Hexa-Graphyne: A Transparent and Semimetallic 2D Carbon Allotrope with Distinct Optical Properties Jhionathan de Lima, Felipe Hawthorne, Cristiano F. Woellner ACS Omega, 2026 -hybridized carbon atoms. First-principles calculations confirm its energetic, dynamical and thermal stability (up to at least 1000 K). Regarding its band structure, this material exhibits a semimetallic nature. It exhibits high mechanical compliance, with a Young's modulus approximately 13 times lower and a Poisson's ratio nearly 4 times higher than those of graphene. The optical response is marked by strong ultraviolet absorption, high infrared reflectivity, and pronounced transparency in the visible-light range. Raman and infrared spectra exhibit sharp and well-separated peaks, providing a clear signature of acetylenic linkage stretching vibrations. Nanoribbon structures derived from HXGY show distinct electronic behaviors depending on the edge termination type and width. These findings highlight the HXGY potential for nanoelectronic and optoelectronic applications.
Deciphering the Interface between Two-Dimensional Aluminum Quasicrystals and Norepinephrine Neurotransmitter Anyesha Chakraborty, Felipe Hawthorne, Thakur Prasad Yadav, Nilay Krishna Mukhopadhyay, Prikshat Dadhwal, Pranith Chander Saka, Basudev Lahiri, Cristiano F. Woellner, Chandra Sekhar Tiwary ACS Applied Materials and Interfaces, 2025 Norepinephrine (NE) serves as a vital neurotransmitter, regulating various physiological and cognitive processes in the central nervous system. NE detection is crucial for improving diagnostic and therapeutic monitoring. The current study elucidates the molecular interactions of NE with a two-dimensional multielement aluminum quasicrystal (2D-Al70Co10Fe5Ni10Cu5 (2D-Al QC)) through vibrational spectroscopy and theoretical simulations including geometry optimization, charge transfer dynamics, and bond length variations. The interaction dynamics are monitored in real-time at the atomic scale by in situ liquid cell transmission electron microscopy (LCTEM). The results confirm the binding of the –OH group of NE molecules with the aluminum atoms of the 2D-Al QC by Al–O bonding. Based on this binding mechanism, an electrochemical sensor is developed using the 2D-Al QC, for ultrasensitive and selective detection of NE. The sensor exhibits two distinct linear detection ranges: a higher range from 1 nM to 1 μM, and a lower range from 1 pM to 500 pM. The sensor achieves ultralow detection limits of 0.42 ± 0.02 nM and 0.17 ± 0.04 pM, with corresponding quantification limits of 1.28 ± 0.02 nM and 0.5 ± 0.04 pM. The sensor demonstrates outstanding selectivity against potential interferents, excellent reproducibility across seven electrodes with minimal variation of 3%, and sustained performance over 90 days with a negligible deviation of 4.6%. This work highlights the potential of 2D-Al QC-based electrochemical sensors as a robust, scalable platform for neurotransmitter detection, paving the way for enhanced point-of-care diagnostics and neurochemical monitoring.
Role of translational noise in motility-induced phase separation of hard active particles Felipe Hawthorne, Pablo de Castro, José A. Freire Physical Review E, 2025 Self-propelled particles, like motile cells and artificial colloids, can spontaneously form macroscopic clusters. This phenomenon is called motility-induced phase separation (MIPS) and occurs even without attractive forces, provided that the self-propulsion direction fluctuates slowly. In addition to rotational noise, these particles may experience translational noise, not coupled to rotational noise, due to environmental fluctuations. We study the role of translational noise in the clustering of active Brownian hard disks. To tease apart the contribution of translational noise, we model excluded-volume interactions through a Monte-Carlo-like overlap rejection approach. We find that increasing translational diffusivity has a nonmonotonic effect on clustering. At low values, it makes clusters more compact and rounded (less filamentous), eventually promoting genuine MIPS. For sufficiently higher translational diffusivity, clusters evaporate. We develop a theory for the cluster mass distribution, and employ a hydrodynamic approach with parameters taken from the simulation, which explains the clustering phase diagram.
