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At least 289 records · Page 16

Tale of Three Molecular Nitrides: Mononuclear Vanadium (V) and (IV) Nitrides As Well As a Mixed-Valence Trivanadium Nitride Having a V 3 N 4 Double-Diamond Core

Here, transmetallation of [VCl 3 (THF) 3 ] and [TlTp tBu,Me ] afforded [(Tp tBu,Me )VCl 2 ] (1, Tp tBu,Me = hydro-tris(3-tert-butyl-5-methylpyrazol-1-yl)borate), which was reduced with KC 8 to form a $C_{3v}$ symmetric V II complex, [(Tp tBu,Me )VCl] (2). Complex 1 has a high-spin ($\textit{S}$ = 1) ground state and displays rhombic high-frequency and -field electron paramagnetic resonance (HFEPR) spectra, while complex 2 has an $\textit{S}$ = 3/2 4 A 2 ground state observable by conventional EPR spectroscopy. Complex 1 reacts with NaN 3 to form the V V nitride-azide complex [(Tp tBu,Me )V≡N(N 3 )] (3). A likely V III azide intermediate en route to 3, [(Tp tBu,Me )VCl(N 3 )] (4), was isolated by reacting 1 with N 3 SiMe 3 . Complex 4 is thermally stable but reacts with NaN3 to form 3, implying a bis-azide intermediate, [(Tp tBu,Me )V(N 3 ) 2 ] (A), leading to 3. Reduction of 3 with KC 8 furnishes a trinuclear and mixed-valent nitride, [{(Tp tBu,Me )V} 2 ($μ_{4-}$VN 4 )] (5), conforming to a Robin–Day class I description. Complex 5 features a central vanadium ion supported only by bridging nitride ligands. Contrary to 1, complex 2 reacts with NaN 3 to produce an azide-bridged dimer, [{(Tp tBu,Me )V} 2 (1,3-$μ_2$-N 3 ) 2 ] (6), with two antiferromagnetically coupled high-spin V II ions. Complex 5 could be independently produced along with [($κ_2$-Tp tBu,Me ) 2 V] upon photolysis of 6 in arene solvents. The putative {V IV ≡N} intermediate, [(Tp tBu,Me )V≡N] (B), was intercepted by photolyzing 6 in a coordinating solvent, such as tetrahydrofuran (THF), yielding [(Tp tBu,Me )V≡N(THF)] (B-THF). In arene solvents, B-THF expels THF to afford 5 and [($κ_2$-Tp tBu,Me ) 2 V]. A more stable adduct (B-OPPh 3 ) was prepared by reacting B-THF with OPPh 3 . These adducts of B are the first neutral and mononuclear V IV nitride complexes to be isolated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanochemical Solid Form Screening of Zeolitic Imidazolate Frameworks Using Structure-Directing Liquid Additives

We demonstrate a systematic application of the mechanochemical liquid-assisted grinding (LAG) methodology to screen for forms of zinc imidazolate (ZnIm 2 ), of fundamental importance as the simplest member of the zeolitic imidazolate framework materials family. The exploration of 45 different liquid additives, selected based on their molecular structure and physicochemical properties has resulted in eight different ZnIm 2 topological forms, appearing in 13 crystallographically distinct solid forms (including two previously unknown forms of the crb (BCT) topology), amorphous phases, and the interrupted moc-Zn 4 Im 8 HIm. All prepared topological forms were also explored computationally, using dispersion-corrected periodic density functional theory (DFT) calculations, enabling the rationalization of screening outcomes, and setting the stage for future prediction of additive-directed metal–organic framework (MOF) synthesis. This first systematic exploration of LAG in screening for three-dimensional MOFs demonstrates the potential of the liquid additive to not only accelerate materials synthesis, but also to direct it toward topologically different MOFs. The discovery of novel forms of a material that already exhibits at least 21 crystallographically and functionally different forms provides a strong testimony on the power of mechanochemistry in metal–organic materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Torsional Flexibility Tuning of Hexa-Carboxylate Ligands to Unlock Distinct Topological Access to Zirconium Metal–Organic Frameworks

