@article{KrishnadasCharronFournier2025, author = {Krishnadas, Anirudh and Charron, Nicolas and Fournier, Rene}, title = {Melting Transitions in Small Aluminum Clusters Simulated with Energies Approaching DFT Accuracy.}, journal = {ACS Publications- Journal of Chemical Theory and Computation}, year = {2025}, abstract = {We describe a computational framework for modelling melting-like transitions in atomic clusters that combines first-principles energy calculations, global optimization, and machine-learned interatomic potentials. A diverse set of configurations is generated by global optimization, and energies are calculated by Density Functional Theory. The energies are fitted to an accuracy of 10 meV/atom or better with an Allegro E(3)-equivariant neural network potential. The model allows efficient parallel tempering Monte Carlo simulations with near DFT-level accuracy. This methodology was validated by simulating Na_20 and comparing it to earlier experimental and computational results. We used it to study melting-like transitions in Al_n+ clusters (n=9 to 16), and Al_n and Al_n^- (n=12, 13,14). The simulated heat capacity of these clusters, in particular Al_16+, are in qualitative agreement with experiments. The melting point of Al_n+ clusters with n=11-16 are well above the bulk melting point (934 K). The closed-shell Al_13- species has an exceptionally high melting point, close to 2100 K.}, language = {en} } @article{KrishnadasMoshiQuintanaetal.2025, author = {Krishnadas, Anirudh and Moshi, Maryam and Quintana, Ramon Alain Miranda and Fournier, Rene}, title = {Geometric Features and a Neural Network Classifier for Detecting Melting-Like Transitions in Clusters.}, journal = {AIP Publications - The Journal of Chemical Physics}, year = {2025}, abstract = {Melting-like transitions in clusters are normally identified by a peak in the heat capacity curve C(T ) at T = Tc. Computing C(T ) requires costly simulations with millions of steps. We discuss four easily calculated functions of temperature that help detect and characterize melting-like transitions. The first, f1 (or WU ), is the width of the potential energy distribution which shows an abrupt increase near Tc. The other three are statistics of the ordered set of N(N - 1)/2 interatomic distances rij: (i) f2 is a measure of dissimilarity to the lowest energy configuration, or global minimum; (ii) f3 is the effective number of rij's found in a small interval centered around (r1 + r2)/2 where r1, r2 are the positions of the first two peaks in the pair distribution function; and (iii) f4 is a measure of non-uniformity in the distribution of the ri j's. Numerical tests with empirical potentials that model three types of bonding (van der Waals, covalent, and metallic) show that f1, f2, f3, and f4 produce estimates for the middle of the melting region in general agreement with Tc. An Artificial Neural Network (ANN) classifier that takes, as inputs, f2, f3, and many variants of f4, is used to calculate the solid fraction FS(T) and find the solid-liquid coexistence region between freezing and melting temperatures, [Tf , Tm]. Inflection points in f3(T ) and FS(T ) are very sensitive indicators of phase transitions. Estimates of Tc obtained from them converge one to three orders of magnitude faster, in simulation time, than those obtained with C(T ).}, language = {en} } @article{HoelterLemkeWeinzierletal.2025, author = {H{\"o}lter, Arne and Lemke, Mathias and Weinzierl, Stefan and Stein, Lewin}, title = {Non-Reflecting Characteristic Boundary Conditions for Adjoint Time-Domain Acoustic Simulations}, journal = {Journal of Theoretical and Computational Acoustics}, year = {2025}, abstract = {Accurate acoustic simulations in the free field require non-reflective boundary conditions to suppress spurious reflections at the computational domain boundaries. Although several characteristic-based formulations for direct (forward) simulations have been proposed in recent decades, the adjoint formulations of such characteristic-based boundary conditions (CBCs) have received limited atten- tion in the literature and lack a comprehensive analysis. This paper presents the derivation and evaluation of adjoint CBCs complementing the existing direct CBCs. Both the forward and adjoint CBCs are applied to the (nonlinear) Euler equations and linear acoustic equations in time-domain simulations. In this manner, the CBCs are investigated and subsequently compared to assess their respective accuracy and consistency. The CBCs were implemented using both a single-point and a zonal approach, with the former optionally combined with a sponge layer. Both approaches yielded comparable results in direct and adjoint simulations, while the zonal CBC exhibited improved ac- curacy at lower frequencies. Across the evaluated frequency range of approximately 350 - 5600 Hz, spurious reflections were attenuated by up to -70dB in both forward and adjoint cases, demon- strating the effectiveness and consistency of the proposed boundary treatment.