Materials discovery increasingly relies on the coordinated use of theory, computation, experiment, data-driven methods, and emerging quantum technologies, yet the full potential of these tools is realised only when they operate within workflows that reflect the complexity of real systems. This perspective summarises current capabilities, limitations, and opportunities across these domains, drawing on contributions from academia, industry, and national laboratories to identify the scientific and structural requirements for more reliable and efficient discovery. Classical simulations provide broad coverage across design spaces, while experimental measurements reveal degradation, heterogeneity, and kinetic processes that determine performance under realistic conditions. Machine learning accelerates exploration when supported by well-curated datasets with clear provenance and uncertainty quantification, and quantum computing offers promising routes into correlated electronic behaviour when aligned with properties that influence engineering decisions. Collectively, these insights highlight the need for reproducible workflows, shared data standards, realistic benchmarks, and a research culture that prepares scientists to work across paradigms. By integrating these methodological and organisational elements, the community can move toward discovery processes that deliver robust predictions, support confident decision making, and shorten the path from conceptual design to deployable materials.

Quantum computers (QC) could harbor the potential to significantly advance materials simulations, particularly at the atomistic scale involving strongly correlated fermionic systems, where an accurate description of quantum many-body effects scales unfavorably with size. While a full-scale treatment of condensed matter systems with currently available noisy quantum computers remains elusive, quantum embedding schemes like dynamical mean-field theory (DMFT) allow the mapping of an effective, reduced subspace Hamiltonian to available devices to improve the accuracy of ab initio calculations such as density functional theory (DFT). Here, we report on the development of a hybrid quantum-classical DFT + DMFT simulation framework which relies on a quantum impurity solver based on the Lehmann representation of the impurity Green’s function. Hardware experiments with up to 14 qubits on the IBM Quantum system are conducted, using advanced error mitigation methods and a novel calibration scheme for an improved zero-noise extrapolation to effectively reduce adverse effects from inherent noise on current quantum devices. We showcase the utility of our quantum DFT + DMFT workflow by assessing the correlation effects on the electronic structure of a real material, Ca2CuO2Cl2, which is mapped to an effective single-band Hubbard Hamiltonian and the subsequently derived Anderson impurity model solved with up to 6 bath sites on available quantum hardware. Further, we carefully benchmark our quantum results with respect to exact reference solutions and experimental spectroscopy measurements. While challenges remain to scale our approach to larger, multi-orbital and multi-site systems with more bath sites, the present work marks an important milestone towards achieving utility-scale quantum computation in materials simulation.

The variational quantum eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of issues, such as barren plateaus, local minima, quantum hardware noise, and limited qubit connectivity, thus posing challenges for their successful deployment on hardware and simulators. In this work, we propose a VQE optimization strategy that builds upon recent advances in the literature, and exhibits very shallow circuit depths when applied to the specific system of interest, namely a model Hamiltonian representing a cuprate superconductor. These features make our approach a favorable candidate for generating good ground state approximations on current NISQ devices. Our findings illustrate the potential of VQE algorithmic development for leveraging the full capabilities of NISQ devices.

We present a variational quantum thermalizer (VQT), called quantum-VQT (qVQT), which extends the variational quantum eigensolver (VQE) to finite temperatures. The qVQT makes use of an intermediate measurement between two variational circuits to encode a density matrix on a quantum device. A classical optimization provides the thermal state and, simultaneously, all associated excited states of a quantum mechanical system. We demonstrate the capabilities of the qVQT for two different spin systems. First, we analyze the performance of qVQT as a function of the circuit depth and the temperature for a 1-dimensional Heisenberg chain. Second, we use the excited states to map the complete, temperature dependent phase diagram of a 2-dimensional J1-J2 Heisenberg model. The numerical experiments demonstrate the efficiency of our approach, which can be readily applied to study various quantum many-body systems at finite temperatures on currently available NISQ devices.

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional highperformance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

SiC polytypes have been studied for decades, both experimentally and with atomistic simulations, yet no consensus has been reached on the factors that determine their stability and growth. Proposed governing factors are temperature-dependent differences in the bulk energy, biaxial strain induced through point defects, and surface properties. In this work, we investigate the thermodynamic stability of the 3C, 2H, 4H, and 6H polytypes with density functional theory (DFT) calculations. The small differences of the bulk energies between the polytypes can lead to intricate changes in their energetic ordering depending on the computational method. Therefore, we employ and compare various DFT codes, i.e., VASP, CP2K, and FHI-AIMS; exchange-correlation functionals, i.e., LDA, PBE, PBEsol, PW91, HSE06, SCAN, and RTPSS; and nine different van der Waals (vdW) corrections. At T = 0 K, 4H-SiC is marginally more stable than 3C-SiC, and the stability further increases with temperature by including entropic effects from lattice vibrations. Neither the most advanced vdW corrections nor strain on the lattice have a significant effect on the relative polytype stability. We further investigate the energies of the (0001) polytype surfaces that are commonly exposed during epitaxial growth. For Si-terminated surfaces, we find 3C-SiC to be significantly more stable than 4H-SiC. We conclude that the difference in surface energy is likely the driving force for 3C-nucleation, whereas the difference in the bulk thermodynamic stability slightly favors the 4H and 6H polytypes. In order to describe the polytype stability during crystal growth correctly, it is thus crucial to take into account both of these effects.

