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Physics Condensed Matter Materials Science

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Thursday 30 July

Materials Science

Oxygen Sensing Without Organic Molecules: Mixed-phase TiO2 as Cost-effective Ultrasensitive Optical Sensors

R.Rega, A.Fioravanti, F.Borbone et al. (+2 more)

Oxygen (O2) detection is commonly carried out via either fluorescence-based optical sensors or chemoresistive sensors. Each approach has its own limitations. Optical sensors require the molecular design and synthesis of specific organic fluorescent species which can be costly and less stable. Chemoresistive sensors, despite presenting advantages in using more cost-effective inorganic materials, are often limited by low sensitivities to O2 at ppm concentrations and by their inability to operate at room temperature. In this work, we demonstrate the detection of O2 at concentrations as low as a few tens of ppm at room temperature by using titanium dioxide (TiO2) mixed-phase nanoparticles as optical sensors. By simultaneously measuring the photoluminescence of nanoparticles in rutile and anatase phase, O2 detection was achieved in the concentration range of 30-500 ppm, with a response curve well-calibrated by a Langmuir function. Good response promptness and repeatability are also demonstrated. This approach to O2 optical sensing offers two intrinsic advantages over the most commonly used methodologies: (1) use of a cost-effective, easy-to-prepare and stable of the sensitive material compared to those typically employed in optical sensing, and (2) improved room-temperature detection efficiency in the low O2 concentration range, outperforming most commonly-used chemoresistive sensors.
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All authors R.Rega, A.Fioravanti, F.Borbone, M.Mazzocchi, S.Lettieri

Materials Science

High-Field EPR/ENDOR of N/Be Centers for Defect Engineering in 6H-SiC

Yuliya Ermakova, Ekaterina Dmitrieva, Margarita Sadovnikova et al. (+5 more)

Silicon carbide (SiC) in its various structural modifications is widely used in power semiconductor electronics, operating under extreme conditions of high temperature, high voltage, and intense radiation. The discovery of spin defects (S>0) with unique optical and coherent properties has further positioned SiC as a promising platform for quantum technologies. Here, we investigate a 6H-SiC single crystal co-doped with nitrogen and beryllium at concentrations of 1018 cm-3, using continuous-wave and pulsed electron paramagnetic resonance (EPR) and electron-nuclear double resonance (ENDOR). To enhance spectral resolution, experiments were conducted in the W-band (94 GHz; B = 3.4 T). Pulsed EPR identified nitrogen donors and beryllium acceptors in various lattice positions, allowing for the determination of their phase coherence and spin-lattice relaxation times. ENDOR measurements elucidated the electron-nuclear interactions with the local silicon and carbon environment, including distant coordination spheres. The observed hyperfine structures indicated highly delocalized spin density within the supercell. The TRIPLE resonance spectra verify coupled nuclear spin subspaces from different coordination spheres due to defect spin density. These results demonstrate the feasibility of incorporating dual impurities with distinct functional roles while preserving the crystal lattice`s structural features.
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All authors Yuliya Ermakova, Ekaterina Dmitrieva, Margarita Sadovnikova, Fadis Murzakhanov, George Mamin, Sergey Nagalyuk, Evgeny Mokhov, Marat Gafurov

Materials Science · Cross-listed from cond-mat.mes-hall

Giant nonlinear Hall effect in a Pt/ferrimagnetic insulator bilayer under Zeeman-exchange frustration

Takayuki Shiino, Matteo Fettizio, Weronika Janus et al. (+1 more)

Competing magnetic interactions can create metastable or unstable states and render magnetic systems highly susceptible to external perturbations. Here we show that Zeeman-exchange frustration in an Al-substituted terbium iron garnet with a compositional gradient across its thickness gives rise to a giant nonlinear Hall response in an adjacent Pt layer. Near magnetic compensation, a field-induced spin-flip transition is accompanied by unusually large higher-order odd harmonic voltages, with the third, fifth, and seventh harmonics reaching amplitudes comparable to that of the first harmonic. The field, temperature, and current dependences collectively identify Joule heating as the parametric drive of the harmonic response. Macrospin-chain simulations further show that current-induced thermal modulation periodically switches the interfacial Fe magnetization between exchange- and Zeeman-dominated states and reproduces the observed harmonic signals. These results demonstrate how frustration can convert a weak thermal perturbation into a large nonlinear electrical response, providing a route to nonlinear magnetotransport in compensated ferrimagnets.
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All authors Takayuki Shiino, Matteo Fettizio, Weronika Janus, Can Onur Avci

Materials Science

Deep Learning for Accelerated Long-Horizon Forecasting of Multicomponent Multiphase Microstructure Evolution in High-Entropy Alloys

Hamidreza Razavi and Nele Moelans

Phase-field modeling provides a powerful approach for predicting microstructure evolution but becomes computationally prohibitive for multicomponent and multiphase systems over large spatial and temporal scales. This work presents an AE-GCN-LSTM surrogate framework for long-horizon forecasting of microstructure evolution in the multicomponent AlCrFeNi high-entropy alloy system containing coexisting BCC and FCC phases. A multi-head autoencoder compresses the four elemental concentration fields and phase-field order parameter into latent representations, which are formulated as graphs for learning their spatial and temporal evolution. The framework accurately forecasts microstructure evolution over horizons extending to 3,000,000 simulation timesteps. Its robustness is systematically evaluated under previously unseen conditions without retraining, fine-tuning, or parameter adaptation. These evaluations include variations in FCC precipitate size and initial position, microstructures containing one, two, and five FCC precipitates, and complex phase interactions involving precipitate merging and splitting. Although trained only on 100 x 100 computational domains containing a single nominal alloy composition, the framework is successfully transferred to larger 256 x 256 and 512 x 512 systems and to previously unseen AlCrFeNi compositions. Across the evaluated configurations, the model preserves the dominant phase morphology and compositional evolution while providing computational speedups ranging from approximately 7200 to 62300 relative to conventional phase-field simulations. These results demonstrate that latent graph-based AE-GCN-LSTM forecasting provides a scalable and computationally efficient surrogate for long-horizon simulation of multicomponent, multiphase microstructures and offers a promising foundation for high-throughput alloy design.
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Materials Science

