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At least 487 records · Page 27

Hydration structure and energetics of iron-exchanged montmorillonite

The interaction between iron released from corroded steel canisters and bentonite is a key process influencing the long-term performance of nuclear waste repositories. In particular, the migration of Fe²⁺ into montmorillonite (Mnt) interlayers may alter its hydration, swelling, and ion-transport properties. In the present study, molecular dynamics simulations were performed to investigate the hydration behavior, structural response, and transport properties of Fe-exchanged montmorillonite (Fe-Mnt) under varying hydration states. The simulations focus on short- to intermediate-time-scale Fe 2+ and Fe 3+ interlayer exchange and hydration effects, and do not consider long-term structural substitution, Fe-bearing clay phase stabilization, or secondary iron mineral precipitation. Systems containing Na + -, Fe 2+ -, and Fe 3+ -Mnt were examined using both periodic and edge-exposed configurations to evaluate interlayer structure, ion exchange, and free energy of Fe intercalation. The results show that Fe ions influence the interlayer spacing primarily at low water contents (<1 bilayer), where Fe-Mnt exhibits a d-spacing 1–2 Å larger than Na-Mnt due to stronger hydration. The calculated hydration energies follow the order Fe 2+ $<$Fe 3+ $<$Na + . Both water and ion diffusion coefficients decrease upon Fe ion intercalation, with Fe 2+ ions diffusing an order of magnitude more slowly than those of Na + . Free energy profiles further confirm that Fe 2+ and Fe 3+ ions are thermodynamically favored in the interlayer, with Fe 3+ being the most stable. In conclusion, these findings provide molecular-scale insights into the mechanisms of Fe–Na exchange and their implications for bentonite alteration in repository environments.

clay↗

Optimization of Random Phase Approximation Calculations for Improved Energies of Molecules, Solids, and Surfaces

We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA through an optimized choice of reference orbitals and energy components, rather than a modification of the RPA correlation functional itself. The method employs an empirically constructed hybrid functional to generate DFT orbitals to evaluate the RPA correlation energy, which is then scaled by a constant. Comprehensive benchmarks across molecules, bulk solids, and surface systems demonstrate that optRPA26 consistently achieves high accuracy, with mean absolute errors of 0.05 eV for W4-11-RE reaction energies, 0.07 eV for cohesive energies, 0.09 eV for metal oxide formation energies, 0.11–0.12 eV for adsorption of small molecules on metals, and 0.06 eV for adsorption on oxides. In addition, optRPA26 correctly captures phase stability in metal oxides and magnetic metals. The optRPA26 approach can be run using standard RPA implementations, highlighting its potential as a general-purpose reference method that can accurately capture covalent, ionic, metallic, and van der Waals bonding in molecules, solids, and interfaces.

Adsorption↗

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ~0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Overall, our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

36 MATERIALS SCIENCE↗

Porous Colloidal Nanoparticles as Injectable Multimodal Contrast Agents for Enhanced Geophysical Sensing

Injecting fluids into underground geologic structures is crucial for the development of long-term strategies for managing captured carbon and facilitating sustainable energy extraction operations. Here, we have previously reported that the injection of metal–organic frameworks (MOFs) into the subsurface can enhance seismic monitoring tools to track fluids and map complex structures, reduce risk, and verify containment in carbon storage reservoirs because of their absorption capacity of low-frequency seismic waves. Here, we demonstrate that water-based Cr/Zn/Zr MOF colloidal suspensions (nanofluids) are multimodal geophysical contrast agents that enhance near-wellbore logging tools. Based on experimental fluid-only measurements, MIL-101(Cr), ZIF-8, and UiO-66 nanofluids have distinct complex conductivity and/or low-field nuclear magnetic resonance (NMR) signatures that are relevant to field-deployed technologies, implying the potential to enhance near-wellbore monitoring of CO 2 injection and associated processes with downhole logging tools. Small- and wide-angle X-ray scattering characterization of ~0.5 wt % MIL-101(Cr) suspensions confirmed phase stability and provided insight into the fractal nature of colloidal nanoparticles. Finally, low-field (2 MHz) NMR measurements of MIL-101(Cr) nanofluid injection into a prototypical Berea sandstone demonstrate how paramagnetic high-surface area MOFs may dominate the relaxation times of hydrogen-bearing fluids in porous geologic matrices, enhancing the mapping of near-surface and near-wellbore transport pathways and advancing sustainable subsurface energy technologies.

