Materials Science · Cross-listed from cs.DL
APTLAS: An Indexed APT Literature Repository
Bavley Guerguis and Nabil Bassim
Atom probe
tomography (APT) literature is broad, rapidly growing, and dispersed across a wide range of journals, which can make it difficult to identify prior work on a given material system, instrument, or analytical approach. Conventional search engines (e.g., Google Scholar) excel at general
retrieval but do not preserve the domain-specific metadata that often determines the relevance of an APT publication (e.g., analysis mode,
laser wavelength, or instrument configuration). Herein, APTLAS is presented, which is an indexed repository of published APT literature. At present, the database contains ~2,300 records, each accompanied by metadata extracted from the source publication. The accompanying web tool, available at https://aptlas.bavleyguerguis.com/, allows users to browse and filter by material system, instrument, application, publication type, or keyword search.
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Materials Science
Data-Driven Discovery of Unconventional Antiferromagnets
Qirui Cui, Chenxu Liu, Anna Delin et al. (+1 more)
Unconventional antiferromagnets combine zero net magnetization with
spin-split electronic bands, offering a distinct, important platform for spintronics. Their discovery, however, has so far depended largely on case-by-case studies and on a limited number of compounds with experimentally resolved
magnetic structures. Here, we overcome these bottlenecks by resolving
magnetic ground states across a broad materials database. We narrow down 37163 magnets from the Materials Project to 189 collinear antiferromagnets by combining physics-informed prescreening, high-throughput exchange calculations and Luttinger-Tisza analysis. Among these,
symmetry analysis identifies 36 altermagnets and 11 Luttinger-compensated ferrimagnets (LCFs), including 22 altermagnets and 9 LCFs that have not been reported previously. The identified unconventional antiferromagnets can support nonrelativistic
spin Hall effects and doping-tunable
spin transport with switchable polarization and
giant anisotropy. Our framework converts broad structural databases into a curated,
symmetry-classified set of experimentally testable compensated
spin-split magnets, establishing a scalable route for the efficient discovery of functional antiferromagnets.
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All authors Qirui Cui, Chenxu Liu, Anna Delin, Kaiyou Wang
Materials Science
Microscopic origin of polytype-dependent melting in SiC revealed by machine-learning molecular dynamics
Ljiljana Stojanović, Samuel J. Magorrian, Lara Kabalan et al. (+3 more)
Predicting how
crystal structure influences high-temperature stability remains a key challenge in materials modelling and design. Silicon carbide (SiC), one of the most thermally and chemically stable materials known, provides an ideal system for studying this problem because its many polytypes preserve similar local tetrahedral bonding while differing in long-range stacking geometry. Here, we combine phase-coexistence machine-learning molecular dynamics with finite-temperature
phonon analysis, enabled by a fine-tuned MACE interatomic potential that accurately describes crystalline, high-temperature, and disordered configurations across multiple SiC polytypes. We identify a clear relative stability ordering, 3C > 2H > 9R, reflected consistently in structural disordering, interlayer sliding, and finite-temperature
phonon spectra. Across all polytypes, melting initiates through the formation of short C-C contacts and carbon-rich local regions, followed by a progressive loss of tetrahedral Si-C connectivity. The reduced stability of the long-period 9R polytype is traced to low-frequency transverse-acoustic shear modes associated with relative
bilayer sliding, which are already present in the 0 K
phonon spectra and soften further at high temperature. These modes generate larger lateral
bilayer displacements, linking enhanced interlayer sliding to local chemical disordering and ultimately melting. More broadly, our results show that high-temperature stability in polytypic covalent materials is governed not only by local bond strength, but also by stacking-dependent transverse dynamics.
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All authors Ljiljana Stojanović, Samuel J. Magorrian, Lara Kabalan, Richard N. White, Fabian L. Thiemann, Viktor Zólyomi
Materials Science · Cross-listed from physics.comp-ph
Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations
Abhiram Badrinarayanan, Davor Davidovic, Edoardo Di Napoli et al. (+4 more)
Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architectures. In the context of the LimitX project, we propose a data-driven framework to accelerate these calculations. By shifting the machine learning target from discrete
eigenvalues to the coefficients of an interpolating Chebyshev
polynomial, and by comparing both all-atom and fragment-based structural representations, we successfully overcome the dimensionality constraints of large-scale spectral prediction. We investigate three machine learning models (Kernel Ridge Regression, Graph Neural Networks, and Random Forests) trained on a novel 2 TB
dataset of
protein dimers. The predicted spectra provide initial guesses that effectively bypass early Self-Consistent Field (SCF) iterations in BigDFT. Ultimately, these spectral predictors will be deployed to dynamically optimize upcoming rational filter-based eigensolvers, such as FrASE, which is currently in initial development.