Finite-temperature bulk moduli from an EOS-based Grüneisen function

Çetin K{\i}l{\i}ç

An equation-of-state (EOS)-based construction of the Grüneisen function is developed and assessed through predictions of finite-temperature bulk moduli. In this approach, the volume dependence of the Grüneisen function is expressed analytically in terms of static EOS information, anchored by Debye temperatures obtained from elastic data sampled near equilibrium, and constrained by the infinite-compression limit. The resulting form requires as material-specific input only static energy-volume data and near-equilibrium elastic properties, with no parameters adjusted to thermal data. Within a Mie–Grüneisen–Debye framework, the approach is examined for diamond, magnesium oxide, silicon, and sodium chloride, chosen to span a broad range of stiffness, using machine-learning interatomic potentials from the Universal Models for Atoms (UMA) and Universal Point Edge Transformer (UPET) families, together with a dispersion-corrected variant of UMA. The calculated bulk moduli reproduce the expected experimental softening trends and capture the overall scale of the bulk-modulus temperature derivatives, although the level of quantitative agreement depends on the material, the underlying interatomic potential, and the selected analytic EOS form. These results show that an EOS-based construction of the Grüneisen function can capture the leading thermal-softening behavior of bulk moduli without fitting to thermal data. The observed sensitivity to the underlying static description further suggests that the framework may help identify deficiencies relevant to thermoelastic transferability and thereby inform future training and validation strategies for universal machine-learning interatomic potentials.
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Materials Science

A Combined Microbeam and Phase-Field Approach to Identify the Toughness and Ultimate Strength of Amorphous Silica

Gustavo Alberto Rosales-Sosa, Gergely Molnar, Yoshinari Kato et al. (+7 more)

This work presents a new approach to evaluating the toughness, described by the critical energy release rate ($G_c$), and ultimate tensile strength ($\sigma_c$) of amorphous silica (SiO$_2$ glass), combining microbeam tests and phase-field calculations. The latter provides a numerical route to brittle fracture without prescribing explicit fracture surfaces a priori, enabling crack initiation and propagation to be tracked. Single-notched microbeams and newly designed bone-shaped microbeams with a notch-free gauge section were fabricated by Focused Ion Beam (FIB) milling nd tested under bending in air, probing the brittle-fracture and strength-controlled regimes, respectively. Both geometries were modeled by Finite Element Analysis (FEA) coupled with a phase-field formulation. We found $G_c = 5.1$~J/m$^2$ (critical stress intensity factor $K_{IC} = 0.61$~MPa$\cdot$m$^{1/2}$), an intrinsic material length scale $\ell_c = 9.1$~nm, and $\sigma_c = 6.8$~GPa, consistent with previously reported brittle properties of silica glass. Through a parametric study, we show the effect of notch geometry on the fracture response of the microbeams and the impact of dimensional measurement error on the determined toughness. Unlike conventional micromechanical methods that yield only $K_{IC}$, our combined microbeam geometries and phase-field approach simultaneously deliver $G_c$ and $\sigma_c$, bridging brittle-fracture characterization and the strength-controlled regime inaccessible to toughness-only techniques.
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All authors Gustavo Alberto Rosales-Sosa, Gergely Molnar, Yoshinari Kato, Taichi Nakashima, Takahito Ohmura, Etienne Barthel, Guillaume Kermouche, Sergio Sao Joao, Shingo Nakane, Hiroki Yamazaki

Materials Science

Tilt-driven ferrielectricity in PbZrO$_3$

Huazhang Zhang, Ying Liu, Carson Carroll et al. (+6 more)

We reveal a tilt-driven mechanism for ferrielectricity in prototypical antiferroelectric PbZrO$_3$. Specifically, introducing an additional octahedral tilt into the antiferroelectric $Pbam$ phase breaks the symmetry constraint that enforces equal antiparallel dipoles, converting the compensated “$\uparrow \uparrow \downarrow \downarrow$” nonpolar configuration into an uncompensated “$\uparrow \uparrow \downarrow \downarrow$” polar $Pmc2_1$ phase. First-principles calculations show that the $Pmc2_1$ phase becomes stabilized under lattice contraction and gains increasing free-energy advantage over competing phases at finite temperatures. Atomic-scale imaging directly confirms the presence of $Pmc2_1$-like structures in thin films and single crystals. This work identifies a symmetry-governed, kinetically easily accessible pathway to ferrielectricity and establishes a form of “competitive” improper ferroelectricity, with broad implications for antiferroelectrics.
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All authors Huazhang Zhang, Ying Liu, Carson Carroll, Saptam Ganguly, Bin Xu, Xiaozhou Liao, Gustau Catalan, Philippe Ghosez, Nicholas C. Bristowe

Materials Science

Optimization of magneto-electric properties in Lead-free (x)Co1.2Ti0.2Fe1.6O4 - (100-x)BaTiO3 based composites

Rajeev Dwivedi, Samanway Mohanta, Ashutosh Anand et al. (+7 more)