Interface Engineering of 3D-Printed Liquid Crystal and 2D-White Pearl Composite for Tunable Fluorescence Nabarun Mandal, Felipe Hawthorne, Rahul Rao, Ajit K. Roy, Douglas Soares Galvão, Vidya Kochat, Cristiano F. Woellner, Michael E. McConney, Chandra Sekhar Tiwary Advanced Engineering Materials, 2025 The ability to tune fluorescence in polymer composites via 2D materials, dyes, or interfacial modifications provides a versatile platform for advancing optoelectronics as the underlying mechanisms offer control over emission properties, leading to innovative materials. In this work, 2D‐white pearl (2D‐WP) has been synthesized from naturally occurring WP. Liquid crystal polymer (LCP) composites based on liquid crystal (LC) monomer mixture E7 have been produced via 3D printing. 2D‐WP has been dispersed in the LCP composite to demonstrate LC–2D interaction and generation of fluorescence. It has been shown that by introducing interfaces, a secondary emission can be obtained from 2D‐dispersed LCP composites. The interactions between the four monomers in E7 and 2D‐WP have been simulated, depicting a reduction in the original bandgap of 4.31 eV for 2D‐WP to 2.5 eV for LCP‐2D composite. In this way, 3D‐printed LCP in combination with 2D‐WP is shown to be an exciting prospect in further optical and photonics studies.
Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress–Strain and Vibrational Properties Felipe Hawthorne, Paulo R. E. Raulino, Ronaldo Rodrigues Pelá, Cristiano F. Woellner Journal of Physical Chemistry C, 2025 High Resolution Image Download MS PowerPoint Slide Machine learning interatomic potentials (MLIPs) offer an efficient and accurate framework for large-scale molecular dynamics (MD) simulations, effectively bridging the gap between classical force fields and ab initio methods. In this work, we present a reactive MLIP for graphene, trained on an extensive data set generated via ab initio molecular dynamics (AIMD) simulations performed using the local density approximation (LDA) exchange–correlation functional and the projector-augmented wave (PAW) method. The model accurately reproduces key mechanical and vibrational properties, including stress–strain behavior, elastic constants, phonon dispersion, and the vibrational density of states. Notably, it captures temperature-dependent fracture mechanisms and the emergence of linear acetylenic carbon chains upon tearing. The phonon analysis also reveals the expected quadratic ZA mode and excellent agreement with experimental and density functional theory (DFT) benchmarks. Our MLIP scales linearly with system size, enabling simulations of large graphene sheets with ab initio -level precision. This work delivers a robust and transferable MLIP, alongside an accessible training workflow that can be extended to other materials.
Melanin-Based Compounds as Low-Cost Sensors for Nitroaromatics: Theoretical Insights on Molecular Interactions and Optoelectronic Responses João P. Cachaneski-Lopes, Felipe Hawthorne, Cristiano F. Woellner, Toby L. Nelson, Roger C. Hiorns, Carlos F. O. Graeff, Didier Bégué, Augusto Batagin-Neto ACS Omega, 2025 Nitroaromatic compounds (NACs) are used in various industrial applications including dyes, inks, herbicides, pharmaceuticals, and explosives. Due to their toxicity and environmental persistence, reliable detection and monitoring methods are required. Hybrid organic-inorganic structures have shown potential for NAC sensing; however, their complex synthesis, high processing costs, and limited reproducibility hinder practical implementation, highlighting the need for simpler and more accessible materials. In this study, we employed density functional theory (DFT)-based calculations to evaluate the electronic, optical, and reactive properties of two melanin-based oligomeric systems, aiming to assess their potential use as NAC detectors. Our results indicate the potential of these materials to detect a series of nitroaromatic compounds such as 2,4-DNP, 2,4-DNT, 2,6-DNT, TNP, and TNT by electrical and infrared optical measurements. Born-Oppenheimer molecular dynamics (BOMD) simulations reveal the thermal stability of the adsorption process, confirming effective substrate-analyte interaction under different temperature conditions. To the best of our knowledge, this compound has not been proposed for sensing applications. Its low cost and facile synthesis make it a promising candidate for the development of environmentally friendly organic NAC sensors.