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All authors Abhiram Badrinarayanan, Davor Davidovic, Edoardo Di Napoli, Jurica Novak, Luigi Genovese, Gustavo Ramirez-Hidalgo, Xinzhe Wu
Materials Science
Robust control over polar skyrmion bubble density with a combined optical and electrical approach
Lingyuan Gao and Laurent Bellaiche
Polar skyrmion bubbles are nanoscale ferroelectric domain configurations with swirling polarization textures, and often emerge in ferroelectric
oxide systems. Owing to their inhomogeneous polarization patterns, which endow them with distinct
topologies and electrical responses from homogeneous monodomains, polar skyrmion bubbles are envisaged to be promising candidates for non-volatile
memory devices. In such device, the recorded information density is directly proportional to the density of bubbles, underscoring the need for precise control over bubble nucleation. Here, using first-principles-based calculations, we demonstrate that when assisted with a DC electric field, twisted light, which has a spatially inhomogeneous field pattern, can robustly tune the density of polar skyrmion bubbles in ferroelectric ultrathin films between $10^2\sim 10^4 \rm{bit}/\mu m^2$. Moreover, by modulating DC and optical field strengths together with the beam radius, the nucleation rate, which characterizes the creation and annihilation speed of polar skyrmion bubbles, can also be well controlled. These findings highlight the unique response of ferroelectric nanofilms to optical and electric fields, which is crucial for employing polar skyrmion bubbles in the next-generation of ultrahigh-density
memory technologies.
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Materials Science
Microstructure-specific mechanisms define multistage relaxation dynamics in a metallic model-glass
Achraf Atila, Zengquan Wang, Birte Riechers et al. (+1 more)
Deciphering complex relaxation pathways in disordered solids is a central challenge across polymeric,
oxide, and metallic glasses, which traditionally relies on the interpretation of mechanical spectroscopy and resulting damping modes. Here we demonstrate the direct observation of dominant atomic-scale relaxation mechanisms during isothermal annealing of an as-quenched binary model glass towards incipient crystallization. Assessed via simulated x-ray
photon correlation spectroscopy, a multi-state structural decorrelation is uncovered via speckle-pattern analysis of the full three-dimensional diffraction sphere across the first peak of the structure factor. Over a simulation time of up to 10 $\mu$s, three distinct and subsequent decorrelation stages of thermal vibration, glassy network
evolution, and structural and chemical ordering towards crystallization are identified. These findings promote a picture where specific dynamically-separated mechanisms drive the microstructural
evolution during glass relaxation and suggest a much richer multi-mode relaxation behavior of metallic glasses than hitherto identified.
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All authors Achraf Atila, Zengquan Wang, Birte Riechers, Robert Maaß
Materials Science · Cross-listed from cs.AI
Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
Edward W. Staley, Tom Arbaugh, Michael Pekala et al. (+6 more)
Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning of these materials remains difficult due to the complexity of the associated physical processes and limited availability of computational tools. We introduce a novel hybrid framework to evaluate Large
Language Models (LLMs) in inorganic synthesis planning by combining thermodynamic databases with simplified kinetics models to approximate realistic synthesis conditions. As a case study, we focus on the niobium-oxygen system, which features multiple industrially relevant
oxide phases with well-characterized data. In computational simulations, we compare LLM-generated synthesis routes with classical path-planning
algorithms, showing that the implicit priors in LLMs can yield more viable strategies. In our evaluation setting, classical search methods serve primarily as a foil rather than a direct competitor. This illustrates the relative complexity of the problem and highlights where the LLM's implicit priors add value.
