AI for Science

Scalable prediction of optical spectra is a critical component of high-throughput materials screening for optoelectronic applications such as solar cells. Existing surrogate models are trained on spectra computed from lower levels of theory or rely on rotation-invariant scalar features, limiting their geometric expressiveness. We explore the use of equivariant graph neural networks for optical spectra prediction, adapting GotenNet to this task and evaluating it on multiple datasets including a recently published collection of 10,533 structures with spectra computed at the level of the random phase approximation (RPA). The proposed model outperforms the current state of the art, with the largest gains in the 0-8 eV range and on predicting the static real permittivity, both of particular relevance for thin-film optics.

Pre-trained materials foundation models, or machine learning interatomic potentials, leverage general physicochemical knowledge to effectively approximate potential energy surfaces. However, they often require domain-specific calibration due to physicochemical diversity as well as mismatches between practical computational settings and those used in constructing the pre-training data. To address this, we propose a sparsity-promoting fine-tuning method that selectively updates model parameters by exploiting the structural properties of E(3)-equivariant materials foundation models. On energy and force prediction tasks across molecular and crystalline benchmarks, our method matches or surpasses full fine-tuning and equivariant low-rank adaptation while updating only $\sim$3~\% of parameters, and in some cases as little as $\sim$0.5~\%. Beyond energy and force calibration, we further demonstrate task generalizability by applying our method to magnetic moment prediction and magnetism-aware total energy modeling. Finally, analysis of sparsity patterns reveals physically interpretable signatures, such as enhanced $d$-orbital contributions in transition metal systems. Overall, our results establish sparsity-promoting fine-tuning as a flexible and interpretable method for domain specialization of equivariant materials foundation models.

Ni-based structural alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni$_{0.75}$Cr$_{0.25}$ exposed to molten FLiNaK at 800$^\circ$C. A $\Sigma5(210)$ grain boundary model is subjected to tensile (+4%) to compressive (-4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary evolution. Tensile strain accelerates intergranular corrosion by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain suppresses corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.

Colloidal quantum dots that simultaneously offer room-temperature single-photon purity and high photoluminescence quantum yield are sought for quantum optics, but remain elusive in environmentally benign materials. We introduce a thermodynamic-kinetic decoupling strategy that transforms defect-tolerant CuInS2 quantum dots into bright, narrowband, and photostable single-photon emitters. Zn2+ alloying strains the lattice, thermodynamically suppressing native copper vacancies and narrowing the emission from a broad defect band of approximately 300 meV to an excitonic line of approximately 120 meV. Ga3+ incorporation then kinetically pins the cation sublattice against Cu+ migration, preventing defect regeneration during ZnS shell growth. The resulting Cd-free core/shell dots achieve near-unity quantum yield of approximately 98% while retaining narrow excitonic emission. Critically, room-temperature single-dot spectroscopy reveals homogeneous linewidths as low as approximately 58 meV, strongly suppressed blinking, and high-purity single-photon emission with g2(0) = 0.06. This stabilized excitonic emission directly reduces reabsorption losses in luminescent solar concentrators, yielding an external optical efficiency of 12.68%. Our work establishes a generalizable framework to unlock intrinsic excitonic photophysics in ion-mobile, defect-prone semiconductors, opening a viable path toward high-performance heavy-metal-free emitters for quantum light sources.

A comprehensive study of the possible types of non-relativistic spin splitting of electronic bands in coplanar and non-coplanar magnetic structures is presented on the basis of spin-group theory. First, we tabulate all non-equivalent spin point groups (SpPGs) which can be expressed as a direct product of a nontrivial part and a spin-only group limited to be the intrinsic (trivial) one, or augmented by the time-reversal (TR) operation. This tabulation, which includes the listing of symmetry operations for 1249 nonequivalent SpPGs, is now available as an online database SPGENPOS in the Bilbao Crystallographic Server (BCS). This extends previous enumerations, in which the possible presence of TR in the magnetic point group was not taken into account, thus overlooking the full SpPG symmetry associated with the numerous magnetic structures which have a magnetic space group of type IV. For each of the listed coplanar and non-coplanar SpPGs, the spin-splitting that is symmetry allowed is analyzed in detail using the program STENSOR also in the BCS. Except for the SpPGs that include the operation 1', i.e., the combined operation of TR and space inversion, all other coplanar and non-coplanar SpPGs allow spin splitting at some order in a power expansion of the electron wave vector components. We find that, depending on the SpPG, spin-splitting terms can appear with the lowest-order monomials ranging from l=0 to 9, with the exception of l=8. This contrasts with the collinear case, where the lowest order is not higher than l=6, and where TR forbids any spin splitting. For the newly identified spin textures with powers l=5, 7, and 9, which are possible in some noncentrosymmetric SpPGs, the functional form of the spin splitting in terms of the components of the crystal momentum is given. One example of a real material, LaMnAu5, showing l=5 spin splitting is identified.