}, language = {en} } @article{LaeuterKramer2025, author = {L{\"a}uter, Matthias and Kramer, Tobias}, title = {Rotation dynamics and torque efficiency of cometary nuclei}, volume = {699}, journal = {Astronomy \& Astrophysics}, arxiv = {http://arxiv.org/abs/2507.06036}, doi = {10.1051/0004-6361/202553845}, pages = {A75}, year = {2025}, abstract = {The dynamics of a rigid cometary nucleus is described by the evolutions of its center-of-mass and of its rotation state. Solar irradiation that reaches the surface of a cometary nucleus causes the sublimation of volatiles that form the coma around the nucleus. The sublimation process transfers linear momentum and rotational angular momentum from the nucleus to the surrounding space, and thus affects the dynamics via nongravitational forces and nongravitational torques. With the exception of close approaches to planets, these torques exert the dominant influence on the rotation states of cometary nuclei. The Rosetta mission 2014-2016 accompanying comet 67P/Churyumov-Gerasimenko provides the longest continuous observational data to track its rotation state. In particular, the data set encompasses the direction of the angular velocity, denoted by ω, and the angular frequency |ω|over a time period of approximately 700 days. The observed change of the rotation state is not explained by a low heat conductivity thermophysical model in combination with a homogeneous surface ice coverage of comet 67P. Spatially and/or temporally varying weights for effective active fraction with respect to a prescribed set of surface regions provide a potential solution to this problem. Here, we present a methodology for classifying the surface based on vectorial efficiency of the torque. On any cometary surface without geometric symmetry, the methodology highlights the decomposition into eight characteristic regions that encode the signs of torque efficiency with respect to all vector components. This decomposition is divided into two subsets of four regions each of which is located in one of both hemispheric regions. We analyze in detail rotation states close to lowest energy and different thermophysical models, and we discuss how the uncertainties of observations affect the model parameters. We study the occurrence of these regions for an oblate ellipsoid, a nearprolate ellipsoid, a bilobed shape, and a shape model analogous to that of comet 67P. The sensitivity analysis for comet 67P indicates that the observations constrain only one of the eight weights uniquely. The other directions are poorly constrained and show the limitation of the rotational data to determine the regional activity on comet 67P.}, language = {en} } @article{RossiQiaoDykstraetal.2025, author = {Rossi, Thomas and Qiao, Lu and Dykstra, Conner P. and Rodrigues Pel{\´a}, Ronaldo and Gnewkow, Richard and Wallick, Rachel F. and Burke, John H. and Nicholas, Erin and March, Anne-Marie and Doumy, Gilles and Buchholz, D. Bruce and Deparis, Christiane and Zu{\~n}iga-P{\´e}rez, Jesus and Weise, Michael and Ellmer, Klaus and Fondell, Mattis and Draxl, Claudia and van der Veen, Renske}, title = {Dynamic control of X-ray core-exciton resonances by Coulomb screening in photoexcited semiconductors}, volume = {6}, journal = {Communications Materials}, arxiv = {http://arxiv.org/abs/2412.01945}, doi = {10.1038/s43246-025-00909-w}, pages = {191}, year = {2025}, language = {en} } @article{HawthorneRaulinoRodriguesPelaetal.2025, author = {Hawthorne, Felipe and Raulino, Paulo R. E. and Rodrigues Pel{\´a}, Ronaldo and Woellner, Cristiano F.}, title = {Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress-Strain and Vibrational Properties}, volume = {129}, journal = {The Journal of Physical Chemistry C}, arxiv = {http://arxiv.org/abs/2505.12140}, doi = {10.1021/acs.jpcc.5c03470}, pages = {16319 -- 16326}, year = {2025}, language = {en} } @article{GroussinJordaAttreeetal.2025, author = {Groussin, Olivier and Jorda, L. and Attree, N. and Birch, S.P.D. and B{\"u}rger, Johanna and Guti{\´e}rrez, Pedro and Jindal, Abhinav S. and Keller, H.U. and Kramer, Tobias and Lasagni Manghi, Riccardo and L{\"a}uter, Matthias and Markkanen, J. and Marschall, R. and Schuckart, C.