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All authors Edward W. Staley, Tom Arbaugh, Michael Pekala, Alexander New, Christopher D. Stiles, Nam Q. Le, Gregory Bassen, Wyatt Bunstine, Tyrel McQueen
Materials Science
Co-adsorption mechanism drives CO oxidation on defective ZnS
P.R.A. de Oliveira, C.Codeço, M.G.Menezes et al. (+3 more)
Reactivity on wide-bandgap
semiconductor surfaces relies critically on the generation of active sites. In the case of CO oxidation, however, the mere presence of defects is insufficient to drive reactivity. Here, we investigate CO oxidation on a defective ZnS single-
crystal surface by combining near ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) and density functional theory (DFT) calculations. NAP-XPS measurements reveal CO$_2$-like surface intermediates only under oxygen-rich conditions, consistent with oxygen-assisted CO oxidation. DFT calculations support an oxygen-assisted co-adsorption pathway in which CO interacts preferentially with adsorbed oxygen species stabilized near Zn-deficient sites, forming weakly bound CO$_2$-like structures. These results identify oxygen coverage, rather than defect density alone, as the key factor controlling CO$_2$-like intermediate formation on defective ZnS and establish defective ZnS as a model platform for studying oxygen-assisted surface chemistry on non-
oxide semiconductors.
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All authors P.R.A. de Oliveira, C.Codeço, M.G.Menezes, P.Venezuela, F.Stavale, J.A.Boscoboinik
Materials Science · Cross-listed from cond-mat.str-el
Electron vs. hole doping in infinite-layer nickelates: electronic structure, magnetism and correlations
Ezra Day-Roberts, Fabio Bernardini, Harrison LaBollita et al. (+3 more)
The observation of superconductivity in undoped infinite-layer nickelates $R$NiO$_2$ ($R$ = rare earth) challenges our current understanding and calls for a re-examination of the underlying electronic structure of this family of materials. In this context, it is particularly important to extend the investigation of $R$NiO$_2$ compounds from the intensively studied hole-doped regime to the almost unexplored electron-doped one. Here, we use a combination of density-functional theory and dynamical mean-field theory to study the
evolution of the electronic structure of infinite-layer nickelates in these two doping regimes. We find a striking asymmetry in the self-doping of the Ni-$d_{x^2-y^2}$ band due to the $R(5d)$ states: while this effect is strongly suppressed upon hole doping, electron doping instead leads to an increase in the size of the $R(5d)$ electron pockets, but without effectively hole-doping the Ni-$d_{x^2-y^2}$ band. This asymmetry has an important impact on the
magnetic response as antiferromagnetism is rapidly suppressed upon hole doping, whereas it remains the ground state upon electron doping. Despite these differences, electronic correlations on both sides of the phase diagram are dominated by the Ni $d_{x^2-y^2}$ orbital, suggesting that a single-band description may be appropriate for infinite-layer nickelates in both the electron- and hole-doped regimes.
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All authors Ezra Day-Roberts, Fabio Bernardini, Harrison LaBollita, Yi-Feng Zhao, Andres Cano, Antia S. Botana
Materials Science · Cross-listed from cs.LG
AI-Guided Design and Optimization of Graphite-Based Anodes via Iterative Experimental Feedback
Qian Du, Mark M. Sullivan, James E. Saal et al. (+1 more)
This study presents an iterative AI-guided workflow that accelerates graphite-based anode development by improving both formulation feasibility and process robustness. Sequential learning via AI/ML-guided multiobjective inverse design for anode optimization was implemented using the Citrine Platform. Starting from a noisy, incomplete
dataset, the Citrine Platform was used to generate early surrogate models, which despite low predictive certainty highlighted missing process constraints. By iteratively adding feasibility labels and boundary condition failures, the workflow rapidly converged toward manufacturable, higher-performing formulations. Fabrication reliability improved from frequent process failures to 100% successful
cell production, while the fraction of
cells delivering $\geq$ 350 mAh g$^{-1}$ increased from 28.4% to 84.8%, with capacity retention rising from 42.1% to 97.3%. These results demonstrate that structured, feedback-driven AI workflows can transform imperfect industrial data into actionable guidance, enabling faster, more reproducible optimization of battery electrode manufacturing.