Accurate predictions of exfoliation energies and lattice constants of layered materials hinge on a correct description of London dispersion physics. Modern a posteriori dispersion corrections in density-functional theory (DFT), such as the exchange-hole dipole moment (XDM) model, capture the proper asymptotic behaviour at long range while making use of damping functions to prevent unphysical divergence at short range. In the united-atom limit, the dispersion energy is damped to a finite, non-zero value by both the canonical Becke--Johnson (BJ) damping function and the new Z-damping function. XDM(BJ) has previously demonstrated exceptional accuracy for modelling layered materials, such as in the LM26 benchmark, which includes graphite, hexagonal boron nitride, lead(II) oxide, and transition-metal dichalcogenides. This work presents the first assessment of XDM(Z) on the same benchmark. We also show that inclusion of three-body interactions via the Axilrod--Teller--Muto (ATM) term further improves the computed exfoliation energies for both XDM(BJ) and XDM(Z), yielding the best performance achieved on LM26 using semi-local functionals to date, relative to reference data from the random-phase approximation.

Density-functional theory (DFT) has become the workhorse of modern computational chemistry, with dispersion corrections such as the exchange-hole dipole moment (XDM) model playing a key role in high-accuracy modelling of large-scale systems. All previous production implementations of XDM have used the two-parameter Becke--Johnson damping function based on atomic radii. Here, we introduce and implement a new XDM variant that uses a one-parameter damping function based on atomic numbers, recently proposed by Becke. Both this new Z damping and the canonical BJ-damping variants of XDM are benchmarked on the comprehensive GMTKN55 database using minimally empirical generalised-gradient-approximation, global hybrid, and range-separated hybrid functionals. This marks the first time that the XDM (and many-body dispersion, MBD) corrections have been tested on the GMTKN55 set. Using the new WTMAD-4 metric, an outlier analysis is performed for all new data, as well as for top-ranking functionals from the literature at each rung, providing insight into both performance and consistency across the dataset. We also extended our analysis to the DM21 and Skala machine-learned functionals that have garnered recent attention. To test Z damping's transferability to the solid state, four benchmarks involving molecular crystals are also considered. Across these molecular and solid-state benchmarks, the revPBE0 and B86bPBE0 hybrid functionals, paired with the Z-damped XDM variant, show excellent performance.

Developing intrinsic homojunctions without chemical heterogeneity remains a key challenge in future two - dimensional devices. Here, we report a geometry - defined metal--semiconductor--metal homojunction in bilayer blue phosphorus (BlueP) created by a localized bubble corrugation, without chemical doping or foreign - material interfaces. First - principles calculations show that enlarging the interlayer separation in the metallic A\(_1\)B\(_1\) - stacked BlueP bilayer opens a band gap, enabling a semiconducting barrier embedded between metallic segments. First - principles quantum - transport simulations reveal a crossover from ballistic to tunneling transport upon bubble formation. In the tunneling regime, transmission decreases exponentially with bubble width while remaining weakly sensitive to bubble height and bulging direction. The junction acts as an orientation - dependent \(k\) - space filter, producing transport anisotropy and momentum selectivity. Orbital - resolved scattering analysis shows that intralayer - bonding channels persist under deformation whereas interlayer - hybridized channels are quenched, and that σ- type bonding yields higher conductance than π- type bonding. These insights motivate two electromechanical device concepts: a mechanically switchable memory element with ON/OFF ratios up to 30 and a nanoscale sliding rheostat with reproducible exponential resistance tuning for Å- scale displacement sensing.