NMR↗

Amine-Assisted Ligand-Exchange Method to Enhance Photovoltaic Parameters in FAPbI3 Nanocrystal Solar Cells

Perovskite colloidal nanocrystals (PeNCs) have exceptional optoelectronic properties and phase stability, making them promising for photovoltaic applications. However, insulating ligands on PeNC surfaces limit the current density and reduce the power conversion efficiency (PCE) in PeNC solar cells (SCs). This study introduces an amine-assisted ligand-exchange (ALE) strategy using 3-phenyl-1-propylamine (3P1P) to effectively remove long ligands from PeNC films. ALE reduced long-chain ligand density without increasing the number of defect states and therefore reduced the exciton-binding energy of FAPbI3 NC films. These changes facilitated exciton dissociation and charge transport in FAPbI3 PeNC SCs. The facilitation of exciton dissociation was due to the increased magnetic dipole interaction between excitons after the ALE process. The use of ALE achieved FAPbI3 PeNC SCs that had an improved short-circuit current density of 17.98 mA/cm2 and a PCE of 15.56% with improved stability after the treatment and negligible hysteresis. This work provides new insight into engineering PeNC films.

amines↗

Transient Lattice Response upon Photoexcitation in CuInSe 2 Nanocrystals with Organic or Inorganic Surface Passivation

CuInSe 2 nanocrystals offer promise for optoelectronics including thin-film photovoltaics and printed electronics. Additive manufacturing methods such as photonic curing controllably sinter particles into quasi-continuous films and offer improved device performance. To gain understanding of nanocrystal response under such processing conditions, we investigate impacts of photoexcitation on colloidal nanocrystal lattices via time-resolved X-ray diffraction. We probe three sizes of particles and two capping ligands (oleylamine and inorganic S 2- ) to evaluate resultant crystal lattice temperature, phase stability, and thermal dissipation. Elevated fluences produce heating and loss of crystallinity, the onset of which exhibits particle size dependence. We find size-dependent recrystallization and cooling lifetimes ranging from 90 to 200 ps with additional slower cooling on the nanosecond time scale. Sulfide-capped nanocrystals show faster recrystallization and cooling compared to oleylamine-capped nanocrystals. Using these lifetimes, we find interfacial thermal conductivities from 3 to 28 MW/(m 2 K), demonstrating that ligand identity strongly influences thermal dissipation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of High-Performance Lead-Free Quaternary Antiperovskites for Photovoltaics via Ion Type Inversion and Anion Ordering

The emergence of halide double perovskites significantly increases the compositional space for lead-free and air-stable photovoltaic absorbers compared to halide perovskites. Nevertheless, most halide double perovskites exhibit oversized band gaps (>1.9 eV) or dipole-forbidden optical transition, which are unfavorable for efficient single-junction solar cell applications. The current device performance of halide double perovskite is still inferior to that of lead-based halide perovskites, such as CH 3 NH 3 PbI 3 (MAPbI 3 ). Here, by ion type inversion and anion ordering on perovskite lattice sites, two new classes of pnictogen-based quaternary antiperovskites with the formula of X 6 B 2 AA' and X 6 BB'A 2 are designed. Phase stability and tunable band gaps in these quaternary antiperovskites are demonstrated based on first-principles calculations. Further photovoltaic-functionality-directed screening of these materials leads to the discovery of 5 stable compounds (Ca 6 N 2 AsSb, Ca 6 N 2 PSb, Sr 6 N 2 AsSb, Sr 6 N 2 PSb, and Ca 6 NPSb 2 ) with suitable direct band gaps, small carrier effective masses and low exciton binding energies, and dipole-allowed strong optical absorption, which are favorable properties for a photovoltaic absorber material. The calculated theoretical maximum solar cell efficiencies based on these five compounds are all larger than 29%, comparable to or even higher than that of the MAPbI 3 based solar cell. Finally, our work reveals the huge potential of quaternary antiperovskites in the optoelectronic field and provides a new strategy to design lead-free and air-stable perovskite-based photovoltaic absorber materials.