}, title = {Thermal environment and erosion of comet 67P/Churyumov-Gerasimenko}, volume = {694}, journal = {Astronomy and Astrophysics}, doi = {10.1051/0004-6361/202452260}, pages = {A21}, year = {2025}, abstract = {Aims. This paper focuses on how insolation affects the nucleus of comet 67P/Churyumov-Gerasimenko over its current orbit. We aim to better understand the thermal environment of the nucleus, in particular its surface temperature variations, erosion, relationship with topography, and how insolation affects the interior temperature for the location of volatile species (H2O and CO2). Methods. We have developed two thermal models to calculate the surface and subsurface temperatures of 67P over its 6.45-year orbit. The first model, with high resolution (300 000 facets), calculates surface temperatures, taking shadows and self-heating into account but ignoring thermal conductivity. The second model, with lower resolution (10 000 facets), includes thermal conductivity to estimate temperatures down to ∼3 m below the surface. Results. The thermal environment of 67P is strongly influenced by its large obliquity (52◦), which causes significant seasonal effects and polar nights. The northern hemisphere is the coldest region, with temperatures of 210-300 K. H2O is found in the first few centimetres, while CO2 is found deeper (∼2 m) except during polar night around perihelion, when CO2 accumulates near the surface. Cliffs erode 3-5 times faster than plains, forming terraces. The equatorial region receives maximum solar energy (8.5×109 J m-2 per orbit), with maximum surface temperatures of 300-350 K. On the plains, H2O is found in the first few centimetres, while CO2 is found deeper (∼2 m) and never accumulates near the surface. In the southern hemisphere, a brief intense perihelion heating raises temperatures to 350-400 K, which is followed by a 5-year polar night when surface temperatures drop to 55 K. Here H2O remains in the first few centimetres, while CO2 accumulates shallowly during polar night, enriching the region. Erosion is maximal in the southern hemisphere and concentrated on the plains, which explains the observed overall flatness of this hemisphere compared to the northern one. Over one orbit, the total energy from self-heating is 17\% of the total energy budget, and 34\% for thermal conduction. Our study contributes to a better understanding of the surface changes observed on 67P.}, language = {en} } @article{CoomberChewleSeckeretal.2025, author = {Coomber, Celvic and Chewle, Surahit and Secker, Christopher and Fackeldey, Konstantin and Weber, Marcus and Winkelmann, Stefanie and Sch{\"u}tte, Christof and Sunkara, Vikram}, title = {Investigating Endogenous Opioids Unravels the Mechanisms Behind Opioid-Induced Constipation, a Mathematical Modeling Approach}, volume = {26}, journal = {International Journal of Molecular Sciences}, number = {13}, doi = {10.3390/ijms26136207}, year = {2025}, abstract = {Endogenous opioids, such as Endomorphin-2, are not typically associated with severe constipation, unlike pharmaceutical opioids, which induce opioid-induced constipation (OIC) by activating μ-opioid receptors in the gastrointestinal tract. In this study, we present a mathematical model, which integrates the serotonergic and opioid pathways, simulating the interaction between serotonin and opioid signaling within the enteric nervous system (ENS). The model explores the mechanisms underlying OIC, with a focus on the change in adenylyl cyclase (AC) activity, cAMP accumulation, and the distinct functionalities of Endomorphin-2 compared to commonly used pharmaceutical opioids. We study the effects of Morphine, Fentanyl, and Methadone and contrast them with Endomorphin-2. Our findings reveal that opioids do not perturb the signaling of serotonin, but only the activity of AC, suggesting that serotonin levels have no influence on improving opioid-induced constipation. Furthermore, this study reveals that the primary difference between endogenous and pharmaceutical opioids is their degradation rates. This finding shows that modulating opioid degradation rates significantly improves cAMP recovery. In conclusion, our insights steer towards exploring opioid degrading enzymes, localized to the gut, as a strategy for mitigating OIC.