The compaction mechanisms of SiO2 glass under pressure include under certain conditions a specific reduction of the elastic moduli and a complex inelastic behavior whose nature is not yet fully understood. In our work we establish a variational framework describing the evolution of SiO2 glass under hydrostatic pressure. Based on a previous work that presents a model for multi-phase transformations in inelastic materials, we assume isothermal conditions during a compaction process and interpret the typical sigmoidal stress response as indicator of a binary phase transformation. During the process, two volume fractions coexist macroscopically and microstructures such as shear bands or disclination pattern develop in between. We restrict our approach to resolve only the volume fractions, not the corresponding microstructures. Nevertheless, the resulting model is shown to match experimental findings very well. Numerical examples successfully illustrate the relationship between the changes in the elastic moduli and the corresponding change in volume with respect to pressure.

Two-dimensional electronic spectroscopy (2DES) offers unique insights into the coupling between electronic and nuclear motion and dynamics, making it a key technique in diverse fields, including materials science and biology. Obtaining 2DES data requires a series of measurements that involve multiple pulses to construct the full picture - a time-consuming task that often necessitates working with limited or noisy data. Here we introduce a machine-learning based framework that aims to maximize the data that can be extracted from 2DES experiments and provides guidance towards the selection of additional experiments. We design a Gaussian mixture model to learn the underlying spectral density of a system, allowing the extraction of vibronic couplings and the extrapolation of the 2DES spectra to other time delays beyond those measured, and demonstrate how our framework can be used to select additional measurements to further improve the accuracy. We show that our approach yields accurate results on a variety of systems, including simulations ranging from photoactive yellow protein in the gas phase to Nile red in benzene to the anionic green fluorescent protein chromophore in water, and experiments on Nile blue in ethanol. Our work provides an efficient route to extract maximum insights from 2DES while incurring minimal experimental costs.

This paper introduces a comprehensive two-dimensional analytical model of a toroidal magnetic ring with circular cross-section under sinusoidal excitation. Applying Maxwell's equations in local polar coordinates within a complex permeability, the model derives analytical expressions for the internal magnetic field, magnetic flux, complex impedance, and total losses. It rigorously separates the contributions of eddy current losses, hysteresis losses, and winding losses, while explicitly incorporating the skin effect in the conductive core via Bessel functions. An expression for the apparent permeability is also provided, enabling the nonlinear core behavior to be mapped onto simplified linear material models. The resulting analytical model offers a computationally efficient and accurate foundation for standardized magnetic material characterization, such as Brockhaus and Iwatsu ring measurements, as a powerful alternative to 2D and 3D finite element analysis.

The chirality-induced spin selectivity (CISS) effect, discovered by Naaman and collaborators in 1999, describes the emergence of a finite spin polarization in response to current flow through a chiral electronic system. While extensive experimental studies have verified the presence of CISS in molecular systems and, more recently, in chiral materials, a complete microscopic understanding of this effect remains elusive. In this work, we propose a theoretical framework linking the CISS effect to the orbital Edelstein effect. In the latter, a drive current induces a finite orbital magnetization, even in the absence of spin-orbit coupling. Our non-equilibrium theory naturally explains key features of the CISS effect: its persistence in systems with weak or vanishingly small spin-orbit coupling and its connection to natural optical activity, a distinctive signature of chiral systems.

Identifying the lowest-energy surface-adsorbate configuration is critical for modeling heterogeneous catalysis, yet exhaustive exploration with ab initio calculations is computationally prohibitive. Machine-learning force fields (MLFFs) accelerate structural relaxation but leave the search over the vast configurational space a major bottleneck, and open-loop large language model (LLM) agents lack a physics-grounded feedback mechanism to correct erroneous initial guesses. We propose AdsMind (Adsorption configuration discovery with Machine intelligence and relaxation feedback), a closed-loop multi-agent framework that enables autonomous error correction through MLFF relaxation feedback. Across four LLM backends, AdsMind achieves consistently high search reliability, with success rates of 100% and 98.8% on the benchmarks AA20 and OCD-GMAE62. Relative to its single-pass (1-Shot) ablation it reduces cross-backend energy dispersion, and it uses only 4.11 and 4.67 MLFF relaxations per case, respectively -- an approximately 14-fold reduction over heuristic enumeration baselines. Density functional theory (DFT) validation using VASP/PBE on six representative AA20 systems shows that the reported open-loop Adsorb-Agent outputs exhibit qualitative adsorption-energy sign errors for molecular adsorbates, whereas AdsMind preserves the correct sign in all tested cases with closer quantitative agreement. AdsMind thus delivers reliability, self-reflection, and interpretability simultaneously, supporting more DFT-informed autonomous chemistry workflows.