three-dimensional electronic transport↗

Framework Short-Range Order Observed in a Spinel-Type Li Superionic Conductor

Solid-state superionic conductors are characterized by rich structural disorders. Though structural complexities are central to their functionalities, they often give rise to short-range order that eludes detection by conventional diffraction-based techniques and is thus overlooked in establishing precise structure-property relationships. In this work, we synthesized single crystals of a recently discovered lithium (Li) superionic conductor Li16.2(1)In9.00(2)Sn1.10(1)O23.8 (LISO) for in-depth characterizations of structural subtleties. LISO exhibits an unusual spinel-like phase with significant Li overstoichiometry and a face-sharing Li network. Single-crystal neutron diffraction confirms significant Li disorder, as manifested in Li site splitting and partial occupancy. More importantly, synchrotron diffuse scattering combined with 3D-ΔPDF analysis and Monte Carlo simulations reveal short-range order in the nonalkali framework that might contribute to the phase stability and ionic conductivity. This work showcases an example in which subtle local energetics can be directly visualized in structurally disordered ionic conductors.

Chen, Yu↗

Higher Dimensionality in the Mg–Co–B System: Synthesis and Structure of Incommensurate Composite Mg 1+ε Co 4 B 4

Guided by high-temperature in situ X-ray diffraction, the discovery and synthesis of Mg 1+ε Co 4 B 4 (ε ≈ 0.272) using a MgH 2 hydride precursor is reported, along with a detailed crystal structure description and measurement of magnetic properties. The mismatch in lattice periodicities between Mg and Co–B substructures places Mg 1+ε Co 4 B 4 in the family of incommensurate composite crystals and prompted structural refinement in a (3 + 1)-dimensional model. The structure of Mg 1+ε Co 4 B 4 (P4 2 /ncm(00γ)s00s, a = 6.75847(7) Å, c = 3.94007(8) Å, q = (0, 0, 1.2721(3))) was refined from neutron powder diffraction and high-resolution powder X-ray diffraction data and confirmed by scanning transmission electron microscopy and electron diffraction. Mg 1+ε Co 4 B 4 is isostructural to Nd 1+ε Fe 4 B 4 and several related ternary borides with 0.07 ≤ ε ≤ 0.17, with Mg occupying the rare-earth site. Satellite reflections in the electron diffraction patterns hinted at positional modulation of the transition metal–boron substructure by Mg atoms, but this could not be refined from the neutron or X-ray diffraction data. Low-temperature magnetic measurements show no indications of long-range magnetic ordering or superconductivity down to 5 K. DFT calculations confirmed the absence of a magnetically ordered ground state and the stability of a 5:4 supercell (ε = 0.25) relative to the fully commensurate structure. Neutron diffraction and synthesis from elemental Mg demonstrated that Mg 1+ε Co 4 B 4 is not a hydrogen-stabilized phase. Mg 1+ε Co 4 B 4 represents the second compound reported in the Mg–Co–B system and the first superspace symmetry model of a Nd 1+ε Fe 4 B 4 -type incommensurate composite compound refined from powder diffraction data.

chemical structure↗

Equation of State of TiN at High Pressures and Temperatures: A Possible Host for Nitrogen in Planetary Mantles

Nitrogen, the most abundant element in Earth's atmosphere, is also a primary component of solid nitride minerals found in meteorites and on Earth's surface. If they remain stable to high pressures and temperatures, these nitrides may also be important reservoirs of nitrogen in planetary interiors. We used synchrotron X-ray diffraction to measure the thermal equation of state and phase stability of titanium nitride (TiN) in a laser-heated diamond anvil cell at pressures up to ~70 GPa and temperatures up to ~2500 K. TiN maintains the cubic B1 (NaCl-type) crystal structure over the entire pressure and temperature range explored. It has K 0 = 274(4) GPa, K 0 ' = 3.9(2), and γ 0 = 1.39(4) for a fixed V 0 = 76.516(30) Å 3 (based on experimental measurements), q = 1, and θ 0 = 579 K. Additionally, we collected Raman spectra of TiN up to ~60 GPa, where we find that the transverse acoustic (TA), longitudinal acoustic (LA), and transverse optical (TO) phonon modes exhibit mode Grüneisen parameters of 1.66(17), 0.54(15), and 0.93(4), respectively. Based on our equation of state, TiN has a density of ~5.6–6.4 g/cm 3 at Earth's lower mantle conditions, significantly more dense than both the mantle of the Earth and the estimated densities of the mantles of other terrestrial planets, but less dense than planetary cores. Furthermore, we find that TiN remains stable against physical decomposition at the pressures and temperatures found within Earth's mantle, making it a plausible reservoir for deep planetary nitrogen if chemical conditions allow its formation.