Zirconium-based metal–organic frameworks (Zr-MOFs) exhibit remarkable structural diversity and functionality. However, uncovering new topological types within this family remains a considerable challenge today. Herein, we report two new hexa-topic ligands designed through the introduction of torsional flexibility, which enable the construction of two Zr-MOFs featuring rare network topologies. The (4,4′,4″,4‴,4‴′,4‴′′-((2-carboxybenzene-1,3,5-triyl)tris(9H-carbazole-9,3,6-triyl))hexabenzoic acid ligand (BTCH)) was obtained by replacing the rigid triptycene core in the H6PET-1 ligand (4,4′,4″,4‴,4‴′,4‴′′-(9,10-dihydro-9,10-[1,2]benzenoanthracene-2,3,6,7,14,15-hexayl)hexabenzoic acid) with a benzene-tricarbazole unit. Owing to its torsionally flexible core that allows rotational freedom to the arms, this ligand directs the construction of NU-2620 (NU represents Northwestern University), a Zr-MOF with 8-connected Zr6 clusters and the rare nuh topology. Further flexibilization of the carbazole units to benzene rings yielded the even more torsionally flexible 5′,5‴-bis(4-carboxyphenyl)-5″-(4,4″-dicarboxy-[1,1′:3′,1″-terphenyl]-5′-yl)-[1,1′:3′,1″:3″,1‴:3‴,1‴′-quinquephenyl]-4,4‴′-dicarboxylic acid ligand (CCTT), which forms NU-2630 featuring 6-connected clusters and the pcu topology. Both frameworks exhibit good chemical stability, prompting evaluation of their performance in CO2 photoreduction catalysis. Under low-concentration CO2 conditions, NU-2620 displays markedly higher catalytic activity than its benzene-based analogue, NU-2630, thanks to the abundance of photoactive carbazole units within its structure. These results demonstrate that introducing torsional flexibility in high-connected linkers can unlock access to new topologies and accelerates the reticular expansion of Zr-MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗

Using Griffin's Transmutation Solver to Calculate Radiation Damage

Displacement Radiation Damage originates from all nuclides, not just those that are naturally occurring. Currently only damage from naturally-occurring nuclides, or sometimes damage from one transmutation product is considered. It is proposed that the transmutation solvers implemented in many codes be used to calculate this radiation damage. This would explicitly treat damage from all sources without additionally burdening the user. A proof-of-concept implementation was created in Griffin. The implementation showed that only minor code modifications are necessary to add this feature. When compared against an analytical benchmark the results Griffin could calculate were very accurate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Quantum Monte Carlo Study of the Structural, Energetic, and Magnetic Properties of Two-Dimensional H and T Phase VSe 2

Previous works have controversially claimed near-room-temperature ferromagnetism in two-dimensional (2D) VSe 2 , with conflicting results throughout the literature. These discrepancies in magnetic properties between both phases (T and H) of 2D VSe 2 are most likely due to the structural parameters being coupled to the magnetic properties. Specifically, both phases have a close lattice match and similar total energies, which makes it difficult to determine which phase is being observed experimentally. Here, in this study, we used a combination of density functional theory, highly accurate diffusion Monte Carlo (DMC), and a surrogate Hessian line-search optimization technique to resolve the previously reported discrepancy in structural parameters and relative phase stability. With DMC accuracy, we determined the free-standing geometry of both phases and constructed a phase diagram. Our findings demonstrate the successes of the DMC method coupled with the surrogate Hessian structural optimization technique when applied to a 2D magnetic system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A level-set immersed boundary method for reactive transport in complex topologies with moving interfaces

A simulation framework based on the level-set and the immersed boundary methods (LS-IBM) has been developed for reactive transport problems in porous media involving a moving solid-fluid interface. The interface movement due to surface reactions is tracked by the level-set method, while the immersed boundary method captures the momentum and mass transport at the interface. The proposed method is capable of accurately modeling transport near evolving boundaries in Cartesian grids. The framework formulation guarantees second order accuracy in space. Since the interface velocity is only defined at the moving boundary, an interface velocity propagation method is also proposed. The method can be applied to other moving interface problems of the “Stefan” type. Here, we validate the proposed LS-IBM both for flow and transport close to an immersed object with reactive boundaries as well as for crystal growth. Lastly, the proposed method provides a powerful tool to model more realistic problems involving moving reactive interfaces in complex domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimizing Batch Crystallization with Model-based Design of Experiments

Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.