}, language = {en} } @article{GonnermannMuellerHaaseFackeldeyetal.2025, author = {Gonnermann-M{\"u}ller, Jana and Haase, Jennifer and Fackeldey, Konstantin and Pokutta, Sebastian}, title = {FACET: Teacher-Centred LLM-Based Multi-Agent Systems-Towards Personalized Educational WorksheetsHier den Haupttitel eintragen}, arxiv = {http://arxiv.org/abs/2508.11401}, year = {2025}, abstract = {The increasing heterogeneity of student populations poses significant challenges for teachers, particularly in mathematics education, where cognitive, motivational, and emotional differences strongly influence learning outcomes. While AI-driven personalization tools have emerged, most remain performance-focused, offering limited support for teachers and neglecting broader pedagogical needs. This paper presents the FACET framework, a teacher-facing, large language model (LLM)-based multi-agent system designed to generate individualized classroom materials that integrate both cognitive and motivational dimensions of learner profiles. The framework comprises three specialized agents: (1) learner agents that simulate diverse profiles incorporating topic proficiency and intrinsic motivation, (2) a teacher agent that adapts instructional content according to didactical principles, and (3) an evaluator agent that provides automated quality assurance. We tested the system using authentic grade 8 mathematics curriculum content and evaluated its feasibility through a) automated agent-based assessment of output quality and b) exploratory feedback from K-12 in-service teachers. Results from ten internal evaluations highlighted high stability and alignment between generated materials and learner profiles, and teacher feedback particularly highlighted structure and suitability of tasks. The findings demonstrate the potential of multi-agent LLM architectures to provide scalable, context-aware personalization in heterogeneous classroom settings, and outline directions for extending the framework to richer learner profiles and real-world classroom trials.}, language = {en} } @misc{OPUS4-10176, title = {Mathematical Optimization for Machine Learning}, editor = {Fackeldey, Konstantin and Kannan, Aswin and Pokutta, Sebastian and Sharma, Kartikey and Walter, Daniel and Walter, Andrea and Weiser, Martin}, publisher = {De Gruyter}, isbn = {9783111376776}, doi = {10.1515/9783111376776}, year = {2025}, abstract = {Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete optimization, nonlinear programming, optimal control, first-order methods, multilevel optimization, machine learning in optimization, physics-informed learning, and fairness in machine learning.}, language = {en} } @article{GorgullaGarzaKapiletal.2025, author = {Gorgulla, Christoph and Garza, Alejandro J. and Kapil, Venkat and Fackeldey, Konstantin}, title = {QUASAR: A Flexible QM-MM Method for Biomolecular Systems based on Restraining Spheres}, volume = {320}, journal = {Computer Physics Communications}, issn = {0010-4655}, doi = {10.1016/j.cpc.2025.109949}, year = {2025}, abstract = {Quantum mechanical models of molecules theoretically offer unprecedented accuracy in predicting values associated with these systems, including the free energy of interaction between two molecules. However, high-accuracy quantum mechanical methods are computationally too expensive to be applied to larger systems, including most biomolecular systems such as proteins. To circumvent this challenge, the hybrid quantum mechanics/molecular mechanics (QM/MM) method was developed, allowing one to treat only the most important part of the system on the quantum mechanical level and the remaining part on the classical level. To date, QM/MM simulations for biomolecular systems have been carried out almost exclusively on the electronic structure level, neglecting nuclear quantum effects (NQEs). Yet NQEs can play a major role in biomolecular systems [1]. Here, we present i-QI, a QM/MM client for the path integral molecular dynamics (PIMD) software i-PI [2, 3, 4]. i-QI allows for carrying out QM/MM simulations simultaneously, allowing for the inclusion of electronic as well as nuclear quantum effects. i-QI implements a new QM/MM scheme based on constraining potentials called QUASAR, which allows handling diffusive systems, such as biomolecules solvated in water solvent. The QUASAR method is suitable in particular when the properties of interest are equilibrium properties, such as the free energy of binding. i-QI is freely available and open source, and we demonstrate it on a test system.}, language = {en} }