58 GEOSCIENCES↗

Collection of fluorescence from an ion using trap-integrated photonics

Spontaneously emitted photons are entangled with the electronic and nuclear degrees of freedom of the emitting atom, so interference and measurement of these photons can entangle separate matter-based quantum systems as a resource for quantum information processing. Since confinement in a single-mode facilitates the photon interference needed for generating entanglement, the dipole emission patterns relevant in spontaneous emission present a mode-matching challenge. Current demonstrations rely on bulk photon-collection and manipulation optics that suffer from large component size and system-to-system variability—factors that impede scaling to the large numbers of entangled pairs needed for quantum information processing. To address these limitations, we demonstrate a collection method that enables passive phase stability, straightforward photonic manipulation, and intrinsic reproducibility. Specifically, we engineer a waveguide-integrated grating to couple photons emitted from a trapped ion into a single optical mode within a microfabricated ion-trap chip. Using the integrated collection optic, we characterize the collection efficiency, image the ion, and detect the ion’s quantum state. The integrated optic covers 2.18% of the solid angle and collects 1.97 ± 0.3% of the spontaneously emitted light incident on the grating for a total collection efficiency of 0.043% into a single-mode waveguide. This proof-of-principle demonstration lays the foundation for leveraging the inherent stability and reproducibility of integrated photonics to create, manipulate, and measure multipartite quantum states in arrays of quantum emitters.

Optical physics↗

High-entropy engineering of the crystal and electronic structures in a Dirac material

Dirac and Weyl semimetals are a central topic of contemporary condensed matter physics, and the discovery of new compounds with Dirac/Weyl electronic states is crucial to the advancement of topological materials and quantum technologies. Here we show a widely applicable strategy that uses high configuration entropy to engineer relativistic electronic states. We take the A MnSb 2 ( A = Ba, Sr, Ca, Eu, and Yb) Dirac material family as an example and demonstrate that mixing of Ba, Sr, Ca, Eu and Yb at the A site generates the compound (Ba 0.38 Sr 0.14 Ca 0.16 Eu 0.16 Yb 0.16 )MnSb 2 (denoted as A 5 MnSb 2 ), giving access to a polar structure with a space group that is not present in any of the parent compounds. A 5 MnSb 2 is an entropy-stabilized phase that preserves its linear band dispersion despite considerable lattice disorder. Although both A 5 MnSb 2 and A MnSb 2 have quasi-two-dimensional crystal structures, the two-dimensional Dirac states in the pristine A MnSb 2 evolve into a highly anisotropic quasi-three-dimensional Dirac state triggered by local structure distortions in the high-entropy phase, which is revealed by Shubnikov–de Haas oscillations measurements.

36 MATERIALS SCIENCE↗

Distilling physical origins of hardness in multi-principal element alloys directly from ensemble neural network models

Abstract Despite a plethora of data being generated on the mechanical behavior of multi-principal element alloys, a systematic assessment remains inaccessible via Edisonian approaches. We approach this challenge by considering the specific case of alloy hardness, and present a machine-learning framework that captures the essential physical features contributing to hardness and allows high-throughput exploration of multi-dimensional compositional space. The model, tested on diverse datasets, was used to explore and successfully predict hardness in Al x Ti y (CrFeNi) 1- x - y , Hf x Co y (CrFeNi) 1- x - y and Al x (TiZrHf) 1- x systems supported by data from density-functional theory predicted phase stability and ordering behavior. The experimental validation of hardness was done on TiZrHfAl x . The selected systems pose diverse challenges due to the presence of ordering and clustering pairs, as well as vacancy-stabilized novel structures. We also present a detailed model analysis that integrates local partial-dependencies with a compositional-stimulus and model-response study to derive material-specific insights from the decision-making process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A flexible and scalable scheme for mixing computed formation energies from different levels of theory

