information Processing Capability in Reservoir Computing
Yueqi Chen, Xuan Ji, Xi Yu
https://arxiv.org/abs/2508.18014

A General Molecular-Scale Dynamic Memristor Model Based on Non-equilibrium Charge Transport Kinetics and Its Information Processing Capability in Reservoir Computing
Non-equilibrium molecular-scale dynamics, where fast electron transport couples with slow chemical state evolution, underpins the complex behaviors of molecular memristors, yet a general model linking these dynamics to neuromorphic computing remains elusive. We introduce a dynamic memristor model that integrates Landauer and Marcus electron transport theories with the kinetics of slow processes, such as proton/ion migration or conformational changes. This framework reproduces experimental condu…

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Efficient Exploration of Chemical Kinetics
Rohit Goswami

Pairwise correlations of global times in one-dimensional Brownian motion under stochastic resetting
Yihao Wang, Hanshuang Chen
https://arxiv.org/abs/2508.11387 https://

Pairwise correlations of global times in one-dimensional Brownian motion under stochastic resetting
Brownian motion with stochastic resetting-a process combining standard diffusion with random returns to a fixed position-has emerged as a powerful framework with applications spanning statistical physics, chemical kinetics, biology, and finance. In this study, we investigate the mutual correlations among three global characteristic times for one-dimensional resetting Brownian motion $x(τ)$ over the interval $τ\in \left[ 0, t\right] $: the occupation time $t_o$ spent on the positive semi-axis,…

Log-Linear Reaction Quotient Dynamics
Steven Diamond
https://arxiv.org/abs/2508.18523 https://arxiv.org/pdf/2508.18523

Log-Linear Reaction Quotient Dynamics
Chemical reaction networks in living cells maintain precise control over thousands of metabolites despite operating far from equilibrium under constant perturbations. While mass action kinetics accurately describe the underlying dynamics, the resulting nonlinear differential equations are difficult to analyze and control, particularly for large networks. We propose a simplified model where reaction quotients (the ratios that measure how far reactions are from equilibrium) evolve exponentially t…

Multiscale Growth Kinetics of Model Biomolecular Condensates Under Passive and Active Conditions
Tamizhmalar Sundararajan, Matteo Boccalini, Rom\'eo Suss, Sandrine Mariot, Emerson R. Da Silva, Fernando C. Giacomelli, Austin Hubley, Theyencheri Narayanan, Alessandro Barducci, Guillaume Tresset
https://arxiv.org/abs/2508.16398

Multiscale Growth Kinetics of Model Biomolecular Condensates Under Passive and Active Conditions
Living cells exhibit a complex organization comprising numerous compartments, among which are RNA- and protein-rich membraneless, liquid-like organelles known as biomolecular condensates. Energy-consuming processes regulate their formation and dissolution, with (de-)phosphorylation by specific enzymes being among the most commonly involved reactions. By employing a model system consisting of a phosphorylatable peptide and homopolymeric RNA, we elucidate how enzymatic activity modulates the grow…

Phase Separation Kinetics in a Polar Active Field Model
Massimiliano Semeraro, Leticia F. Cugliandolo, Giuseppe Gonnella, Adriano Tiribocchi
https://arxiv.org/abs/2508.13888 htt…

Phase Separation Kinetics in a Polar Active Field Model
A milestone of phase separation kinetics is the emergence of universal power laws $\sim t^{1/z}$ governing the domain growth evolution. We investigate a phase-separating polar active model comprising a scalar density field with an advective coupling to a polarization field. Our analysis reveals a novel $\sim t^{0.6}$ regime, which agrees well with the accelerated growth recently observed in simulations of polar active particles. We provide analytical arguments to explain how advection facilitat…

Stoichiometric recipes for periodic oscillations in reaction networks
Alexander Blokhuis, Peter F. Stadler, Nicola Vassena
https://arxiv.org/abs/2508.15273 https://

Stoichiometric recipes for periodic oscillations in reaction networks
Oscillatory chemical reactions are functional components in a variety of biological contexts. In chemistry, the construction and identification of even rudimentary oscillators remain elusive and lack a general framework. Using parameter-rich kinetics - a methodology enabling the disentanglement of parametric dependencies from structural analysis - we investigate the stoichiometry of chemical oscillators. We introduce the concept of oscillatory cores - minimal subnetworks that guarantee the pote…

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Large Differences Between Stochastic and Deterministic Kinetics in a Simple Autocatalytic Reactio...
Tomasz Bednarek, Jakub J\k{e}drak

Applied causality to infer protein dynamics and kinetics
Akashnathan Aranganathan, Eric R. Beyerle
https://arxiv.org/abs/2508.12060 https://arxiv.org/pdf/2…