This work presents a systematic study of lead-free multiferroic composites of (x)Co1.2Ti0.2Fe1.6O4 - (100-x)BaTiO3 (x = 10, 20, 30), which were synthesized by a solid-state reaction method to investigate the effects of composition and sintering temperature on their structural , electrical, magnetic, and magnetoelectric (ME) properties. X-ray diffraction along with Rietveld refinement confirms the coexistence of tetragonal BaTiO3 (BTO) and cubic spinel Co1.2Ti0.2Fe1.6O4 (CTFO) phases. Microstructural analysis shows that densification and grain growth are better at higher sintering temperatures, leading to better coupling between the two phases. Dielectric and ferroelectric studies indicate lossy polarization-electric field (P-E) behaviour due to leakage from the conductive phase, while magnetic properties show increased magnetization with increasing ferrite content. All composites exhibit ME coefficients, which depend on the composition and sintering conditions; the highest ME coefficient (~1.28 mV/cm.Oe) was observed for the 30CTFO - 70BTO composite sintered at 1200 {\deg}C. This improvement is due to the optimal balance between magnetostrictive and piezoelectric responses and improved interfacial strain transfer. These results demonstrate that simultaneous optimization of dopant-modified composition and sintering conditions is essential for achieving improved magnetoelectric coupling in bulk multiferroic composites. Moreover, the results demonstrate the potential of lead-free composites for multifunctional device applications in next-generation, low-power technologies, including high-density non-volatile memory (e.g. FeRAM/MRAM), magnetic field sensors, spintronic devices, and actuators.
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All authors Rajeev Dwivedi, Samanway Mohanta, Ashutosh Anand, Abhinash Tripathy, Najnin Bano, Dharmendra Kumar, Hemant Singh, R. Venkatesh, Sachin Gupta, Dinesh Kumar Shukla

Materials Science

Unconventional and Fragile Magnetic Exciton in a van der Waals Quantum Magnet

Kai-Xuan Zhang, Min Zhang, Minjae Kim et al. (+25 more)

The recently discovered magnetic exciton in the van der Waals (vdW) antiferromagnet NiPS3 exemplifies these phenomena, exhibiting several distinctive characteristics. Despite extensive investigation, much of its physics remains unresolved, with key questions about why the NiPS3 magnetic exciton is so sharp and optically bright despite the nominally spin-forbidden transition, posing significant challenges to a proper understanding and practical manipulation of the exciton. An urgent question is to what extent it is due to chemical disorder, magnetic weakening, lattice modification, or intrinsic instability of the bright exciton itself: answers to which will put stringent constraints on possible theoretical models. Here we address these questions using hydrostatic pressure as a clean, continuous, reversible, and in-situ tuning parameter. We find that the sharp photoluminescence peak is drastically suppressed by as little as 0.4 GPa and completely quenched by 1.5 GPa, with demonstrating its reversibility. Crucially, this bright-to-dark conversion occurs without magnetic, crystallographic, or electronic reconstruction despite an increase in the Neel temperature, as established by Raman, X-ray absorption, nuclear magnetic resonance spectroscopy, and first-principles many-body calculations. Our results demonstrate that the optical brightness of the magnetic exciton is independent of chemical disorder, lattice expansion, and weakening of magnetic order, indicating that a higher-order correlated mechanism governs the bright exciton. We further propose experimentally constrained microscopic scenarios involving exciton pairing, crystal-field-controlled spin-orbit mixing, and symmetry breaking, providing a framework for future tests of entangled magnetic exciton in correlated quantum magnets.
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All authors Kai-Xuan Zhang, Min Zhang, Minjae Kim, Yong-Hyun Kim, Junghyun Kim, Heejun Yang, Pyeongjae Park, Chaebin Kim, Mangesh Diware, Junik Hwang, Youjin Lee, Byeong-Gwan Cho, Hyeong-Do Kim, Tae-Yeong Koo, Chunhua Chen, Mingtao Li, Xujie Lü, Wenge Yang, Kee-Hoon Kim, Seung-Ho Baek, Hyeonsik Cheong, Sung-Keun Lee, Beom Hyun Kim, Christopher Lane, Jian-Xin Zhu, Zhaorong Yang, Young-Woo Son, Je-Geun Park

Materials Science

A Universal Crystal-Field Design Principle for Orbital-Order-Driven Altermagnetism

Shantanu Pathak and Saswata Bhattacharya

Altermagnets combine collinear antiferromagnetic order with nonrelativistic spin splitting, enabling spintronic functionalities without relying on spin–orbit coupling. While staggered orbital ordering has recently emerged as an alternative route to altermagnetism, its generality has remained unexplored. Here, we establish a universal crystal-field design principle for orbital-order-driven altermagnetism. We show that structural relaxation consistently reconstructs the crystal-field landscape, activating a common $d_{xz}/d_{yz}$ orbital manifold that drives spontaneous staggered orbital ordering and robust $d$-wave nonrelativistic spin splitting across transition-metal compounds spanning electron fillings from $d^1$ to $d^7$. By introducing a unified symmetry framework based on layer-dependent magnetic and orbital order parameters, we demonstrate how interlayer stacking determines whether the system realizes a bulk altermagnetic state or a globally compensated antialtermagnetic phase. Furthermore, we reveal that this symmetry-protected spin-split texture gives rise to highly anisotropic spin-polarized conductivities. Our results establish crystal-field engineering as a predictive design strategy for discovering and engineering orbital-order-driven altermagnets.
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Materials Science

Physics to Circuit Analysis of GaN RF Integrated Circuits versus GaAs and Silicon