The ability to compute electron-phonon coupling from first principles, using density functional perturbation theory and interpolation techniques, has enabled predictive calculations of electronic transport coefficients in crystalline materials. However, these methods are still computationally expensive. Here we present two inexpensive methods to obtain thermoelectric transport properties of semiconductors using a small number of electron-phonon matrix elements calculated from first principles. The first method combines models for coupling of electrons with different phonon modes whose parameters are obtained from $\sim 10$ matrix elements per electronic band and phonon mode calculated from first principles. Within this method, we formulate the acoustic deformation potential model for arbitrary crystal symmetries and band extrema locations. The second method uses machine learning to interpolate $\sim 100$ electron-phonon matrix elements per electronic band and phonon mode on dense reciprocal space grids in the parts of the Brillouin zone relevant for transport. We apply both methods to two-dimensional MoS$_2$ and show very good agreement with the state-of-the-art method. The calculated thermoelectric properties also agree well with experiments. We find that the machine-learning method is more accurate and straightforward to implement compared to the model approach.

In this study, the structural, mechanical, electronic, optical, and thermoelectric properties of the novel lead-free halide double perovskite series beta2SnGeX6 (beta = K, Rb; X = Cl, Br, I) are systematically investigated using density functional theory (DFT). Calculated formation energies, Tolerance factors, and octahedral factors confirm that all six compounds exhibit robust thermodynamic stability within a highly symmetric cubic geometry. Mechanical analysis derived from elastic parameters characterizes the entire series as fundamentally ductile, ensuring high processing elasticity and resistance to micro-cracking during device manufacturing. Electronic band structures reveal direct bandgaps showing exceptional composition-dependent tunability from 1.44 eV down to 0.64 eV via progressive halogen substitution. The wide gap chloride variations are optimized for single-junction photovoltaic absorbers, while the narrower-gap bromide and iodide analogs show immense promise for tandem solar architectures and near-infrared photodetectors. Thermoelectrically, heavy constituent atoms introduce strong lattice anharmonicity and intense high-temperature Umklapp phonon scattering, significantly suppressing lattice thermal conductivity. Combined with low carrier effective masses that optimize electrical transport, the iodide compounds achieve higher power factors and outstanding dimensionless figures of merit (ZT = 2.4 for K2SnGeI6 at 1000 K). Ultimately, these lead-free double perovskite family emerges as an environmentally benign and versatile platform for next-generation green optoelectronics and solid-state waste-heat recovery.

Iron germanium telluride (FGT; FemGenTe2) compounds have attracted significant interest due to their layered van der Waals structure, relatively high Curie temperature, and tunable magnetic properties. Chemical vapor deposition (CVD) is a particularly promising synthesis route owing to its simplicity, low cost, potential for scalability, and widespread adoption in the semiconductor industry, yet it has not been used previously to synthesize FGT with dopants. Here, we report CVD synthesis of both undoped and Ni-doped FGT nanosheets on SiO2/Si substrates. By adjusting precursor molar ratios, we synthesized Ni-doped FGT with multiple Fe concentrations and a 4% Ni-to-Fe ratio. X-ray photoelectron spectroscopy depth profiling further demonstrates that Ni is present in the bulk of the crystals. This straightforward, low-cost, and CMOS-compatible approach demonstrates a route to Ni-doped FGT nanosheets, establishing a foundation for future characterization of Ni-doped FGT and its potential integration into spintronic devices.

Proton dissociation constants (pKa) are critical for functional molecule discovery and molecular modeling. Building on iBonD, the largest experimental pKa database established, we and other researchers have developed several methods including machine-learning-based empirical prediction and high-accuracy energy calculations. Despite this foundation, the rapid augmentation of high-quality pKa data remains fundamentally constrained. As part of this work, we performed large-scale regression-based pKa prediction on unlabeled molecular datasets using a collection of extensively optimized machine-learning models. The results indicate that, since the feature distributions of unlabeled molecular datasets, the pKa data distribution approximates normality, with extreme scarcity of tail-region samples. Although such augmentation is highly valuable for improving overall data availability and predictive modeling, it remains insufficient for efficiently discovering molecules with broad-spectrum pKa properties. To address this, we explore the targeted generation of molecules with sparse pKa properties from the vast chemical space. Given that traditional continuous latent space VAE-RNN methods for molecular generation suffer from insufficient stability and fail to demonstrate clear advantages in complementing sparse data, we design and implement a quantum-assisted sparse-pKa molecular generation. Feasibility is validated on a simulated quantum annealer, and superior extreme-value sampling is further achieved on physical coherent Ising machines (CIMs). (to be continued)