Applied causality to infer protein dynamics and kinetics
The use of generative machine learning models, trained on the experimentally resolved structures deposited in the protein data bank, is an attractive approach to sampling conformational ensembles of proteins. Unfortunately, since the machine-learned model utilized to generate these ensembles is not tied to an equation of motion, such as a molecular dynamics integrator or other causal generator of the dynamics, there is no timescale or causal information encoded in them. As such, with this work,…

Generative Consistency Models for Estimation of Kinetic Parametric Image Posteriors in Total-Body PET
Yun Zhao, Qinlin Gu, Georgios I. Angelis, Andrew J. Reader, Yanan Fan, Steven R. Meikle
https://arxiv.org/abs/2509.13614

Generative Consistency Models for Estimation of Kinetic Parametric Image Posteriors in Total-Body PET
Dynamic total body positron emission tomography (TB-PET) makes it feasible to measure the kinetics of all organs in the body simultaneously which may lead to important applications in multi-organ disease and systems physiology. Since whole-body kinetics are highly heterogeneous with variable signal-to-noise ratios, parametric images should ideally comprise not only point estimates but also measures of posterior statistical uncertainty. However, standard Bayesian techniques, such as Markov chain…

Resetting Induces Memory Loss in Non-Markovian Processes
Debasish Saha, Rati Sharma
https://arxiv.org/abs/2509.11608 https://arxiv.org/pdf/2509.11608

Resetting Induces Memory Loss in Non-Markovian Processes
Stochastic resetting is a powerful strategy known to accelerate the first-passage time statistics of stochastic processes. While its effects on Markovian systems are well understood, a general framework for non-Markovian dynamics is still lacking, mostly due to its mathematical complexity. Here, we present an analytical and numerical framework to study non-Markovian processes under resetting, focusing on the first-passage properties of escape kinetics from metastable states. We show that resett…

Replaced article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Thermodynamics, Dynamics, and Kinetics of Nanostructured Fluid-Solid Interfaces
Carlos E. Colosqui

Replaced article(s) found for physics.bio-ph. https://arxiv.org/list/physics.bio-ph/new
[1/1]:
- Stochastic Kinetics of mRNA Molecules in a General Transcription Model
Yuntao Lu, Yunxin Zhang

Replaced article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
- Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augment...
Ke Xiao, Yangchen Xu, Han Li, Zhi X. Chen

Robustness of classical nucleation theory to chemical heterogeneity of crystal nucleating substrates
Fernanda Sulantay Vargas, Sarwar Hussain, Amir Haji-Akbari
https://arxiv.org/abs/2510.01420

Robustness of classical nucleation theory to chemical heterogeneity of crystal nucleating substrates
Heterogeneous nucleation is a process wherein extrinsic impurities facilitate freezing by lowering nucleation barriers and constitutes the dominant mechanism for crystallization in most systems. Classical nucleation theory (\textsc{Cnt}) has been remarkably successful in predicting the kinetics of heterogeneous nucleation, even on chemically and topographically non-uniform surfaces, despite its reliance on several restrictive assumptions, such as the idealized spherical-cap geometry of the crys…

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Large Differences Between Stochastic and Deterministic Kinetics in a Simple Autocatalytic Reactio...
Tomasz Bednarek, Jakub J\k{e}drak

Verification, Validation, and Uncertainty Quantification (VVUQ) of PBPK Models for Theranostic Digital Twins: Towards Reliable Model-Informed Treatment Planning for Radiopharmaceutical Therapies
Nouran R. R. Zaid (Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA), Deni Hardiansyah (Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia), Tah…

Verification, Validation, and Uncertainty Quantification (VVUQ) of PBPK Models for Theranostic Digital Twins: Towards Reliable Model-Informed Treatment Planning for Radiopharmaceutical Therapies
Physiologically based pharmacokinetic (PBPK) models provide a mechanistic framework for simulating radiopharmaceutical kinetics and estimating patient-specific absorbed doses (ADs). PBPK models incorporate prior knowledge of patient physiology and drug-specific properties, which can enhance the models predictive performance. PBPK models can ultimately be used to predict treatment response and thereby enable theranostic digital twins (TDTs) for personalized treatment planning in radiopharmaceuti…

Crosslisted article(s) found for q-bio.BM. https://arxiv.org/list/q-bio.BM/new
[1/1]:
- Multiscale Growth Kinetics of Model Biomolecular Condensates Under Passive and Active Conditions
Sundararajan, Boccalini, Suss, Mariot, Da Silva, Giacomelli, Hubley, Narayanan, Barducci, Tresset
…

Viscous Growth Law in Bubble Coarsening: A Molecular Dynamics Perspective
Parameshwaran A, Bhaskar Sen Gupta
https://arxiv.org/abs/2509.21457 https://arxiv…

