First principles computational methods can predict the superconducting critical temperature T_c of conventional superconductors through the electron-phonon spectral function. Full convergence of this quantity requires Brillouin zone integration on very dense grids, presenting a bottleneck to high-throughput screening for high T_c systems. In this work, we show that an electron-phonon spectral function calculated at low cost on a coarse grid yields accurate T_c predictions, provided the function is rescaled to correct for the inaccurate value of the density of states at the Fermi energy on coarser grids. Compared to standard approaches, the method converges rapidly and improves the accuracy of predictions for systems with sharp features in the density of states. This approach can be directly integrated into existing materials screening workflows, enabling the rapid identification of promising candidates that might otherwise be overlooked.

Crystal structures can be predicted from first-principles using ab initio random structure searching (AIRSS) to sample the potential energy landscape, and density functional theory (DFT) to robustly and accurately describe it. While classical interatomic potentials lower computational costs at the expense of robustness and accuracy, modern machine-learning potentials offer a compromise, providing both at a fraction of the DFT cost. In this work, we use Ephemeral Data-Derived Potentials (EDDPs) to accelerate AIRSS calculations for binary hydrides at 100 GPa. Since the training data is generated iteratively using AIRSS, the searches require no prior knowledge of hydrides. These potentials allow more diverse searches, sampling diverse compositions, larger unit cells, and many more structures. Besides recovering known structures, the searches reveal hydrogen-rich phases of H-22(BrH), H23Pb, and H32Mg, supermolecular phases of H25Cs and H26Rn, and many 'substoichiometric' variants of known hydrides. Our results indicate that using the current generation of universal MLIPs to search for novel high-pressure hydrides is less effective due to model instabilities or markedly slower inference speeds and highlight the necessity of generating new, targeted data.

Room-temperature superconductivity is arguably the greatest challenge in condensed matter physics, with significant practical and commercial implications if it can be solved. There are no physical laws preventing this from occurring; indeed, superconductivity has been observed in so many different materials under so many different conditions that it is almost a "generic" property of nonmagnetic metals. This guides our viewpoint that high-temperature superconductivity is possible, if difficult to realize. Here, we lay out two grand challenges facing the field, titled the Prediction Challenge and the Engineering Challenge, and put forward a programmatic approach for overcoming them. The Prediction Challenge addresses the fact that our ability to predict new conventional superconductors has dramatically advanced in recent years, but most predicted materials are not experimentally synthesizable. To address this challenge, we propose a shift from modeling the superconducting critical temperature and dynamic stability toward high-throughput ab initio and predictive thermodynamics/synthesis modeling. The Engineering Challenge describes how we can control superconductivity with various "knobs," including pressure, nanostructuring, and light. However, our ability to predict how a specific knob will modify a given superconductor is limited, making it difficult to fully exploit them. We describe the current status and identify areas where additional work is needed to fully exploit six of the most common knobs. Progress in both of these grand challenges, while closely integrating theory and experiment into a continuous feedback loop and incorporating insights from fields beyond physics and materials science, could unlock the underlying keys to room-temperature superconductivity.

Water confined within nanoscale capillaries exhibits phase behaviour and transport properties that differ substantially from bulk, and these effects are commonly interpreted as consequences of geometric confinement and reduced dimensionality. Here we show that confinement topology alone is insufficient to predict the behaviour of nanoconfined water. Using machine learning interatomic potentials with first-principles accuracy, we compute the density-temperature phase diagram of water confined within bilayer graphene nanocapillaries and compare AA and AB stacking arrangements, which differ only by a lateral shift of 1.4 Å. Despite this minimal structural change, AA stacking can stabilise different ice polymorphs, can increase the melting temperature by more than 100 K, can enhance proton transfer, and alters the onset of superionic behaviour relative to AB stacking. We trace these effects to stacking-induced changes in the hydrogen-bond network associated with modifications to the lateral free energy landscape and neighbouring O-O separations. Our results demonstrate that even subtle atomistic variations in the confining walls can qualitatively reshape the physical and chemical behaviour of nanoconfined water, with implications for the interpretation and control of fluids under angstrom-scale confinement.