The GMTKN55 data set is a collection of standard benchmarks used in molecular quantum chemistry that spans small- and large-molecule thermochemistry, reaction barriers, and non-covalent interactions. Herein, we identify a flaw in the weighted mean absolute deviation (WTMAD) definitions commonly used to quantify performance of various electronic-structure methods for the GMTKN55 set, which under-weight some of its component benchmarks by orders of magnitude. A new WTMAD-4 metric is proposed, based on typical errors observed for a set of ten minimally empirical dispersion-corrected density-functional approximations (DFAs), ensuring fair treatment across all benchmarks. The performance of 115 DFAs is then reassessed using WTMAD-4 and we highlight a literature example where a DFA parametrised by minimising WTMAD-2 underperforms for benchmarks marginalised by that metric.

High-quality InAs quantum wells grown on InP are a promising platform for topological quantum information processing due to their large g-factor, strong Rashba spin-orbit interaction, and their compatibility with in-situ-deposited superconductors. In this work, we investigate InAs/InGaAs quantum wells grown on InP (001) wafers, focusing on how the layer structure and strain influence the electronic properties and surface morphology. By combining quantum transport measurements with atomic force microscopy, we show that the layer design predominantly affects the mobility anisotropy, which aligns well with the surface morphology. Surface characterization further reveals the mechanism of quantum well collapse when the layer thickness exceeds the strain limit. In addition, transport measurements demonstrate that quantum confinement has a clear impact on band nonparabolicity.

The relativistic spin-momentum locking has been proven in time-reversal-breaking classes of materials with zero net magnetization in the non-relativistic limit, such as altermagnets and other non-collinear magnets. Using density functional theory calculations, we aim to show relativistic spin-momentum locking in ferromagnets, focusing on a broad class of ferromagnetic materials with magnetic sites connected by rotational symmetry, and compare with fcc Ni. In SrRuO3, the antisymmetric exchange interaction produces a spin canting orthogonal to the easy axis, while in all other cases, spin canting is forbidden. Even when the canted magnetic moment in real space is forbidden, relativistic spin-momentum locking shows sizable contributions in k-space. Using prototypical ferromagnets such as orthorhombic SrRuO3, hexagonal CrTe and CrAs with the NiAs crystal structure, half-Heusler MnPtSb, and fcc Ni, we demonstrate that relativistic spin-momentum locking can generate strong effects in ferromagnets. Subdominant components of centrosymmetric ferro-magnetic materials with magnetic sites connected by rotational symmetry host spin-momentum locking similar to altermagnets, while noncentrosymmetric MnPtSb hosts relativistic p-wave due to the spin-orbit coupling. Fcc Ni shows a more complex behavior with a combination of two spin-momentum locking patterns characteristic of altermagnets. Because ferromagnets typically have larger bandwidths than altermagnets, they provide a promising platform for observing even-wave relativistic spin-momentum locking and associated emergent phenomena. From an application standpoint, relativistic spin-momentum locking governs symmetry-allowed spin Hall currents, spin photocurrents, and other momentum-dependent spin responses in k-space.

We report on a study of the interacting phase diagram of $3.65^\circ$-twisted WSe$_2$ at moiré hole filling $ν=1$, in which we find previously-overlooked types of magnetism. Specifically, in part of the phase diagram we obtain a magnetic order parameter which modulates in space with four different non-zero wave vectors, corresponding to the three $M$-points and one $K$-point of the moiré Brillouin zone. These multi-Q orders, which can be coplanar or non-coplanar, are continuous deformations of the $120^\circ$ spin-valley anti-ferromagnet (AFM), where the unit cell has expanded by a factor of four. Interestingly, we find that the multi-Q states are stabilized for experimentally relevant values of interaction strength and displacement field, and are accompanied by a softening of the spin fluctuations near the $M$-points of the moiré

Altermagnets exhibit momentum-dependent spin splitting without net magnetization, combining characteristics of both ferromagnets and antiferromagnets, making them highly interesting for spintronics applications. CrSb is a prime candidate with a high Néel temperature ($\sim700$~K) and a large exchange-driven splitting of $\sim0.6$--1~eV. Using ab-initio calculations, we consider slabs of various orientations in the ultrathin limit. We find that (100) oriented slabs have spin-degenerate bands. In (0001) oriented slabs, the exchange-driven altermagnetic spin splitting collapses, but including spin-orbit coupling restores a residual anisotropic splitting of $\sim70$~meV. In contrast, the (110) oriented slabs show an altermagnetic spin splitting of $\sim400$~meV, and emerges as a robust candidate for realizing large, exchange-driven altermagnetism

