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At least 127 records · Page 7

Photochemistry of Hypervalent Iodoazide Derivatives

The photochemical properties and reaction mechanisms of a series of hypervalent iodoazide compounds (R–IN3) were investigated, with substituents (−CH 3 , −H, −CF 3 ) tuning the electronic density of the phenyl ring. With the help of UV irradiation, ultrafast time-resolved spectroscopy, and density functional theory (DFT) calculations, we elucidated the mechanisms of azide radical (N 3 • ) release and its subsequent reactivity. UV–vis spectroscopy reveals that the photoconversion rates follow the trend CH3 > H > CF3, aligning with DFT-calculated ΔG values for ring-opening transitions. Homolytic cleavage of the I–N bond is identified as the dominant pathway for N3• generation upon UV irradiation, occurring within 400 fs. The released azide radicals react with the solvent molecules, while the iodo radical R–I C • fragments undergo a thermodynamically uphill lactone ring-opening (RO) reaction and subsequent hydrogen atom abstraction from the solvent to form carboxylic acids R–I–COOH, as validated by NMR and IR spectroscopy. The study also highlights the role of substituents in influencing reaction kinetics and intermediate stability, with electron-donating groups accelerating the release of the N 3 • species. This work bridges experimental observations with computational predictions, offering a foundation for future advancements in azide-based reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Trigger Linkage Dynamics in Energetic Materials Using Mixed Picramide Nitrate Ester Explosives

The ability to predict the handling sensitivity of new organic energetic materials has been a longstanding goal. We report the synthesis and characterization of six new nitropicramide energetic materials with mixed functional groups that mimic known explosives such as nitroglycerin, erythritol tetranitrate (ETN), and pentaerythritol tetranitrate (PETN). The molecules have been studied theoretically using quantum molecular dynamics (QMD) simulations and density functional theory (DFT) calculations to identify the weakest bond in the reactants - the trigger-linkages - which control handling sensitivity, and to quantify their specific enthalpies of explosion. In good accord with the drop weight impact sensitivity data, our calculations predict that the sensitivities of the molecules are very similar owing to the small variations of the energy output and rates of trigger linkage rupture. In addition, both the QMD and DFT calculations point to the nitropicramide N–NO 2 bonds as the trigger linkages rather than the more typical O–NO 2 bonds. We propose that the switch of the trigger linkage from the nitrate esters to the nitramine groups arises from the strongly electron withdrawing character of the adjacent trinitrobenzene groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equation of state and strength of diamond in high-pressure ramp loading

Diamond is used extensively as a component in high-energy-density experiments, but existing equation of state (EOS) models do not capture its observed response to dynamic loading. In particular, in contrast with first-principles theoretical models of equilibrium multiphase EOS, no solid-solid phase changes have been detected, and no general-purpose EOS models match the measured ambient isotherm. We have performed density functional theory (DFT) calculations of the diamond phase to ~10 TPa, well beyond its predicted range of thermodynamic stability, and used these results as the basis of a Mie-Grüneisen EOS. We also performed DFT calculations of the elastic moduli, and calibrated an algebraic elasticity model for use in simulations. We then estimated the flow stress of diamond by comparison with the stress-density relation measured experimentally in ramp-loading experiments. Furthermore, the resulting constitutive model allows us to place a constraint on the Taylor-Quinney factor (the fraction of plastic work converted to heat) from the observation that diamond does not melt on ramp compression.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Revealing Robust Room Temperature Ferromagnetism in Gd‐Doped Few‐Layered MoS 2 Thin Films