Niobium nitride is renowned for its exceptional mechanical, electronic, magnetic, and superconducting properties. The ideal 1:1 stoichiometric δ -NbN cubic phase, however, is known to be dynamically unstable, and repeated experimental observations have indicated that vacancies are necessary for its stabilization. In this work, we demonstrate that when the structure is fully relaxed and allowed to distort under quantum anharmonic effects, a stable cubic phase with space group $$P\bar{4}3m$$ P 4 ¯ 3 m emerges — 65 meV/atom lower in free energy than the δ phase. This discovery is enabled by state-of-the-art first-principles calculations accelerated by machine-learned interatomic potentials. To evaluate the vibrational properties with quantum anharmonic effects accounted for, we use the stochastic self-consistent harmonic approximation and molecular dynamics spectral energy density methods. Electron-phonon coupling calculations based on the anharmonic phonon dispersion yield a superconducting transition temperature of 20 K, which aligns with experimentally reported values for near-stoichiometric NbN. These findings challenge the long-held assumption that vacancies are essential for stabilizing cubic NbN and point to the potential of synthesizing the ideal 1:1 stoichiometric phase as a route to achieving enhanced superconducting performance in this technologically significant material.

Predicting the (meta)stable crystal structures in a binary phase diagram under pressure is essential for enhancing our understanding of high-pressure materials. The gallium-sulfur system is especially intriguing because of the semiconductor materials present at atmospheric pressure, with the potential for new compositions to form under compression. In this article, we employed two distinct and powerful methodologies for crystal structure prediction from ambient pressure up to 100 GPa in the Ga-S system: evolutionary algorithms as implemented in the USPEX package, utilizing the accuracy of density functional theory (DFT) for precise electronic structure calculations, and ab initio random structure searching (AIRSS), leveraging ephemeral data-derived potentials (EDDP) to achieve high-speed exploration. Our crystal structure search not only reaffirms the existence of the known GaS and Ga2S3 phases but also reveals eleven novel phases emerging progressively as the pressure is increased from 0 to 100 GPa, demonstrating their dynamic stability across varying pressure regimes. Our calculations predict P63/mmc → C2/m → R3̄m and Cc → R3m → R3̄m transitions in GaS and Ga2S3, respectively. Among the eleven predicted phases, C2/m GaS2 and C2/m Ga3S4 persist to ambient pressure on decompression, which are dynamically stable. C2/m GaS2 is a layered material composed of 2D sheets of Ga2S2 and intercalated S2 dimers that exhibits electrical insulating properties. Upon compression, a pressure-induced polymerisation is observed in GaS2. The S2 dimers couple to form a linear, infinite sulphur chain with 1 electron-2 center bonds. This electronic configuration, i.e. 7 electrons per -(S-)- repeating unit, confers the electrical metallic properties of the high-pressure Cmcm GaS2 phase.

The synthesis of new polyhydrides with high superconducting Tc is challenging owing to the high pressures and temperatures required. In this study, we used machine-learning potential molecular dynamics simulations to investigate the initial stage of polyhydride formation in calcium hydrides. Upon contact with high-pressure H2, the surface of CaH2 melts, leading to CaH4 formation. This surface melting proceeds via CaH4 liquid phase as an intermediate state. High pressure reduces not only the hydrogenation (CaH2(s) + H2(l) ↔ CaH4(s)) enthalpy but also the enthalpy for liquid polyhydride formation (CaH2(s) + H2(l) ↔ CaH4(l)). Consequently, this surface melting process becomes more favorable than the fusion of the polyhydride bulk. Thus, high pressure not only shifts the equilibrium toward the polyhydride product but also lowers the activation energy, thereby promoting the hydrogenation reaction. From these thermodynamic insights, we propose structure-search criteria for polyhydride synthesis that are both computationally effective and experimentally relevant. These criteria are based on bulk properties, such as polyhydride (product) melting temperature and pressure-dependent hydrogenation enthalpy, readily determined through supplementary calculations during structure prediction workflows.