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All authors Qian Du, Mark M. Sullivan, James E. Saal, Florian Huber
Materials Science
Advances in electrical contacts to single crystals of emerging materials for transport measurements
Huandong Chen, Abhay N. Pasupathy and Jayakanth Ravichandran
Transport measurements that probe electrical resistivity of a material under varying external stimuli, such as temperature,
magnetic field, optical illumination, and gate voltage, are among the most important experimental techniques in condensed matter physics. These measurements provide critical insights into the fundamental electronic properties of materials. In recent years, they have facilitated the discovery and exploration of intriguing physical phenomena (e.g., superconductivity and
quantum oscillations) and unique device functionalities (e.g., photoresponse and electrostatic gating effects) in various emerging materials, particularly in the form of single
crystals. However, unlike large-scale wafers or thin films, newly synthesized single
crystals often pose substantial challenges in establishing reliable electrical contacts due to their irregular geometries, limited dimensions, inherent structural characteristics, and potential susceptibility to degradation. In this review, we highlight recent technological advancements in the fabrication of high-quality, lithographically defined multi-terminal electrodes on both exfoliable and non-exfoliable single
crystals for transport measurements. Our work provides a practical guide for researchers seeking to select appropriate contact-fabrication strategies tailored to unique characteristics of emerging
crystals.
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Materials Science · Cross-listed from cs.CE
Can dents and gouges compromise the structural integrity of hydrogen transport pipelines?
R. Das, B. Bezensek and E. Martínez-Pañeda
Repurposing natural gas pipelines for hydrogen transport requires understanding how external defects, like dents and gouges, affect structural integrity under H$_2$ exposure. To address this, we combine experiments with a new hydrogen embrittlement model aimed at large plastic straining scenarios, which integrates: (i) multi-trap hydrogen transport, (ii) finite-strain plasticity, and (iii) a hydrogen- and triaxiality-dependent damage law. Each constituent of the model is validated with experiments on X65 pipeline steel: (i) hydrogen permeation, (ii) full-scale pipe-indentation, and (iii) mechanical testing at different hydrogen and triaxiality levels. The validated model is used to study passive (indent before H$_2$ exposure) and active (indent with H$_2$) dents and gouges. Results reveal that hydrogen does not significantly increase the damage severity of those defects, unless hydrogen egress is completely precluded at the outer surface of a pipeline that is being pressurised internally and contains a pre-existing passive dent with a gouge.
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Materials Science
Multiplet-Selective Photoelectron Diffraction from an Altermagnet
L. Plucinski
Direct real-space probes of altermagnetic order remain scarce. Here we introduce multiplet-selective photoelectron diffraction (PED), a methodology in which different regions of a transition-metal core-level multiplet act as distinct photoemission source waves. Using multiple-scattering calculations for the metallic altermagnet candidate CrSb, we show that selected Cr $3p$ multiplet features with predominantly $Y_1^{+1}$ and $Y_1^{-1}$ character generate robust diffraction asymmetries sensitive to altermagnetic domains. We demonstrate that both circularly and linearly polarized light provide access to the effect, while suitable combinations of domains, light polarizations, and multiplet-energy windows suppress nonmagnetic diffraction backgrounds. The proposed approach can be implemented using standard momentum-resolved photoemission instrumentation and establishes core-level PED as a practical route toward domain-resolved studies of altermagnets.
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Materials Science
General-purpose LLMs as Constrained Crystal Composition Generators
Hedda Oschinski, Maximilian L. Ach, Konstantin S. Jakob et al. (+2 more)
The targeted discovery of inorganic materials remains challenging due to the vastness of compositional design spaces and the high cost of exhaustive screening. Task-specific generative artificial intelligence represents a particularly efficient alternative to screening, yet demands tedious collection of training data before providing real benefit. General-purpose large
language models (LLMs) have recently shown tremendous potential for the targeted generation of single, optimal materials compositions without the need for task-specific fine-tuning. However, it is unclear whether LLMs generally pose an advantage compared to specialized generative models, in particular in large design spaces. Here, we demonstrate that such models are capable of covering entire regions of the targeted property space effectively and systematically. Using Elpasolite materials as an established
benchmark for generative tasks in large chemical spaces, we find that an iterative
prompt-and-response framework is able to recover on average 96% of all low-energy Elpasolites in the target region. This performance, driven mainly by iterative in-context learning, surpasses the generative abilities of previous, task-specific models. Our results establish general-purpose LLMs as flexible and accessible components for inverse materials design workflows.