Abstract Computational materials discovery efforts are enabled by large databases of properties derived from high-throughput density functional theory (DFT), which now contain millions of calculations at the generalized gradient approximation (GGA) level of theory. It is now feasible to carry out high-throughput calculations using more accurate methods, such as meta-GGA DFT; however recomputing an entire database with a higher-fidelity method would not effectively leverage the enormous investment of computational resources embodied in existing (GGA) calculations. Instead, we propose here a general procedure by which higher-fidelity, low-coverage calculations (e.g., meta-GGA calculations for selected chemical systems) can be combined with lower-fidelity, high-coverage calculations (e.g., an existing database of GGA calculations) in a robust and scalable manner. We then use legacy PBE(+ U ) GGA calculations and new r 2 SCAN meta-GGA calculations from the Materials Project database to demonstrate that our scheme improves solid and aqueous phase stability predictions, and discuss practical considerations for its implementation.

36 MATERIALS SCIENCE↗

New insight into tuning magnetic phases of RMn6Sn6 kagome metals

Abstract Predicting magnetic ordering in kagome compounds offers the possibility of harnessing topological or flat-band physical properties through tuning of the magnetism. Here, we examine the magnetic interactions and phases of ErMn 6 Sn 6 which belongs to a family of R Mn 6 Sn 6 , R = Sc, Y, Gd–Lu, compounds with magnetic kagome Mn layers, triangular R layers, and signatures of topological properties. Using results from single-crystal neutron diffraction and mean-field analysis, we find that ErMn 6 Sn 6 sits close to the critical boundary separating the spiral-magnetic and ferrimagnetic ordered states typical for non-magnetic versus magnetic R layers, respectively. Finding interlayer magnetic interactions and easy-plane Mn magnetic anisotropy consistent with other members of the family, we predict the existence of a number of temperature and field dependent collinear, noncollinear, and noncoplanar magnetic phases. We show that thermal fluctuations of the Er magnetic moment, which act to weaken the Mn-Er interlayer magnetic interaction and quench the Er magnetic anisotropy, dictate magnetic phase stability. Our results provide a starting point and outline a multitude of possibilities for studying the behavior of Dirac fermions in R Mn 6 Sn 6 compounds with control of the Mn spin orientation and real-space spin chirality.

36 MATERIALS SCIENCE↗

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗

Machine learned synthesizability predictions aided by density functional theory

Abstract A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.

Lee, Andrew (ORCID:0000000153014295)↗

Chemical short-range order in derivative Cr–Ta–Ti–V–W high entropy alloys from the first-principles thermodynamic study

The development of high-entropy alloys (HEAs) focuses on exploring compositional regions in multi-component systems with all alloy elements in equal or near-equal atomic concentrations. Initially it was based on the main idea that high mixing configurational entropy contributions to the alloy free energy could promote the formation of a single solid solution phase. By using the ab-initio based Cluster Expansion (CE) Hamiltonian model constructed for the quinary bcc Cr–Ta–Ti–V–W system in combination with Monte Carlo (MC) simulations, we show that the phase stability and chemical short-range order (SRO) of the equiatomic quinary and five sub-quaternary systems, as well as their derivative alloys, can dramatically change the order–disorder transition temperatures (ODTT) as a function of alloy compositions. In particular, it has been found, that the equiatomic quaternary Ta–Ti–V–W and Cr–Ta–Ti–W alloys had the lowest order–disorder transition temperature (500 K) among all the analysed equiatomic compositions. In all investigated alloy systems, the strongest chemical ordering has been observed between Cr and V, which led to the conclusion that decreasing the concentration of either Cr or V might be beneficial in terms of decreasing the ODTT. It also predicts that increasing concentration of Ti significantly decreases the ODTT. Our analysis of chemical SRO as a function of alloy composition allows to understand the microstructure evolution of HEAs as a function of temperature in excellent agreement with available experimental observations. Importantly, our free energy of mixing and SRO calculations predict that the origin of precipitates formed by Cr- and V-rich in the sub-quaternary Cr–Ta–V–W system is driven by the thermodynamics. The modelling results are in an excellent agreement with experimental observation of Cr and V segregation in the W 0.38 Ta 0.36 Cr 0.15 V 0.11 alloy which in turns shows an exceptional radiation resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