One of the most promising applications for near term quantum computers is the simulation of physical quantum systems, particularly many-electron systems in chemistry and condensed matter physics. In solid state physics, finding the correct symmetry broken ground state of an interacting electron system is one of the central challenges. To help finding the correct broken symmetries in the thermodynamic limit methods that allow to determine the groundstate of large but finite interacting electron systems are very useful. The variational Hamiltonian ansatz (VHA), a variational hybrid quantum-classical algorithm especially suited for finding the ground state of a solid state system, will in general not prepare a broken symmetry state unless the initial state is chosen to exhibit the correct symmetry. In this work, we discuss three variations of the VHA designed to find the symmetry-breaking groundstate of a finite system close to a transition point between different orders. As a test case we use the two-dimensional Hubbard model where we break the symmetry explicitly by means of external fields coupling to the Hamiltonian and calculate the response to these fields. For the calculation we simulate a gate-based quantum computer and also consider the effects of dephasing noise on the algorithms. We find that two of the three algorithms are in good agreement with the exact solution for the considered parameter range. The third algorithm agrees with the exact solution only for a part of the parameter regime, but is more robust with respect to dephasing compared to the other two algorithms.

We show that the topological equivalence class of holomorphic foliation germs with an isolated singularity of Poincar\'e type is determined by the topological equivalence class of the real intersection foliation of the (suitably normalized) foliation germ with a sphere centered in the singularity. We use this Reconstruction Theorem to completely classify topological equivalence classes of plane holomorphic foliation germs of Poincar\'e type and discuss a conjecture on the classification in dimension $\geq 3$.

Property map of the voltage for Li–Mn–Ni–O electrode materials as a function of the ratio of Li2MnO3·LiMnO2 and the Ni content in LiMnO2 at T = 300 K.

We prove birational superrigidity of Fano double hypersurfaces of index one with quadratic and multi-quadratic singularities, satisfying certain regularity conditions, and give an effective explicit lower bound for the codimension of the set of non-rigid varieties in the natural parameter space of the family. The lower bound is quadratic in the dimension of the variety. The proof is based on the techniques of hypertangent divisors combined with the recently discovered $$4n^2$$ -inequality for complete intersection singularities.

Over-lithiated transition metal oxides are currently the most promising high energy cathode materials. DFT calculations show that Li2MnO3 becomes increasingly unstable upon delithiation and experiences a driving force for either oxygen release from the surface or peroxide formation in the bulk. Both mechanisms are shown to be detrimental for the electrochemistry.

In analogy to the relation between symplectic packings and symplectic blow ups we show that multiple point Seshadri constants on projective complex surfaces can be calculated as the supremum of radii of multiple Kähler ball embeddings. We exemplify this connection on toric surfaces, also discussing how toric moment maps reflect the packing.

We add further notions to Lehmann’s list of numerical analogues to the Kodaira dimension of pseudo-effective divisors on smooth complex projective varieties, and show new relations between them. Then we use these notions and relations to fill in a gap in Lehmann’s arguments, thus proving that most of these notions are equal. Finally, we show that the Abundance Conjecture, as formulated in the context of the Minimal Model Program, and the Generalized Abundance Conjecture using these numerical analogues to the Kodaira dimension, are equivalent for non-uniruled complex projective varieties.

LiS cells are currently built with metallic lithium as node, a liquid electrolyte, and a cathode composed of a mixture of sulfur, carbon, and binder. While this type of cell produces good capacity during the early cycles, unwanted reactions with the electrolyte degrade the cathode and anode; making the whole cell not competitive with Li-ion batteries. A viable solution to mitigate this problem is the replacement of the carbon, binder, and electrolyte with a ceramic matrix, with high electronic and ionic conductivity. Lithium titanate (Li4Ti5O12) spinel may be a potential candidate for the fabrication of composite cathodes, due to its mechanical robustness and its high electronic and Li-ion conductivity. In this paper, we present an ab initio molecular dynamics study complemented with experimental investigations, offering a novel interpretation for the Li-ion mobility in Li4Ti5O12 and Li7Ti5O12 as well as for the chemical reactivity of these materials with molecular sulfur. Also, we present a model for the passivation of Li4Ti5O12 and Li7Ti5O12 surfaces by lithium carbonate, addressing both Li-ion mobility at the interface and sulfur reactivity. On the basis of our results, the deployment of Li4Ti5O12 and Li7Ti5O12 materials for sulfur-based battery technology is questioned mainly by the lower Li-ion conductivity of the carbonate-passivated surfaces and by the chemical reactivity of Li7Ti5O12 with sulfur molecules, which would lead to self-discharge, with resulting loss of capacity and inferior battery performance.