Viscous Growth Law in Bubble Coarsening: A Molecular Dynamics Perspective
We investigate the kinetics of bubble coarsening in a single component Lennard-Jones fluid using large-scale molecular dynamics simulations. A homogeneous high-temperature system is quenched below the critical temperature to induce the nucleation and growth of vapor bubbles within a dense liquid matrix. The structural evolution is characterized by two point correlation functions and the static structure factor, both of which exhibit dynamic scaling and sharp interfaces consistent with Porod law…

Lithiation Analysis of Metal Components for Li-Ion Battery using Ion Beams
Arturo Galindo, Neubi Xavier, Noelia Maldonado, Jes\'us D\'iaz-S\'anchez, Carmen Morant, Gast\'on Garc\'ia, Celia Polop, Qiong Cai, Enrique Vasco
https://arxiv.org/abs/2508.21017

Lithiation Analysis of Metal Components for Li-Ion Battery using Ion Beams
Metal components are extensively used as current collectors, anodes, and interlayers in lithium-ion batteries. Integrating these functions into one component enhances the cell energy density and simplifies its design. However, this multifunctional component must meet stringent requirements, including high and reversible Li storage capacity, rapid lithiation/delithiation kinetics, mechanical stability, and safety. Six single-atom metals (Mg, Zn, Al, Ag, Sn and Cu) are screened for lithiation beh…

Global properties of the energy landscape: a testing and training arena for machine learned potentials
Vlad C\u{a}rare, Fabian L. Thiemann, Joe Morrow, David J. Wales, Edward O. Pyzer-Knapp, Luke Dicks
https://arxiv.org/abs/2508.16425

Global properties of the energy landscape: a testing and training arena for machine learned potentials
Machine learning interatomic potentials (MLIPs) have achieved remarkable accuracy on standard benchmarks, yet their ability to reproduce molecular kinetics -- critical for reaction rate calculations -- remains largely unexplored. We introduce Landscape17, a dataset of complete kinetic transition networks (KTNs) for the molecules of the MD17 dataset, computed using hybrid-level density functional theory. Each KTN contains minima, transition states, and approximate steepest-descent paths, along w…

Quantum Molecular Dynamics Calculations on H H$_2$, H$_2$ H$_2$, H$_2$O/Cu(111), and Anthracene with Various Masses
Xingyu Zhang, Jinke Yu, Qingyong Meng
https://arxiv.org/abs/2509.17316

Quantum Molecular Dynamics Calculations on H + H$_2$, H$_2$ + H$_2$, H$_2$O/Cu(111), and Anthracene with Various Masses
In this work, a theoretical scheme on quantum molecular dynamics in curved Schwarzschild spacetime is developed. To this end, the gravitational field is introduced by revising the kinetics energy operator (KEO) rather than by adding Newtonian gravitational interaction in the potential energy surface (PES) due to the important role of the metric tensor in deriving the KEO. To test the present Schr{ö}dinger-type framework, spherically symmetric Schwarzschild spacetime is chosen to explore (1) th…

Ultrafast X-ray interaction with photovoltaic materials: Thermal and nonthermal responses
Aldo Art\'imez Pe\~na, Nikita Medvedev
https://arxiv.org/abs/2508.11549 https://

Ultrafast X-ray interaction with photovoltaic materials: Thermal and nonthermal responses
Cadmium telluride (CdTe), lead sulfide (PbS), and indium tin oxide (ITO) are important in various electronic technologies, for which laser irradiation is used to selectively modify and design their unique semiconductor properties. We employ the hybrid multiscale code XTANT-3 to simulate the kinetics of material response to ultrafast X-ray irradiation. The code accounts for nonequilibrium electronic and atomic dynamics, nonadiabatic coupling, nonthermal melting, and bond breaking due to electron…

Evolution of surfactant-free 'pristine' emulsions
Andrei Dukhin, Renliang Xu, Darrell Velegol
https://arxiv.org/abs/2509.13529 https://arxiv.org/pd…

Evolution of surfactant-free 'pristine' emulsions
The term pristine interface was introduced by Beattie and Djerdjev 20 years ago for emulsions that consist of only water and oil with no surfactant. They are different from Pickering emulsions, which are also surfactant-free but stabilized with colloidal particles. In contrast to previous studies, we monitor the kinetics of the initial stages of emulsion formation. We conducted such tests in an open setup when samples are open to air and CO2 content in the water varies, and in closed setup when…

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Large Differences Between Stochastic and Deterministic Kinetics in a Simple Autocatalytic Reactio...
Tomasz Bednarek, Jakub J\k{e}drak