Harkirat Kaur, Palak Kapoor and Rajesh Vedala

The migration of radio-frequency (RF) integrated-circuit platforms from silicon to GaAs and now to gallium nitride is derived here from first principles. The hexagonal non-centrosymmetric GaN lattice admits a macroscopic polarization; elasticity and the piezoelectric tensor fix the bound sheet charge at an AlGaN/GaN interface, and Poisson's equation with triangular-well quantisation yields a degenerate quasi-two-dimensional channel of ~10^13 cm^-2 with no doping. Energy-momentum conservation for pair creation and phonon-limited energy relaxation set the breakdown field (3.3 MV/cm) and saturation velocity (2.5 x 10^7 cm/s), which combine into geometry-free limits V_brf_T = E_cv_sat/(2pi) and R_on^sp = 4V_br^2/(muepsilonE_c^3). These limits are mapped onto the low-noise amplifier, power amplifier, and switch/phase-shifter functions of a transmit/receive front end and quantified by a MATLAB device-physics model comparing GaN, GaAs, and Si up to 90 GHz. The purpose of this framework and its simulations is to identify which material platform offers the best performance at millimeter-wave frequency signals.
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Materials Science

Anisotropic Tensile Strength and Fracture Mechanism of $\theta$-TaN: A Machine-Learning Potential Molecular Dynamics Study

Chenyang Cao, Hongfei Li and Shuo Cao

theta-phase tantalum nitride (theta-TaN) combines metallic conductivity with exceptionally high thermal conductivity, making it a potential material for device thermal management and interconnect applications. However, its tensile strength and fracture behavior remain unclear. Here, we investigate the anisotropic tensile response and fracture mechanism of theta-TaN using neuroevolution-potential molecular dynamics simulations. Size-convergence tests show that a 20 nm long model is sufficient for reliable prediction, and the mechanical parameters vary by less than 3.5% over the strain-rate range of 10^7 to 10^9 s^-1. The results reveal strong tensile anisotropy. The c-axis direction ([0001]) shows a higher strength of 80.10 GPa and modulus of 748.63 GPa, but a lower fracture strain of 15.02%. In contrast, the a-axis direction ([2-1-10]) shows a lower strength of 56.87 GPa and modulus of 570.74 GPa, but a higher fracture strain of 17.71%. From 300 to 900 K, the mechanical properties decrease nearly linearly, while more than 73% of the 300 K strength is retained at 900 K. Fracture occurs without observable dislocation activity and is governed by cleavage-plane selection: {10-10} prismatic planes under a-axis tension and the (0001) basal plane under c-axis tension. Atomic displacement analysis shows that local separation and microvoid formation precede macroscopic crack growth, indicating a brittle fracture process driven by local bond-network instability. These results provide atomic-scale mechanical data for assessing the reliability of theta-TaN in thermal management applications.
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Materials Science

Beyond Hexagonal Boron Nitride: First-Principles Study of Pentaoctite-BN and Pop-BN Monolayers

Victor M. S. da Conceição, Erika N. Lima, Roberto H. Miwa et al. (+1 more)

We investigate two novel non-hexagonal boron nitride monolayers, pentaoctite-BN (PO-BN) and pop-BN (PP-BN), using first-principles calculations. Their structural, electronic, mechanical, vibrational, thermal, and optical properties are systematically analyzed to assess their stability and potential applications. Despite being metastable with respect to hexagonal BN, both polymorphs satisfy the criteria for dynamical, mechanical, and thermal stability, indicating that they are viable two-dimensional materials. Both systems are indirect-gap semiconductors whose electronic states near the band edges are dominated by out-of-plane pz orbitals. Their distinct pentagon-octagon ring networks also give rise to different in-plane elastic anisotropies. Many-body optical calculations reveal strong excitonic effects and pronounced polarization-dependent optical absorption, with lattice engineering shifting the optical response from the ultraviolet toward the visible and infrared regions. These findings demonstrate that engineering non-hexagonal lattice architectures provides an effective strategy for tuning the electronic and optical properties of two-dimensional BN, highlighting PO-BN and PP-BN as promising candidates for future optoelectronic and photonic applications.
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All authors Victor M. S. da Conceição, Erika N. Lima, Roberto H. Miwa, Igor S. S. de Oliveira

Wednesday 29 July

Materials Science · Cross-listed from physics.med-ph

Dual-Mode SERS and Colorimetric Sensor for Lung Cancer VOC-Biomarker Detection Using Hydrogel Patches

Jialin Li, Shaowei Liu, Amil Aligayev et al. (+7 more)

Hexanal, a volatile organic compound (VOC), is a potential biomarker for the early detection of lung cancer. In this study, we developed a dual-mode flexible biosensor that integrates surface-enhanced Raman scattering (SERS) and colorimetric detection for the quantitative analysis of hexanal in human exhaled breath. The biosensor employs Ag nanocubes wrapped with Co-Ni layered double hydroxide (AgNCs@Co-Ni LDH) as a functional matrix, offering both superior SERS enhancement and efficient VOC adsorption properties. To achieve selective detection, AgNCs@Co-Ni LDH were incorporated into agarose hydrogels along with 3-methyl-2-benzothiazolinone hydrazone (MBTH). The resulting MBTH-AgNCs@Co-Ni LDH/hydrogel-patch facilitate the oxidation of hexanal, enabling simultaneous colorimetric and SERS signal generation, while producing acrizine, a blue-colored reaction product. This hydrogel-based dual-mode sensing platform exhibits high selectivity, excellent stability, and precision in SERS-based hexanal detection. The detection limit for the SERS method was determined to be as low as 3.34x10-13 M. Furthermore, developed and optimized compact CNN-based multi-terminal intelligent recognition system for enhanced hydrogel-patch detection through AI-driven, portable, and real-time colorimetric analysis. Therefore, this work not only enables the effective detection of hexanal in the exhaled breath of suspected lung cancer patients, underscoring its potential for early lung cancer screening, but also establishes a foundation for the development of multimodal hydrogel biosensors for broader applications in disease diagnosis.
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All authors Jialin Li, Shaowei Liu, Amil Aligayev, Hao Jiang, Muhammad, Xin Yu, Jin Tao, Jiaqi Wang, Agnieszka Jastrzębska, Qing Huang