2D MoS 2 holds great promise for spintronics, yet is limited by intrinsic diamagnetism. This study demonstrates inducing ferromagnetic behavior in MoS 2 films doped with 0.47% Gd, achieving an ultrahigh saturation magnetization of 454 emu/cm 3 in a few‐layered film over 11‐times higher than bulk films (40 nm). Raman spectroscopy, X‐ray photoelectron spectroscopy, X‐ray magnetic circular dichroism, and density functional theory (DFT) calculations reveal an interplay between Gd dopants and Mo, S vacancies (V 1Mo+2S ), leading to the formation of bound magnetic polarons (BMPs) that drive ferromagnetic ordering. H 2 S annealing and DFT calculations reveal that defect healing reduces the saturation magnetization by 83%. High sulfur migration barrier in few‐layered films helps preserve BMPs, thereby sustaining ferromagnetism, whereas lower migration barriers in bulk films lead to suppression. These findings highlight the synergy between Gd doping and defect engineering in achieving ultrahigh room‐temperature ferromagnetism, offering a scalable strategy for developing high‐performance 2D magnetic materials for spintronic applications.

36 MATERIALS SCIENCE↗

Atomic Layer Deposition of Pt on the Surface Deactivated by Fluorocarbon Implantation: Investigation of the Growth Mechanism

Selective atomic layer deposition (ALD) using surface-controlled reactivity is attracting a great deal of attention as a simple bottom-up patterning process that can provide both continued dimensional scaling and accurate pattern placement for next-generation nanoelectronics. Previously, we reported topographically selective deposition through Pt ALD using a MeCpPtMe 3 precursor and an O 2 counter reactant on fluorocarbon (CF x )-modified surfaces; however, gradual loss of selectivity in the CF x -modified regions was observed during the Pt ALD process. This work develops a fundamental understanding of the microscopic growth mechanisms of Pt ALD on the CF x -modified surface using a combination of experimental analyses and theoretical methods. The Pt growth characteristics on the CF x surface are investigated within a temperature window from 225 to 350 °C, and the results show a sharp sensitivity to growth temperature, with significant Pt growth occurring at temperatures above 300 °C. Through density functional theory (DFT) calculations, the reaction energies for adsorption of oxygen and the MeCpPtMe 3 precursor as well as formation of reaction products of CF x degradation are determined. Based on experimental results in conjunction with the DFT calculations, we show that while lower temperature Pt ALD (<300 °C) on CF x -modified surfaces can be significantly retarded because of a lack of MeCpPtMe 3 chemisorption, the surface reaction pathways for Pt ALD on CF x -modified surfaces at temperatures above 300 °C can proceed through oxygen adsorption and CF 4 desorption followed by Pt nucleation in CF x -degraded regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

KSSOLV 2.0: An efficient MATLAB toolbox for solving the Kohn-Sham equations with plane-wave basis set

KSSOLV (Kohn-Sham Solver) is a MATLAB toolbox for performing Kohn-Sham density functional theory (DFT) calculations with a plane-wave basis set. KSSOLV 2.0 preserves the design features of the original KSSOLV software to allow users and developers to easily set up a problem and perform ground-state calculations as well as to prototype and test new algorithms. Furthermore, it includes new functionalities such as new iterative diagonalization algorithms, k-point sampling for electron band structures, geometry optimization and advanced algorithms for performing DFT calculations with local, semi-local, and hybrid exchange-correlation functionals. It can be used to study the electronic structures of both molecules and solids. So, we describe these new capabilities in this work through a few use cases. We also demonstrate the numerical accuracy and computational efficiency of KSSOLV on a variety of examples.

97 MATHEMATICS AND COMPUTING↗

Fermi surface and Berry phase analysis for Dirac nodal line semimetals: Cautionary tale from SrGa 2 and BaGa 2