Lithium titanate (LTO) is a promising candidate as an anode material in future generations of lithium ion batteries due to its high intrinsic safety and stability. In this work, we investigate the diffusion barriers for lithium ions in two different crystal structures of LTO using the density functional theory. Our calculations show that the activation barriers vary between 0.30-0.48 eV for the spinel phase Li4Ti5O12 and between 0.20-0.51 eV in the lithiated rocksalt phase Li7Ti5O12. The origins of the rather broad ranges of activation energies are related to different chemical environments of the diffusion channels due to mixed occupancies of some sites in LTO. Our results reveal that the determination of lithium diffusion constants in LTO can not be carried out by using a single activation barrier. Instead, the local environment of the diffusion paths must be considered to correctly capture the variety of activation barriers. Moreover, we find the sites which have mixed occupation in LTO to trap lithium vacancies in the spinel phase. This effect is not observed in the rocksalt phase. This behavior explains the low lithium diffusivity found in experiments for lithium concentrations in the vicinity of the spinel phase.

Let π: X →ℙ^2 be the blow-up of ℂℙ^2 in n points x_i in very general position, and let E_i be the exceptional divisor over x_i. For 0 ≤ n ≤ 9 we calculate Okounkov bodies of graded linear series given by sections of multiples of line bundles π^∗𝒪_ℙ^2(d) ⊗𝒪_X(-m∑_i=1^n E_i) with respect to a flag consisting of a line on ℂℙ^2 and a point on the line in general position. Furthermore, we show what Nagata's Conjecture predicts on these Okounkov bodies when n > 9.

We show that the Zariski closure of the set of hypersurfaces of degree $M$ in ${\mathbb P}^{M}$, where $M\geq 5$, which are either not factorial or not birationally superrigid, is of codimension at least $\binom{M-3}{2}+1$ in the parameter space.

Lithium titanate (LTO) is a promising candidate as an anode material in future generations of lithium ion batteries due to its high intrinsic safety and stability. In this work, we investigate the diffusion barriers for lithium ions in two different crystal structures of LTO using the density functional theory. Our calculations show that the activation barriers vary between 0.30--0.48 eV for the spinel phase ${\mathrm{Li}}_{4}{\mathrm{Ti}}_{5}{\mathrm{O}}_{12}$ and between 0.20--0.51 eV in the lithiated rocksalt phase ${\mathrm{Li}}_{7}{\mathrm{Ti}}_{5}{\mathrm{O}}_{12}$. The origins of the rather broad ranges of activation energies are related to different chemical environments of the diffusion channels due to mixed occupancies of some sites in LTO. Our results reveal that the determination of lithium diffusion constants in LTO can not be carried out by using a single activation barrier. Instead, the local environment of the diffusion paths must be considered to correctly capture the variety of activation barriers. Moreover, we find the sites which have mixed occupation in LTO to trap lithium vacancies in the spinel phase. This effect is not observed in the rocksalt phase. This behavior explains the low lithium diffusivity found in experiments for lithium concentrations in the vicinity of the spinel phase.

In this paper a computational high-throughput screening (HTS) approach to the search for alternative permanent magnetic materials is presented. Systems considered for a start are binary intermetallic compounds composed of rare-earth (RE) and transition metal (TM) elements. With the tight-binding-linear muffin-tin-orbital-atomic-sphere-approximation (TB-LMTO-ASA) method of density functional theory (DFT) a variety of RE-TM intermetallic phases is investigated and their magnetic properties are obtained at rather low computational costs. Next, interstitial elements such as boron, carbon and nitrogen in these phases are considered. For promising candidate phases with high and stable spontaneous ferromagnetic polarization, the calculated local magnetic moments and exchange coupling parameters, as obtained from TB-LMTO-ASA calculations, are then used for Monte Carlo simulations to identify candidates with sufficiently high Curie temperatures (T-c). Finally, magnetocrystalline anisotropy constants (K-1) of the most promising candidate phases are calculated with accurate, potential-shape-unrestricted DFT calculations using the Vienna ab initio simulation package. The computational HTS procedure is illustrated by results for a selection of hard-magnetic RE-TM phases like RETM5, RE2TM17 and RE2TM14B.