Materials Science · Cross-listed from cond-mat.soft

Design principles for energy dissipation in viscoelastic network metamaterials

Niranjan Sarpangala, Sean Fancher, Prashant K. Purohit et al. (+1 more)

Mechanical energy dissipation in networked materials is relevant for applications from vibration isolation to impact protection, yet identifying optimal dissipative architectures in large disordered truss networks is computationally prohibitive with conventional finite element methods. We develop an efficient graph Laplacian-based spectral framework for viscoelastic truss networks, in which the full continuum dynamics of each rod are retained exactly and the problem size scales with the number of joints rather than element-level discretization points. Using this framework, we investigate how redistributing cross-sectional areas within a network (without changing material composition) controls energy dissipation. We find that random redistribution typically reduces dissipation relative to a uniform baseline, while gradient-based optimization yields nontrivial architectures whose form is governed by the intrinsic attenuation length of the base material. Focusing on driving frequencies near a global resonant mode of the network, we show that the optimal mass distribution decays from the source (driven joint) with the attenuation length scale, and at small attenuation lengths the optimal architecture is independent of the boundary conditions. These results motivate future studies of dissipation length scale based design principles on more complex disordered architectures and provide an efficient computational framework for exploring such structures at scale.
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All authors Niranjan Sarpangala, Sean Fancher, Prashant K. Purohit, Eleni Katifori

Materials Science

Temperature-doping phase diagram and endurance in Ce-doped HfO2

Amit Kumar Shah, Haidong Lu, Kawshan Hathurusingha et al. (+2 more)

The structural and ferroelectric properties of epitaxial Hf1-xCexO2 (CHO) thin films in the ultrathin regime are investigated as a function of Ce concentration (5% <= x <= 20%) and temperature. A temperature-doping phase diagram is established for 10 nm films, showing a systematic evolution from the ferroelectric orthorhombic phase to tetragonal and cubic phases with increasing Ce content. The orthorhombic-tetragonal transition temperature decreases from ~800{\deg}C at x = 5% to $~300{\deg}C$ at x = 15%, indicating strong stabilization of higher-symmetry phases with doping. Consistently, the remanent polarization decreases from ~15 to $3.8 {\mu}C/cm2$ as x increases from 5% to 20%. In contrast, the endurance improves significantly, with higher Ce concentrations exhibiting markedly enhanced cycling stability up to 108 cycles. The opposing trends of polarization and endurance are correlated with reduced orthorhombic distortion, suggesting that fatigue mitigation in Ce-doped HfO2 is linked to structural evolution. These results provide a framework for optimizing composition and reliability in ultrathin ferroelectric HfO2 devices.
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All authors Amit Kumar Shah, Haidong Lu, Kawshan Hathurusingha, Alexei Gruverman, Xiaoshan Xu

Materials Science · Cross-listed from cond-mat.soft

Phase transitions and microphases in elastomers. I. Emergence of stable domains

Manu Mannattil, Haim Diamant and David Andelman

Elasticity often plays a key role in regulating phase separation in physical systems. Recent experiments have shown that elastic effects can be used to control microphase separation in swollen elastomers. Here, microphase separation arises from a mismatch between the characteristic length scales of elastic and thermodynamic interactions. In this first part of a two-part paper, we show that microphase formation in elastomers can be explained using conventional theories of elasticity through a nonlocal thermodynamic-elastic coupling arising from volume conservation. Our theory reproduces the observed dependence of phase transition temperature and domain size on elastomer stiffness in isotropically swollen elastomers. In the companion paper, we investigate the effects of anisotropic swelling and inhomogeneous elastic moduli.
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Materials Science

Topology of Shape and Data in Material Microstructures

Jeanie Schreiber, Zachary Grey and Adam Creuziger

One of the challenges in microstructure analysis is the rigorous quantification of the shape, size, and spatial arrangement of the microstructure beyond comparison of average values. We expound on formal principles combining Topological Data Analysis (TDA) and non-Euclidean distances between curves to motivate novel perspectives on the form and nature of pattern and shape in images. Specifically, TDA descriptors extracting persistent topological structures are combined with product submanifold learning of separable shape tensors (SST) to offer unique insights about electron backscatter diffraction (EBSD) images of material microstructures through the lens of a dual-parameter filtration. Beyond standard approaches, our methodology highlights how different choices or permutations of shape distances can lead to distinct notions of topological persistence, thereby broadening the interpretive scope of TDA. The resulting visualizations of feature extraction are designed to be both principled and explanatory, offering novel tools for modern imaging science with applications to material metrology. More broadly, this framework has strong potential to impact domains where precise quantification of topology and shape is critical for uncovering fundamental image patterns and features, and enables additional data-driven tools for microstructure analysis.
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Materials Science

Dynamics of Null and Electrostatic Blind Spots for Quantitative PFM

Marti Checa, Holland Swicegood, Ruben Millan-Solsona et al. (+5 more)