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All authors Hedda Oschinski, Maximilian L. Ach, Konstantin S. Jakob, Christian Carbogno, Karsten Reuter
Materials Science
Ab Initio Spinor Kadanoff-Baym Approach to Nonequilibrium Electron, Phonon and Magnon Dynamics in Itinerant Ferromagnets
Giovanni Marini
This work introduces a theoretical framework based on the Kadanoff-Baym equations in spinor space to study ultrafast magnetization dynamics in itinerant
ferromagnetic systems from first principles. By incorporating
spin-orbit coupling into the ab initio
Hamiltonian and generalizing the self-energies to include terms beyond the charge sector, I derive scattering integrals within the Markov approximation and quasiparticle renormalizations for electrons and
phonons in the presence of
spin-dependent effective interactions within a many-body perturbation theory approach. I explicitly discuss how
magnons emerge in this framework, and derive, through suitable approximations, a closed and tractable set of equations for coupled electron,
phonon and
magnon dynamics that can be solved from first principles. I discuss the equations of motion within a minimal
ferromagnetic model, where the coupled equations are solved numerically. This approach allows one to treat coherent and incoherent
magnetic dynamics on an equal footing, paving the way for a first principles understanding of ultrafast
magnetic dynamics and demagnetization, and opening to a truly predictive theory of femtomagnetism in periodic systems.
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Materials Science · Cross-listed from cond-mat.supr-con
What controls the superconducting dome of electron-doped FeSe?
Paul T. Malinowski, Chad J. Mowers, Yaoju Tarn et al. (+3 more)
Superconducting domes are conspicuous features of the phase diagrams of most unconventional and high-temperature
superconductors. The superconducting transition temperature ($T_{c}$) of FeSe can be dramatically enhanced with electron doping, but unlike all other high-temperature and unconventional
superconductors, its full phase diagram and superconducting dome have yet to be fully explored. Here, we employ a combination of molecular beam epitaxy synthesis, alkali surface doping, in-
vacuum electrical transport, and angle-resolved photoemission spectroscopy to investigate the entire superconducting dome of electron-doped FeSe, achieving a fully metallic state where superconductivity is suppressed in the heavily overdoped regime. We discover a robust scaling between $T_{c}$ and the residual resistivity ($\rho_{0}$) which holds across the entire superconducting dome, suggesting that the
evolution of $T_{c}$ is heavily influenced by the
evolution of the elastic scattering rate in the high-$T_{c}$ electron-doped phase. This in turn suggests that the superconducting dome in electron-doped FeSe appears to be fundamentally different than that of other unconventional
superconductors where doping plays the primary role, and may be driven primarily by the sensitivity of the superconductivity to disorder.
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All authors Paul T. Malinowski, Chad J. Mowers, Yaoju Tarn, Darrell G. Schlom, Brendan D. Faeth, Kyle M. Shen
Materials Science
Strain-Engineered s-C$_3$N$_6$ Monolayer for Efficient Water Splitting: A first-principles study
Khushboo Dange and Alok Shukla
Photocatalytic water splitting offers a sustainable route for
solar-to-hydrogen energy conversion, yet identifying stable, metal-free
semiconductors with suitable electronic, optical, and band-
alignment properties remains challenging. Here, we investigate the structural, mechanical, electronic, optical, and photocatalytic properties of the two-dimensional s-C$_3$N$_6$ monolayer using first-principles calculations. Ab initio molecular dynamics and elastic constant analysis confirm its thermal and mechanical stability. Hybrid HSE06 calculations reveal pristine s-C$_3$N$_6$ is a direct-band-gap
semiconductor (2.62 eV). However, its conduction-band minimum lies below the hydrogen reduction potential, preventing spontaneous hydrogen
evolution. To overcome this limitation, we employ biaxial and uniaxial strains (-10% to +10%) to modulate its electronic structure. We find that compressive biaxial strains of -8% and -10% uniquely tune the band edges to straddle the redox potentials, enabling spontaneous overall water splitting. Crucially, these photocatalytically active states remain mechanically and thermally stable. Optical properties calculations show the fundamental gap in both pristine and strained structures is optically dark, with the primary absorption peak in the UV region. Furthermore, a strain-induced mobility mismatch between electrons and holes facilitates efficient charge separation. However, thermodynamic modeling of surface kinetics reveals that the s-C$_3$N$_6$ surface binds intermediates strongly, necessitating a co-catalyst to overcome kinetic barriers. Our results establish strain engineering as an effective strategy to tailor band-edge
alignment, carrier dynamics, and optical transitions in s-C$_3$N$_6$, highlighting its potential for stable 2D photocatalytic water splitting.