The low-pressure stabilization of superconducting hydrides with high critical temperatures (T_cs) remains a significant challenge, and experimentally verified superconducting hydrides are generally constrained to a limited number of structural prototypes. Ternary transition-metal complex hydrides (hydrido complexes)-typically regarded as hydrogen storage materials-exhibit a large range of compounds stabilized at low pressure with recent predictions for high-T_c superconductivity. Motivated by this class of materials, we investigated complex hydride formation in the Mg-Pt-H system, which has no known ternary hydride compounds. Guided by ab initio structural predictions, we successfully synthesized a novel complex transition-metal hydride, Mg_4Pt_3H_6, using laser-heated diamond anvil cells. The compound forms in a body-centered cubic structural prototype at moderate pressures between 8-25 GPa. Unlike the majority of known hydrido complexes, Mg_4Pt_3H_6 is metallic, with formal charge described as 4[Mg]^2+.3[PtH_2]^2-. X-ray diffraction (XRD) measurements obtained during decompression reveal that Mg_4Pt_3H_6 remains stable upon quenching to ambient conditions. Magnetic-field and temperature-dependent electrical transport measurements indicate ambient-pressure superconductivity with T_c (50 reasonable agreement with theoretical calculations. These findings clarify the phase behavior in the Mg-Pt-H system and provide valuable insights for transition-metal complex hydrides as a new class of hydrogen-rich superconductors.

Current studies show that oxygen does not aggregate into a polymeric phase even under pressures up to 10 TPa. To address the critical knowledge gap in understanding dense oxygen, here we show the complete polymerization process of oxygen, by using structure prediction methods. We determine the crystal structures of oxygen up to 1 PPa (1000 TPa), identifying a novel two-dimensionally bonded body-centered tetragonal (bct) phase and a fully polymerized hexagonal close-packed (hcp) phase. Electronic structure analysis reveals significant bond softening in the bct phase with increasing pressure, which may affect the dynamic behavior under finite temperatures. So, we employ the machine learning potential molecular dynamics and the two-phase method to construct the melting curve of oxygen up to 200 TPa (200 TPa, 23,740 K) and identify abnormal melting behavior beyond 100 TPa. We find oxygen exhibits higher thermal conductivity and lower isochoric heat capacity than helium at identical pressures. These results indicate that oxygen-rich envelopes may accelerate the cooling process of white dwarfs.

Fundamental physical constants govern key effects in high-energy particle physics and astrophysics, including the stability of particles, nuclear reactions, formation and evolution of stars, synthesis of heavy nuclei and emergence of stable molecular structures. Here, we show that fundamental constants also set an upper bound for the frequency of phonons in condensed matter phases, or how rapidly an atom can vibrate. This bound is in agreement with \textit{ab initio} simulations of atomic hydrogen and high-temperature hydride superconductors, and implies an upper limit to the superconducting transition temperature $T_c$ in condensed matter. Fundamental constants set this limit to the order of 10$^2-10^3$ K. This range is consistent with our calculations of $T_c$ from optimal Eliashberg functions. As a corollary, we observe that the very existence of the current research of finding $T_{\mathrm{c}}$ at and above $300$ K is due to the observed values of fundamental constants. We finally discuss how fundamental constants affect the observability and operation of other effects and phenomena including phase transitions.

Data driven methods have transformed the prospects of the computational chemical sciences, with machine learned interatomic potentials (MLIPs) speeding up calculations by several orders of magnitude. I reflect on theory driven, as opposed to data driven, discovery based on ab initio random structure searching (AIRSS), and then introduce two methods which exploit machine learning acceleration. I show how long high throughput anneals, between direct structural relaxation, enabled by ephemeral data derived potentials (EDDPs), can be incorporated into AIRSS to bias the sampling of challenging systems towards low energy configurations. Hot AIRSS (hot-AIRSS) preserves the parallel advantage of random search, while allowing much more complex systems to be tackled. This is demonstrated through searches for complex boron structures in large unit cells. I then show how low energy carbon structures can be directly generated from a single, experimentally determined, diamond structure. An extension to the generation of random sensible structures, candidates are stochastically generated and then optimised to minimise the difference between the EDDP environment vector and that of the reference diamond structure. The distance-based cost function is captured in an actively learned EDDP. Graphite, small nanotubes and caged, fullerene-like, structures emerge from searches using this potential, along with a rich variety of tetrahedral framework structures. Using the same approach, the pyrope, Mg$_3$Al$_2$(SiO$_4$)$_3$, garnet structure is recovered from a low energy AIRSS structure generated in a smaller unit cell with a different chemical composition. The relationship of this approach to modern diffusion model based generative methods is discussed.