Piezoresponse force microscopy is a cornerstone technique for probing nanoscale electromechanical phenomena, yet quantitative and in some cases qualitative interpretation remains hindered by parasitic electrostatic forces coupled through cantilever dynamics. Recent approaches aim to suppress these artifacts by operating at resonance defined null spots or electrostatic blind spots, but whether these conditions are equivalent and how they evolve under realistic measurement conditions has remained unclear. Here, combining analytical beam models, geometrically faithful finite-element simulations, and automated interferometric measurements, we show that NS and ESBS are fundamentally different operating conditions. The NS is a modal zero at contact resonance where sensitivity to all excitations vanishes, whereas the ESBS is a quasistatic position where only the distributed electrostatic response is suppressed. Automated measurements reveal that both conditions evolve with the tip sample boundary condition yet remain spatially separated under realistic experimental conditions. While beam models capture the dominant cantilever mechanics, finite-element simulations and experiment show that quantitative prediction of near tip behavior requires realistic three dimensional probe electrostatics and mechanics. These findings establish NS and ESBS as dynamic operating conditions and provide a practical framework for advancing interferometric PFM toward truly quantitative electromechanical metrology.
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All authors Marti Checa, Holland Swicegood, Ruben Millan-Solsona, Ralph Bulanadi, Jerry Zhao, Jack Lasseter, Stephen Jesse, Liam Collins

Materials Science

Decoding the Micromagnetic Hamiltonian from Magnetic Fingerprints

Bradley J. Fugetta, Anqi Liu, Kai Liu et al. (+2 more)

Extracting intrinsic magnetic Hamiltonians directly from magnetometry is challenging due to the high dimensionality of the parameter space and the degeneracy induced by ensemble averaging. Here, we introduce a collection of deep convolutional neural networks (CNNs) to extract the full phenomenological micromagnetic Hamiltonian directly from the magnetic fingerprints encoded within First-Order Reversal Curves (FORCs). We validate this approach via closed-loop verification, re-creating the input magnetometry for both simulated and experimental FORCs. To mitigate false positives, we deploy an `Alice–Bob' parallel network that quantifies prediction uncertainty based on solely the information in FORCs without any additional ground-truth knowledge. This framework provides a robust, machine-learning-assisted approach to unravel the underlying spin behaviors in complex magnetic systems
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All authors Bradley J. Fugetta, Anqi Liu, Kai Liu, Amy Y. Liu, Gen Yin

Materials Science

Structure and thermodynamic stability of $\beta$-Ga$_2$O$_3$ surfaces

Konstantin Lion and Claudia Draxl

We present a comprehensive first-principles investigation of all symmetrically inequivalent low-index surfaces of $\beta$-Ga$_2$O$_3$, examining their structural properties and thermodynamic stability across experimentally relevant growth conditions. Using density-functional theory with both the semi-local functional PBEsol and a modified PBE0 hybrid functional with 26% exact exchange, denoted PBE0(0.26), we calculate surface free energies for the (010), (100), (001), ($\bar{2}01$), (110), (111), and ($11\bar{1}$) orientations, including the effects of harmonic vibrational contributions and varying oxygen chemical potentials. We demonstrate that the energetic ordering remains consistent across computational approaches and that the vibrational contributions remain below 0.2 J/m$^2$ up to temperatures of 1000 K. A coordination-based model that correlates surface stability with the density of under-coordinated atoms reveals that under-coordinated oxygen atoms and tetrahedral Ga sites substantially destabilize surfaces, while exposed under-coordinated octahedral Ga atoms serve as indicators of surface stability. Our thermodynamic analysis shows that stoichiometric terminations dominate over nearly the entire range of chemical potentials relevant for $\beta$-Ga$_2$O$_3$ stability, while non-stoichiometric terminations emerge only under extreme reducing or oxidizing conditions. Notably, we predict the formation of stable Ga-rich terminations resembling Ga adlayers for the (100) and ($\bar{2}01$) surfaces under highly reducing conditions.
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Materials Science

Optimization of Epitaxial Mn4N Thin Films Grown by Sputtering for Spintronic Applications

Teodor Apetrei, Emre Demiroglu, Caner Deger et al. (+2 more)

Ferrimagnetic Mn4N has recently emerged as a promising rare-earth-free platform for spintronic devices due to its low magnetization, high domain wall mobility, and strong anomalous Hall response. However, the realization of thin films with robust perpendicular magnetic anisotropy (PMA) and spin-orbit torque (SOT) functionality through scalable deposition techniques remains a significant challenge. In this work, we systematically investigate the growth of Mn4N thin films by reactive magnetron sputtering and determine the conditions required to achieve high-quality films suitable for SOT applications. We demonstrate that epitaxial, single-crystalline Mn4N films with strong PMA can be obtained on MgO(100), whereas films deposited on SrTiO3(100) exhibit a textured structure. The optimized films show square-shaped hysteresis loops with high remanence, large and tunable coercivity, and a pronounced anomalous Hall effect. By combining structural, magnetic, and magnetotransport characterization with density functional theory calculations, we reveal that epitaxial strain plays a key role in tuning magnetic anisotropy, while also showing that it is not the only contributing factor. In particular, our results emphasize the importance of interfacial effects in stabilizing PMA. Finally, we demonstrate efficient current-induced magnetization switching in Mn4N/Pt bilayers, confirming strong interfacial spin transparency. These findings establish sputtered Mn4N as a promising and versatile material platform for energy-efficient spin-orbitronic devices.
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All authors Teodor Apetrei, Emre Demiroglu, Caner Deger, Can Onur Avci, Silvia Damerio

Materials Science

PEDOT:PSS-Coated Magnetoelastic Sensors for Highly Sensitive Wireless Humidity Sensing

Wenderson R. F. Silva, Robson C. O. Guedes, Gilberto Rodrigues-Junior et al. (+3 more)