A Berry phase of odd multiples of 𝜋 inferred from quantum oscillations (QOs) has often been treated as evidence for nontrivial reciprocal space topology. However, disentangling the Berry phase values from the Zeeman effect and the orbital magnetic moment is often challenging. In centrosymmetric compounds, the case is simpler as the orbital magnetic moment contribution is negligible. Although the Zeeman effect can be significant, it is usually overlooked in most studies of QOs in centrosymmetric compounds. Here, we present a detailed study on the nonmagnetic centrosymmetric SrGa 2 and BaGa 2 , which are predicted to be Dirac nodal line semimetals based on density functional theory (DFT) calculations. Evidence of the nontrivial topology is found in magnetotransport measurements. The Fermi surface topology and band structure are carefully studied through a combination of angle-dependent QOs, angle-resolved photoemission spectroscopy (ARPES), and DFT calculations, where the nodal line is observed in the vicinity of the Fermi level. Strong de Haas–van Alphen fundamental oscillations associated with higher harmonics are observed in both compounds, which are well fitted by the Lifshitz-Kosevich (LK) formula. However, even with the inclusion of higher harmonics in the fitting, we found that the Berry phases cannot be unambiguously determined when the Zeeman effect is included. We revisit the LK formula and analyze the phenomena and outcomes that were associated with the Zeeman effect in previous studies. Our experimental results confirm that SrGa 2 and BaGa 2 are Dirac nodal line semimetals. Additionally, we highlight the often overlooked role of spin-damping terms in Berry phase analysis.

36 MATERIALS SCIENCE↗

Electronic signatures of successive itinerant, antiferromagnetic transitions in hexagonal La 2 Ni 7

We use high-resolution angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) calculations to study the electronic and magnetic properties of La 2 Ni 7 , an itinerant magnetic system with a series of three magnetic transition temperatures upon cooling, which end in a small moment antiferromagnetic (smAFM) ground state. Our APRES data reveal several electron and hole pockets that have hexagonal symmetry near the Γ point. We observe significant reconstruction of the band structure upon successive magnetic transitions at T 1 ~ 61 K, T 2 ~ 57 K and T 3 ~ 42 K. Several features observed in ARPES data were reasonably well reproduced by DFT calculations, while others were not. In particular, the flat band near E f predicted by DFT in AFM state, was seemingly absent in ARPES data. Our results detail the effects of magnetic ordering on the electronic structure in a Ni-based small moment antiferromagnet and highlight challenges of current computational methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Role of Phonons and Oxygen Vacancies in Non-Cubic SrVO 3

Combining neutron diffraction with pair distribution function analysis, we have uncovered hidden reduced symmetry in the correlated metallic d 1 perovskite, SrVO 3 . Specifically, we show that both the local and global structures are better described using a GdFeO 3 distorted (orthorhombic) model as opposed to the ideal cubic ABO 3 perovskite type. Recent reports of imaginary phonon frequencies in the density functional theory (DFT)-calculated phonon dispersion for cubic SrVO 3 suggest a possible origin of this observed non-cubicity. Namely, the imaginary frequencies computed could indicate that the cubic crystal structure is unstable at T = 0 K. However, our DFT calculations provide compelling evidence that point defects in the form of oxygen vacancies, and not an observable symmetry breaking associated with calculated imaginary frequencies, primarily result in the observed non-cubicity of SrVO 3 . These experimental and computational results are broadly impactful because they reach into the thin-film and theoretical communities who have shown that SrVO 3 is a technologically viable transparent conducting oxide material and have used SrVO 3 to develop theoretical methods, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DFT-Based Calculation of Dissolution Activation Energy and Kinetics of Ni–Cr Alloys

A density functional theory investigation of the process of dissolution of Ni and Cr adatoms from model Ni–Cr(111) alloy surfaces is presented, both in vacuum and with explicit water molecules. The goal is to understand how the electronic structures solved using DFT can provide insights as to changes in valence, energy and coordination of the adatoms in the process of dissolving from the alloy surface. It is found that nearby Cr solute atoms increase the dissolution activation energy of Ni. Cr adatoms have a similar dissolution activation energy as Ni adatoms, except for one particular surface configuration that has a much smaller dissolution activation energy, which might promote selective dissolution of Cr in Ni–Cr alloys. To interpret the first-principles modeling results for the potential energy trajectory along the dissolution reaction coordinate, we provide a thermodynamic breakdown of the various terms that contribute to the dissolution activation and total reaction energy. The role of addition of Cr is explored on the dissolution kinetics of a Ni–Cr alloys of varying composition by constructing a model for the corrosion current density with DFT-based activation energies. Lastly, dissolution resistance index is proposed as a quantifiable descriptor of the dissolution resistance of corrosion resistant alloys.