We investigate the pressure-temperature (p-T ) phase diagram of elemental lithium (Li) up to multiterapascal (TPa) pressures using ab initio random structure search (AIRSS) and density functional theory (DFT). At zero temperature, beyond the high-pressure Fd3m diamond structure already predicted in previous studies, we find 11 solid-state phase transitions to structures of greatly varying complexity. The full p-T dependence of the phase boundaries are computed within the vibrational quasi-harmonic approximation (QHA), and the solid-liquid melting line is calculated using two different ab initio molecular dynamics simulation methods (heat-until-melt and the Z method). Notably, between 39.1 and 55.7 TPa, Li adopts an elaborate monoclinic structure with 46 atoms in the primitive unit cell, and between 71.9 and 103 TPa, an incommensurate host-guest phase of the Ba-IV type. We find that Li, hitherto predicted to be an electride at TPa pressures, abruptly loses its electride character above 16 TPa, reverting back to normal metallic behavior with a corresponding rise in the Fermi-level electronic density of states (eDOS) and broadening of the electronic bands.

Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many different chemical elements and domains, these potentials are widely applicable, but comparably slow and resource-intensive to run. Here we show how distillation via synthetic data can be used to cheaply transfer knowledge from atomistic foundation models to a range of different architectures, unlocking much smaller, more efficient potentials. We demonstrate speed-ups of > 10× by distilling from one graph-network architecture into another, and > 100× by leveraging the atomic cluster expansion framework. We showcase applicability across chemical and materials domains: from liquid water to hydrogen under extreme conditions; from porous silica and a hybrid halide perovskite solar-cell material to modelling organic reactions. Our work shows how distillation can support the routine and computationally efficient use of current and future atomistic foundation models in real-world scientific research.

The synthesis of new superhydrides with high superconducting Tc is challenging owing to the high temperatures and pressures required. Herein, we use machine-learning potential molecular dynamics simulations to investigate the initial stages of superhydride formation in calcium hydrides. Upon contact with high-pressure H2, the surface of CaH2 melts, leading to CaH4 formation. This surface melting, facilitated by the negative enthalpy of the hydrogenation reaction, proceeds via a liquid CaH4 intermediate state. Our findings show that surface melting becomes more favorable than the melting of the superhydride bulk under high pressure, reducing the activation energy required for hydrogenation. From these thermodynamics, we propose superhydride synthesis guidelines based on bulk properties: superhydride melting temperature and pressure-dependent hydrogenation enthalpy, readily determined through supplementary calculations during structure prediction workflows.

Following long-standing predictions associated with hydrogen, high-temperature superconductivity has recently been observed in several hydride-based materials. Nevertheless, these high-T-c phases only exist at extremely high pressures, and achieving high transition temperatures at ambient pressure remains a major challenge. Recent predictions of the complex hydride Mg2IrH6 may help overcome this challenge with calculations of high-T-c superconductivity (65K < T-c < 170K) in a material that is stable at atmospheric pressure. In this paper, the synthesis of Mg2IrH6 was targeted over a broad range of P-T conditions, and the resulting products were characterized using x-ray diffraction (XRD) and vibrational spectroscopy, in concert with first-principles calculations. The results indicate that the charge-balanced complex hydride Mg2IrH5 is more stable over all conditions tested up to approximately 28 GPa. The resulting hydride is isostructural with the predicted superconducting Mg2IrH6 phase except for a single hydrogen vacancy, which shows a favorable replacement barrier upon insertion of hydrogen into the lattice. Bulk Mg2IrH5 is readily accessible at mild P-T conditions and may thus represent a convenient platform to access superconducting Mg2IrH6 via nonequilibrium processing methods. Finally, the critical factors influencing the calculated range of superconducting transition temperatures for this material are discussed.

The recent claim of room temperature superconductivity in a copper-doped lead apatite compound, called LK-99, has sparked remarkable interest and controversy. Subsequent experiments have largely failed to reproduce the claimed superconductivity, while theoretical works have identified multiple key features including strong electronic correlation, structural instabilities, and dopability constraints. A puzzling claim of several recent theoretical studies is that both parent and copper-doped lead apatite structures are dynamically unstable at the harmonic level, questioning decades of experimental reports of the parent compound structures and the recently proposed copper-doped structures. In this work, we demonstrate that both parent and copper-doped lead apatite structures are dynamically stable at room temperature. Anharmonic phonon-phonon interactions play a key role in stabilizing some copper-doped phases, while most phases are largely stable even at the harmonic level. We also show that dynamical stability depends on both volume and correlation strength, suggesting controllable ways of exploring the copper-doped lead apatite structural phase diagram. Our results fully reconcile the theoretical description of the structures of both parent and copper-doped lead apatite with experiment.