Magnetoelastic (ME) resonators provide an attractive platform for passive and wireless sensing, particularly for monitoring relative humidity (RH) in sealed or hard-to-access environments. In this work, we introduce ME humidity sensors functionalized with poly(3,4-ethylenedioxythiophene) sulfonate (PEDOT), marking the first application of this conductive polymer in ME-based humidity sensing. PEDOT films were deposited onto Metglas resonators via a simple drop-casting process, producing uniform and mechanically stable coatings. Comprehensive structural and morphological characterization by SEM, EDX, Raman spectroscopy, AFM/KPFM, and XRD confirmed the structural integrity of the polymer and revealed humidity-induced swelling of the PSS-rich domains, accompanied by enhanced polymer-chain mobility and an increase in the lamellar spacing from 23.5 Å to 24.2 Å at 95% RH. These structural changes directly affected the dynamic response of the resonators, leading to a systematic resonance-frequency downshift driven by the combined effects of water adsorption, mass loading, and viscoelastic damping. The optimized device achieved a sensitivity of 155 Hz/% RH in the 20 - 70% RH range, outperforming previously reported ME humidity sensors, while exhibiting a resolution better than 0.1% RH together with excellent response and recovery times. These results establish PEDOT as a highly effective functional coating for magnetoelastic humidity sensors and demonstrate a simple, low-cost, wireless sensing platform with high sensitivity and strong potential for practical environmental and industrial monitoring applications.
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All authors Wenderson R. F. Silva, Robson C. O. Guedes, Gilberto Rodrigues-Junior, Eduarda P. M. Campos, Angelo Malachias, Joaquim B. S. Mendes

Materials Science · Cross-listed from cond-mat.str-el

Excited state optimization for strongly correlated quantum defects using ensemble variational Monte Carlo

Kevin G. Kleiner and Lucas K. Wagner

Using the recently introduced ensemble variational Monte Carlo (VMC), we study optimized wave functions for strongly correlated point defects, including nitrogen-vacancy and silicon-vacancy centers in diamond and substitutional iron and chromium impurities in aluminum nitride. We study the effects of fully optimized determinant expansion parameters, orbitals, and Jastrow correlation factors on these systems. We find that orbitals from the hybrid functional PBE0 are much better (have lower objective functional) than semilocal PBE, which results in changes in the excitation energies up to 0.5 eV. Further improvements can be made by directly optimizing the objective functional, resulting in changes in excitation energies up to 0.2 eV. The most important parameter varies from defect to defect, reinforcing the necessity of optimizing all parameters to obtain accurate excited states in strongly correlated defects.
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Materials Science

Evolution of Irradiation-Induced Defect Landscape through Edge Dislocation and Vacancy Loop Interactions in Tungsten

Soumya Mishra and Suchandrima Das

Structural materials in fusion reactors develop irradiation-induced defect populations that govern their mechanical behaviour. While advanced microscopy provides detailed characterisation of such defects, their dynamic evolution through dislocation-defect interactions during plastic deformation remains unresolved. Here, we address this gap using molecular dynamics simulations to resolve dislocation-defect interaction mechanisms and the resulting evolution of defect morphology and obstacle strength. Tungsten is the leading candidate plasma-facing material for fusion reactors, where vacancy loops are common irradiation defects. Using vacancy loops as a prototype defect, we systematically investigate their interactions with edge dislocations by varying loop size, orientation, and dislocation-loop intersection position. Parallel loops exhibit three distinct evolution pathways: complete annihilation, transformation into weaker remnant defects, or defect transport, depending on the intersection position and loop size. In contrast, inclined closed loops undergo dislocation reactions that produce sessile $\langle010\rangle$ dislocation segments, leading to substantially higher obstacle strengths with little sensitivity to the intersection position. Repeated dislocation interactions further demonstrate that the defect landscape is not static: remnant defects can persist, transform, or lose their ability to impede subsequent dislocations, depending on the preceding interaction mechanism. These results show that the obstacle strength of a vacancy loop is governed not only by its initial size and orientation, but also by its interaction history and the resulting defect structure.
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Materials Science

Machine Learning for Designing Undesignable Metal-Organic Frameworks

Satya Kokonda

Many crucial processes are too complex for computational modeling, requiring experimentation to identify promising materials. Here, a methodology for material design is presented, while photocatalysis is presented as a specific case-study. Metal-Organic Frameworks (MOFs) are a subset of highly promising porous nanomaterials, used in a variety of unmodellable applications. Reinforcement learning generated 60,000 novel MOFs optimized for CO/H20 selectivity. A predictor funnel system was created, iteratively removing low-scoring MOFs to 10,986 potential candidates, improving computational efficiency by 276%. While trained Crystal Graph Convolutional Neural Network (CGCNN) models predicted features for creating a fitness function incorporating stability, catalytic ability, material cost, sustainability, and adsorption while allowing the inclusion of application specific design criterion. This designed function provides a computational method to model photocatalytic performance- and filtered down to two promising MOFs which each pass a myriad of synthesis criteria, first a Cr-based MOF with photocatalyst score 230% higher than the control. Second, a Zn-based MOF outperforms the best control across all relevant metrics, demonstrating robustness against variable fitness functions. This work designed 20 materials, each 125% better than the control for this application. Furthermore, analysis revealed insightful design patterns, such as the significant influence of metal cluster N262 on catalytic performance, providing a method for future work to narrow the chemical space. By incorporating industrially applicable features such as cost or stability of the material, this work successfully designs industrially promising materials in otherwise unmodellable processes such as drug delivery, while paving a method for multi-objective optimization incorporating 260% more features than prior work.
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Materials Science

Parity-selective spin splitting in coplanar antiferromagnets via bichromatic driving