36 MATERIALS SCIENCE↗

Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications

Redox-driven conductance changes are critical processes in molecular- and coordination-complex-based memristive thin films and devices that are envisioned for neuromorphic technologies, but fundamental mechanisms of conductance switching are not fully understood. Here, we explore charge disproportionation (CD) processes in [Ru II L 2 ](PF 6 ) 2 molecular systems that intrinsically involve interfragment charge transfer (IFCT). Using a combination of ab initio molecular dynamics simulation (AIMD), time-dependent density functional theory (TD-DFT), and density functional theory (DFT) calculations, we investigate the electron transfer mechanisms and the roles of temperature and cell volumetric expansion in facilitating the counterion movements and electronic transitions required for low-cost IFCT and charge redistribution. A detailed analysis of the density of states and TD-DFT calculations highlights that unpaired electrons play a crucial role in low-energy transitions, with the azo (N=N) groups of the ligand serving as the primary sites for electronic transport between molecular fragments, further stabilizing the asymmetric state. Localization of added electrons on azo ligands occurs with negligible change at the Ru centers, supported by atomic volume expansions up to +4.74 bohr 3 , and goes along with a progressive reduction of the HOMO−LUMO gap across redox states, suggesting enhanced conductivity. The TD-DFT analysis reveals a dominant IFCT excitation at 2082.76 nm in the doubly reduced (22) state, while a stabilization energy of 1.20 eV of the asymmetric (13) state relative to the symmetric (22) state is predicted by constrained DFT. Periodic DFT and AIMD simulations emulating a molecular film show that the stabilization of the asymmetric state, relative to a symmetric one, translates in net charge separation values (order of ∼0.33 e) that are strongly linked to increased counterion mobility (average counterion displacements exceeding 0.7 Å per atom during CD events) and the involvement of azo groups in electron redistribution. These findings, which align with previously reported experimental and computational data, provide key insights into the IFCT mechanisms and electronic transport facilitated by azo groups, with important implications for redox-driven memristive and neuromorphic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven studies of magnetic two-dimensional materials

We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A 2 B 2 X 6 , based on the known material Cr 2 Ge 2 Te 6 , using density functional theory (DFT) calculations and machine learning methods to determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability. We show that machine learning tools, combined with DFT calculations, can provide a computationally efficient means to predict properties of such two-dimensional (2D) magnetic materials. Our data analytics approach provides insights into the microscopic origins of magnetic ordering in these systems. For instance, we find that the X site strongly affects the magnetic coupling between neighboring A sites, which drives the magnetic ordering. Our approach opens new ways for rapid discovery of chemically stable vdW materials that exhibit magnetic behavior.

42 ENGINEERING↗

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗

Predicting electronic structures at any length scale with machine learning

The properties of electrons in matter are of fundamental importance. They give rise to virtually all material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant gas planets. Modeling and simulation of such diverse applications rely primarily on density functional theory (DFT), which has become the principal method for predicting the electronic structure of matter. While DFT calculations have proven to be very useful, their computational scaling limits them to small systems. We have developed a machine learning framework for predicting the electronic structure on any length scale. It shows up to three orders of magnitude speedup on systems where DFT is tractable and, more importantly, enables predictions on scales where DFT calculations are infeasible. Our work demonstrates how machine learning circumvents a long-standing computational bottleneck and advances materials science to frontiers intractable with any current solutions.

36 MATERIALS SCIENCE↗

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