We experimentally demonstrate that absorption and emission spectra of trivalent lanthanide-doped anisotropic crystals can exhibit a significant magnetic-polarization dependence, which has been largely overlooked in spectroscopic studies to date. Focusing on the uniaxial laser host LiYF4 (YLF) doped with Yb3+, Tm3+, Er3+, and Ho3+, we measure magnetic-polarization-dependent absorption and emission spectra for transitions with strong magnetic-dipole (MD) contributions predicted by theory. Our results reveal that MD-induced spectral anisotropy, i.e., spectral differences for the same electric field orientation but for different magnetic field orientations, is present even in these well-established laser materials. A complete spectroscopic characterization of uniaxial crystals requires three polarizations, including the $α$-polarization, with both the electric field vector E and the magnetic field vector H perpendicular to the c-axis (E $\perp$ c, H $\perp$ c), in addition to the commonly used two polarizations $π$ (E $\parallel$ c, H $\perp$ c) and $σ$ (E $\perp$ c, H $\parallel$ c). We further discuss the observed MD-induced spectral anisotropy and calculated MD branching ratios, the impact of the anisotropy on emission cross-section calculations, and the relevance of our results to other uniaxial and biaxial crystals.

We investigate whether giant fluctuations in a gas can induce corresponding fluctuations on a reactive surface in contact with the gas. Numerical simulations of a minimal heterogeneous catalytic reactor demonstrate that such fluctuations indeed emerge on the surface, with spatial correlations extending over micrometer scales. These fluctuations originate from the dependence of the adsorption rate on the reactant partial pressure. As a result, the surface-coverage structure factor mirrors that of the partial pressure, exhibiting similar enhancement and roll-off behavior across wave numbers.

Electrothermal characterization based on the third or other harmonics of an ac Joule heating current is widely deployed for the thermal analysis of solid conductors and their environment, including solid substrates and fluids. However, a unified theory that bridges heat transfer in two archetypal experimental geometries - suspended vs. substrate-supported conductor - has been missing. Here, we present and validate such a theory that explicitly accounts for finite conductor length, thermal mass, and environmental coupling through a unified thermal transfer function. This framework enables the prediction of voltage responses at all harmonics of the driving current (dc, 1$ω$, 2$ω$, 3$ω$) and the formulation of design principles for the characterization of nanoscale conductors. The conductor length $l$ is the primary parameter controlling the frequency regime at which the conductor's thermal mass dominates the thermal response, with the characteristic frequency $ω_\mathrm{c}=α/l^2$, where $α$ is the conductor's thermal diffusivity - closely related to a criterion previously reported for suspended wires free from environmental coupling. Our unified framework generalizes this result, revealing that sufficiently weak environmental coupling is a necessary condition for $ω_\mathrm{c}$ to govern the onset of thermal-mass-dominated response. Optimization of interfacial thermal resistance and environmental thermal impedance may further improve temperature resolution and facilitate on-substrate implementations.

Ferroelectric materials, with their strong nonlinearities, underpin key technologies across radio-frequency (RF) signal processing, optical communications, and emerging quantum systems. Barium titanate (BTO) is a notable example, combining strong piezoelectric and electro-optic responses. While bulk BTO has been studied for decades, the piezoelectric properties of its recently available thin films, and their behavior at the millikelvin temperatures relevant to quantum hardware, remain largely unexplored. Here, we fabricate and characterize surface acoustic wave (SAW) resonators on thin-film BTO. The measured devices exhibit high electromechanical coupling (k2eff 0.14 at 5.2 GHz) and operate up to 7.8 GHz. From these measurements, combined with finite-element modeling of the multi-domain microstructure, we extract an effective piezoelectric coefficient d33eff of 53 pC/N, comparable to bulk BTO. Exploiting the intrinsic ferroelectricity, we further demonstrate low-voltage switching with a fast (100 ns) response, attractive for reconfigurable RF front-ends and parametric amplifiers. Extending these measurements to millikelvin temperatures, we find that the piezoelectric response persists, with d33eff 19 pC/N, pointing to the potential of BTO for piezoelectric coupling in superconducting quantum circuits. These results position thin-film BTO as a promising piezoelectric platform for both classical and quantum information technologies.