Di Zhu, Zhongbo Yan and Mohsen Yarmohammadi

Parity is a central characteristic of momentum-dependent spin splitting in antiferromagnets (AFMs). Yet, intrinsic crystal symmetries typically restrict the splitting to either even or odd parity, preventing flexible spin control. Using a coplanar AFM, we demonstrate that bichromatic ($\omega$–$n\omega$) Floquet driving offers a natural way to bypass this constraint. This mechanism generates asymmetric spin textures unattainable in static AFMs or under monochromatic driving. For the specific AFM considered here, we reveal an elegant relation between spin-splitting parity and harmonic hierarchy: $\omega$–$2\omega$ fields generate highly tunable odd- and mixed-parity spin splittings, whereas higher-order harmonics ($n \ge 3$) exclusively produce even-parity states. The macroscopic magnetization can also be toggled via the specific driving protocol and harmonic $n$. These distinct spin splitting states manifest in qualitatively different macroscopic spin currents generated after an optical quench—a definitive transport signature complementing direct visualization via spin- and angle-resolved photoemission spectroscopy.
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Materials Science · Cross-listed from cond-mat.mes-hall

Harnessing Native Chromium Oxidation for Giant Orbital Torque and Field-Free Magnetization Switching in NiFe/Cr Bilayers

Chirag Kalouni, Abhishek Kumar, Manish Kumar Mohanta et al. (+6 more)

Orbital currents offer charge-to-spin conversion beyond the efficiency limit of conventional heavy-metal Spin Hall sources. However, harnessing them has so far required either thick orbital-Hall materials or additional heavy-metal conversion layers. Here, we show that the native oxide of chromium, typically regarded as parasitic, transforms a simple NiFe\Cr bilayer into a self-contained dual-channel orbital-current source without the need for any conversion layer. First-principles calculations predict a nearly threefold enhancement of the orbital Hall conductivity upon surface oxygenation, driven by Cr(3d)-O(2p) hybridization. Experimentally, naturally oxidized NiFe\Cr heterostructures exhibit a giant damping-like torque efficiency of $3.9 \times 10^{6}$ $\Omega^{-1}$ m$^{-1}$, exceeding Pt (Ta) by one (two) orders of magnitude. The torque depicts a non-monotonic Cr-thickness dependence which cannot be explained by a conventional model. We have developed a drift-diffusion model with an oxidation-gated interfacial source which quantitatively reproduces the data, revealing that the Cr-CrO$_x$ interface generates orbital currents over an order of magnitude stronger than the bulk orbital Hall channel with an orbital transport length of $\approx 4$ nm. The enhanced torque enables field-free magnetization switching at $1.58 \times 10^{11}$ A m$^{-2}$, outperforming heavy-metal and CuO$_x$ benchmarks. These results establish native oxidation as a scalable strategy for realizing efficient orbital-torque devices.
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All authors Chirag Kalouni, Abhishek Kumar, Manish Kumar Mohanta, Kanupriya, Athira Ravindran K, Damanpreet Kaur, Preet Kamal, Puru Jena, Debangsu Roy

Materials Science

MatCreatioNN: Machine learning-guided computational discovery of photocatalysts for environmental applications

Satya Kokonda

The rational design of photocatalysts for environmental remediation and CO2 conversion remains limited by the high computational cost and sparse experimental data describing multi-parameter photocatalytic behavior. This work presents an integrated machine-learning framework that couples reinforcement learning-based metal-organic framework (MOF) generation with a multi-stage Crystal Graph Convolutional Neural Network (CGCNN) prediction funnel to identify photocatalysts optimized across multiple electronic and structural features. 120,000 MOF candidates were generated and screened using 13 key descriptors, including band-gap suitability, CO2/H2O selectivity, adsorption energy, and structural stability. The funnel approach reduced computational cost by 4.13-fold while maintaining predictive robustness. Two top candidates, a Cr-based and a Zn-based MOF, exhibited predicted photocatalytic fitness values of 1.70 +/- 0.25 and 1.20 +/- 0.05 fold higher respectively than benchmark materials such as PCN-224(Zr), demonstrating simultaneous improvements in light absorption, redox energetics, and framework durability. Simulated X-ray diffraction patterns confirmed strong structural agreement with experimentally synthesized MOFs, indicating high synthesizability. Post-hoc analysis revealed recurring structural motifs, such as the N262 metal cluster, that correlated strongly with high predicted photocatalytic activity. These results highlight the potential of data-driven methods to accelerate discovery of efficient and durable photocatalysts for environmental and energy-related transformations, providing a foundation for experimental realization and large-scale implementation of computationally designed MOFs.
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Materials Science · Cross-listed from cond-mat.mes-hall

Magnetic Breakdown and Anomalous Quantum Oscillation in Rhombohedral Tetralayer Graphene

Jing-Yu Zhao, Yang-Zhi Chou and Sankar Das Sarma

We investigate magnetic breakdown near Van Hove singularities (VHSs) in the electron-doped rhombohedral tetralayer graphene, where chiral superconductivity has recently been reported. Using the noninteracting band structure and Kubo formula, we identify anomalous Shubnikov-de Haas effects: Ring-like structures in the Landau fan and anomalous high-frequency peaks in the frequency spectra. These anomalous quantum oscillations can be understood by the reconstruction from magnetic breakdown among three nearby Fermi pockets separated by VHSs. Remarkably, these qualitative anomalous features persist into a stronger-VHS regime, where the semiclassical picture breaks down. The temperature and (weak) disorder dependence of the oscillations are also investigated. Our results establish that the magnetic-breakdown-induced anomalous quantum oscillation provides a general distinctive probe for the underlying Fermi-surface geometry associated with VHSs and may explain the recent quantum oscillation experiment in rhombohedral tetralayer graphene [arXiv:2606.05356].
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