Synthesis of novel inorganic materials involving molecular absorption is challenging owing to the control of interfacial reactions. Here, we reveal the kinetic role of applied pressure in the interfacial reaction. Specifically, we used machine-learning potential molecular dynamics simulations to investigate the initial stage of superhydride formation in calcium hydrides. Upon contact with high-pressure H2, the surface of CaH2 melts, leading to CaH4 formation. This surface melting proceeds via CaH4 liquid phase as an intermediate state. Therefore, the high pressure reduces not only the hydrogenation (CaH2 + H2 ↔ CaH4) enthalpy but also the activation energy of the reaction via liquid product phase. This advantage of high-pressure synthesis is applicable to any interfacial reactions involving molecular absorption, opening new avenue to inorganic material synthesis. From these thermodynamics, we also propose superhydride synthesis guidelines based on bulk properties: superhydride (product) melting temperature and pressure-dependent hydrogenation enthalpy, readily determined through supplementary calculations during structure prediction workflows.

Fluorite-perovskite heterointerfaces garner great interest for enhanced ionic conductivity for application in electronic and energy devices. However, the origin of observed enhanced ionic conductivity as well as the details of the atomic structure at these interfaces remain elusive. Here, systematic, multi-stoichiometry computational searches and experimental investigations are performed to obtain stable and exact atomic structures of interfaces between CeO2 and SrTiO3—two archetypes of the corresponding structural families. Local reconstructions take place at the interface because of mismatched lattices. TiO2 terminated SrTiO3 causes a buckled rock salt CeO interface layer to emerge. In contrast, SrO terminated SrTiO3 maintains the fluorite structure at the interface compensated by a partially occupied anion lattice. Moderate enhancement in oxygen diffusion is found along the interface by simulations, yet evidence to support further significant enhancement is lacking. Our findings demonstrate the control of interface termination as an effective pathway to achieve desired device performance.

Following long-standing predictions associated with hydrogen, high-temperature superconductivity has recently been observed in several hydride-based materials. Nevertheless, these high-T_c phases only exist at extremely high pressures, and achieving high transition temperatures at ambient pressure remains a major challenge. Recent predictions of the complex hydride Mg_2IrH_6 may help overcome this challenge with calculations of high-T_c superconductivity (65 K< T_c < 170 K) in a material that is stable at atmospheric pressure. In this work, the synthesis of Mg_2IrH_6 was targeted over a broad range of P-T conditions, and the resulting products were characterized using X-ray diffraction (XRD) and vibrational spectroscopy, in concert with first-principles calculations. The results indicate that the charge-balanced complex hydride Mg_2IrH_5 is more stable over all conditions tested up to ca 28 GPa. The resulting hydride is isostructural with the predicted superconducting Mg_2IrH_6 phase except for a single hydrogen vacancy, which shows a favorable replacement barrier upon insertion of hydrogen into the lattice. Bulk Mg_2IrH_5 is readily accessible at mild P-T conditions and may thus represent a convenient platform to access superconducting Mg_2IrH_6 via non-equilibrium processing methods.

Using first-principles calculations and crystal structure search methods, we found that many covalently bonded molecules such as H 2 , N 2 , CO 2 , NH 3 , H 2 O and CH 4 may react with NaC l, a prototype ionic solid,and form stable compounds under pressure while retaining their molecular structure. These molecules,despite whether they are homonuclear or heteronuclear, polar or non-polar, small or large, do not show strong chemical interactions with surrounding Na and Cl ions. In contrast, the most stable molecule among all examples, N 2 , is found to transform into cyclo-N 5 - anions while reacting with NaC l under high pressures. It provides a new route to synthesize pentazolates, which are promising green energy materials with high energy density. Our work demonstrates a unique and universal hybridization propensity of covalently bonded molecules and solid compounds under pressure. This surprising miscibility suggests possible mixing regions between the molecular and rock layers in the interiors of large planets.