Nanoconfined water phase transitions in infinite graphene slits: Molecular dynamics simulations and mean-field insights Felipe Hawthorne, Virgília M.S. Neta, José A. Freire, Cristiano F. Woellner Carbon Trends, 2025 Recent experimental and computational studies have demonstrated that nanoconfinement profoundly alters the phase behavior of water, facilitating complex phase transitions at pressures and temperatures far lower than typically observed in bulk systems. When combined with adsorption, nanoconfinement substantially enhances water uptake, primarily due to condensation occurring at the onset of the isotherm curve—a phenomenon intimately related to the facilitated formation of hydrogen bond networks. In this study, we adopt a dual approach to investigate water confined within infinite graphene slits. Our Molecular Dynamics simulations reveal hysteresis across all investigated temperatures. Unlike in finite slits, where hysteresis arises due to surface tension effects at the edges, in the case of infinite slits, the hysteresis is the result of a genuine phase transition at the nanoscale. We analyze the spatial and orientational arrangements of the water molecules, demonstrating how the graphene surface promotes the formation of a hydrogen bond network in the adjacent water layers. The remarkably low pressure required for water uptake in this nano-environment is explained at the mean-field level using a simple interacting lattice model. This is attributed to the exponential dependence of the critical pressure on the adsorbate–adsorbent interaction.
Thermodynamics of a minimal interacting heat engine: Comparison between engine designs Felipe Hawthorne, B. Cleuren, Carlos E. Fiore Physical Review E, 2024 Collective effects stemming from many interacting units have attracted remarkable recent interest, not only for their presence in several systems in nature but also for the possibility of being used for the construction of efficient engine setups. Notwithstanding, little is known about the influence of the engine design, and most studies are restricted to the simplest cases (e.g., simultaneous contact with two thermal baths), not necessarily constituting a realistic setup implementation. In order to investigate the design and its influence on the performance, we introduce the collisional also referred as sequential description for a minimal model for interacting heat engines, composed of two coupled nanomachines placed in contact with a distinct thermal reservoir and subjected to a nonequilibrium work source at each stage. Thermodynamic quantities are exactly obtained irrespective of the model details. Distinct kinds of work sources are investigated and the influence of the interaction, temperature, period, and time asymmetry has been undertaken. Results show that a careful design of interaction provides superior performance than the interactionless case, including optimal power outputs and efficiencies at maximum power greater than known bounds or even the system presenting efficiencies close to the ideal (Carnot) limit. As a complementary analysis, we also show that the case of the system simultaneously placed in contact with two thermal reservoirs constitutes a particular case of our framework.
Nonequilibrium Thermodynamics of the Majority Vote Model Felipe Hawthorne, Pedro E. Harunari, Mário J. de Oliveira, Carlos E. Fiore Entropy, 2023 The majority vote model is one of the simplest opinion systems yielding distinct phase transitions and has garnered significant interest in recent years. This model, as well as many other stochastic lattice models, are formulated in terms of stochastic rules with no connection to thermodynamics, precluding the achievement of quantities such as power and heat, as well as their behaviors at phase transition regimes. Here, we circumvent this limitation by introducing the idea of a distinct and well-defined thermal reservoir associated to each local configuration. Thermodynamic properties are derived for a generic majority vote model, irrespective of its neighborhood and lattice topology. The behavior of energy/heat fluxes at phase transitions, whether continuous or discontinuous, in regular and complex topologies, is investigated in detail. Unraveling the contribution of each local configuration explains the nature of the phase diagram and reveals how dissipation arises from the dynamics.