The $δ$ phase of Niobium Nitride (NbN) is a promising superconducting material, which is chemically stable and shares lattice compatibility with conventional III-Nitride semiconductors. Due to a high critical temperature (T$_{c}$) and a high critical (magnetic) field (H$_{c}$), NbN is much-coveted for a diverse set of applications spanning from single photon detectors, and hot-electron bolometers to quantum computing architectures using superconducting circuits. However, synthesizing high-quality epitaxial films of phase pure and stoichiometric $δ$-NbN in a cost-effective manner, is challenging. In this study, we investigate the epitaxial growth of single crystalline $δ$-NbN on TiN-buffered c-sapphire (Al$_{2}$O$_{3}$) substrates by sputtering at room temperature. For these films, we demonstrate a surface-roughness in picometer-scale, the lowest reported till date. The critical temperature (T$_{c}$) of the epitaxial $δ$-NbN films was observed to decrease with the insertion of the TiN buffer layer, tentatively attributable to the leakage of Cooper pairs, due to the proximity effect. TiN and NbN layer behave as a bilayer system, wherein Cooper-pair leakage is facilitated by the absence of any oxide interlayer. Consequently, T$_{c}$ reduces with increasing thickness of the TiN layer.

Thermal runaway remains a critical safety concern in battery systems and other thermally active devices, necessitating reliable methods for predicting the conditions under which thermal runaway may occur. In this work, we develop a finite element framework for assessing thermal stability in systems undergoing transient heat conduction with temperature-dependent internal heat generation. The formulation leads naturally to a generalized eigenvalue problem, wherein the sign of the smallest eigenvalue provides a direct criterion for determining the onset of thermal runaway. This approach enables direct prediction of thermal runaway thresholds in geometrically complicated problems without requiring computationally expensive transient analysis. The proposed methodology is validated through comparison with analytical solutions for a cylindrical Li-ion cell, as well as with a pack of cylindrical cells, demonstrating excellent agreement in both cases. Based on this model, the influence of material properties, boundary conditions, geometric parameters, and spatially varying heat generation on stability limits is examined. A key advantage of this formulation is its effectiveness even for complex geometries where analytical methods become impractical. By providing a systematic and computationally efficient means to identify stability thresholds, the present work offers a practical tool for the thermal design and safety assessment of battery systems.

Manganese selenide (MnSe) is a promising air-stable two-dimensional magnetic semiconductor for which theory predicts robust ferromagnetism in monolayers with Curie temperatures approaching 250 K. However, the crystallographic phases and magnetic properties of thin-film MnSe grown by scalable methods remain poorly understood. Here, we demonstrate the controllable growth of $α$- and $β$-phase MnSe on C-face sapphire using a three-zone chemical vapor deposition process with elemental Se and ${MnCl_{2}}$ precursors in an $Ar/{H_{2}}$ atmosphere. Using Raman spectroscopy, atomic force microscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy, we show that our process yields phase-pure $α$-MnSe nanorods and $β$-MnSe triangular flakes with lateral sizes up to 20 $μm$ and thicknesses of 15-30 nm. Low-temperature photoluminescence of the $β$-phase films reveals a bandgap of approximately 2.0 eV. Systematic variation of growth parameters shows that precursor vapor pressure, rather than ${H_{2}}$ partial pressure, is the dominant factor controlling lateral flake size. Vibrating-sample magnetometry measurements reveal a $N{é}el$ temperature of 53 K in the $β$-phase films, providing clear evidence of antiferromagnetism in the multilayer regime and establishing MnSe as a tunable platform for 2D spintronic and optoelectronic devices.

Calcium (Ca) insertion into graphite (C) has been considered to require elevated temperatures, and its occurrence at room temperature (RT) has been regarded as highly unlikely. Here, we demonstrate that sodium (Na) catalysis enables the formation of superconducting CaC$_6$ even at RT. In mixtures of Ca, Na, and graphite, the gradual development of superconducting diamagnetism and the emergence of X-ray diffraction peaks confirm the formation of CaC$_6$ during storage at RT. The superconducting transition temperature increases with storage time, and the amount of CaC$_6$ scales proportionally to the square root of storage time. These findings provide new insights into the mechanism of superconductivity and Na-catalyzed formation of CaC$_6$, and highlight the potential of this RT intercalation process for practical applications such as electrode materials in Ca-ion batteries.