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Materials Science
Pu Zhang, Sun-Bo Xie, Junxi Yu et al. (+2 more)
Magnons, as charge-neutral
spin excitations, can transport
spin information without Joule heating and therefore offer a promising platform for low-power spintronics. However, in collinear magnets, the effective time-reversal
symmetry forbids odd-parity
magnon band splitting. Here we propose odd-parity
magnons and establish a general mechanism for realizing them in collinear antiferromagnets. We provide a complete
spin-point-group classification of odd-parity
magnon splitting in two-dimensional collinear antiferromagnets by identifying the leading splitting types and their
symmetry-allowed basis functions. This classification serves as a practical guide for searching for odd-parity
magnons. We show that breaking effective time-reversal
symmetry, for example by circularly polarized light or loop currents, can induce highly tunable $p$- and $f$-wave
magnon splitting. In
bilayer systems, the dynamical modulation can drive a topological
magnon phase transition, accompanied by
chiral edge modes and an abrupt jump in the
magnon thermal
Hall conductivity. Material-specific first-principles calculations further demonstrate the feasibility of this mechanism in real van der Waals antiferromagnets. Our study identifies the odd-parity
magnons as a new class of
spin excitations and provides a theoretical foundation for odd-parity
magnons and ultrafast optically controlled topological magnonic devices.
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All authors Pu Zhang, Sun-Bo Xie, Junxi Yu, Yichen Liu, Cheng-Cheng Liu
Materials Science
Crystallisation kinetics of supercooled liquid palladium
Zuzanna Kostera, Przemyslaw Dziegielewski, Christian Bressler et al. (+13 more)
In this study, we employ classical molecular dynamics (MD) simulations to investigate the crystallisation kinetics of supercooled
liquid palladium and relate the results to time-resolved X-ray diffraction measurements on rapidly quenched Pd thin films.
Crystal nucleation and growth rates are determined over the temperature range $700$–$1150~\mathrm{K}$ ($0.38$–$0.65 T_{\mathrm{m}}$) by analysing the
evolution of the microstructure during the
liquid-to-
crystal transition. The self-
diffusion coefficient of Pd, obtained from the atomic mean-squared displacement, follows Arrhenius behaviour over the investigated temperature range, with an activation energy of $467(6)~\mathrm{meV/atom}$, consistent with available data for supercooled
liquid metals. The steady-state homogeneous nucleation rate exhibits a maximum of approximately $4 \times 10^{35}~\mathrm{m^{-3} s^{-1}}$ near $0.5 T_{\mathrm{m}}$.
Crystal growth occurs at velocities of the order of metres per second, with a temperature dependence consistent with
diffusion-limited Wilson-Frenkel kinetics rather than the collision-limited regime. Based on multiple statistically independent simulations, a time-temperature-transformation (TTT) diagram for crystallisation onset is constructed. The TTT curve exhibits a nose near $0.5 T_{\mathrm{m}}$ and $100~\mathrm{ps}$, corresponding to a critical cooling rate for vitrification on the order of $10^{13}~\mathrm{K s^{-1}}.$ The simulations reproduce the crystallisation onset time and temperature observed in time-resolved X-ray diffraction experiments on optically molten Pd thin films quenched at $5 \times 10^{11}~\mathrm{K s^{-1}}.$ These results indicate that homogeneous, rather than heterogeneous, nucleation governs the achievable supercooling in the experimentally studied films.
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All authors Zuzanna Kostera, Przemyslaw Dziegielewski, Christian Bressler, Wojciech Gawelda, Konstantinos Georgarakis, Dmitry Khakhulin, Oleksii I. Liubchenko, Adam Olczak, Angel Rodriguez-Fernandez, Ryszard Sobierajski, Klaus Sokolowski-Tinten, Peihao Sun, Robert W.E. van de Kruijs, Hazem Yousef, Peter Zalden, Jerzy Antonowicz