Lynch, Hailey↗

Mathematical nuances of Gaussian process-driven autonomous experimentation

Abstract The fields of machine learning (ML) and artificial intelligence (AI) have transformed almost every aspect of science and engineering. The excitement for AI/ML methods is in large part due to their perceived novelty, as compared to traditional methods of statistics, computation, and applied mathematics. But clearly, all methods in ML have their foundations in mathematical theories, such as function approximation, uncertainty quantification, and function optimization. Autonomous experimentation is no exception; it is often formulated as a chain of off-the-shelf tools, organized in a closed loop, without emphasis on the intricacies of each algorithm involved. The uncomfortable truth is that the success of any ML endeavor, and this includes autonomous experimentation, strongly depends on the sophistication of the underlying mathematical methods and software that have to allow for enough flexibility to consider functions that are in agreement with particular physical theories. We have observed that standard off-the-shelf tools, used by many in the applied ML community, often hide the underlying complexities and therefore perform poorly. In this paper, we want to give a perspective on the intricate connections between mathematics and ML, with a focus on Gaussian process-driven autonomous experimentation. Although the Gaussian process is a powerful mathematical concept, it has to be implemented and customized correctly for optimal performance. We present several simple toy problems to explore these nuances and highlight the importance of mathematical and statistical rigor in autonomous experimentation and ML. One key takeaway is that ML is not, as many had hoped, a set of agnostic plug-and-play solvers for everyday scientific problems, but instead needs expertise and mastery to be applied successfully. Graphical abstract

97 MATHEMATICS AND COMPUTING↗

Electron–Nucleus Hyperfine Coupling Calculated from Restricted Active Space Wavefunctions and an Exact Two-Component Hamiltonian

Exact two-component (X2C) relativistic nuclear hyperfine magnetic field operators were incorporated in X2C ab-initio wavefunction calculations at the multi-reference restricted active space (RAS) level for calculations of nuclear hyperfine magnetic properties. Spin-orbit coupling was treated via RAS state interaction (SO-RASSI). The method was tested by calculations of electron – nucleus hyperfine coupling constants. The approach, implemented in the OpenMolcas program, overcomes a major limitation of a previous SO-RASSI implementation for hyperfine coupling that relied on non-relativistic hyperfine operators [J. Chem. Theor. Comput. 2015, 11, 538–549] and therefore had only limited applicability. Furthermore, results from calculations on systems with light and heavy main group elements, transition metals, lanthanides, and one actinide complex, demonstrate reasonably good agreement with experimental data, where available, as long as the active space can generate sufficient spin polarization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of Above-Room-Temperature Superconductivity in Lanthanide/Actinide Extreme Superhydrides

Achieving superconductivity at or above room temperature has been a century long held dream for physicists since the discovery of superconductivity in mercury in 1911. Following the recent predictions and ensuing synthesis of clathrate superhydride LaH 10 under pressure exhibiting extraordinary superconducting critical temperatures (T c ) of 250 260 K, we predict via advanced crystal structure search methods a new class of extremely hydrogen rich clathrate superhydrides. These MH 18 (M: rare earth/actinide metal atom) stoichiometric compounds consisting of H36 cage networks are predicted to host T c values above room temperature up to 330 K at pressures of 350 GPa. The bonding and electronic properties of these MH 18 clathrate superhydrides parallel those of atomic metallic hydrogen, giving rise to the highest superconducting temperatures predicted thus far for a thermodynamically stable hydride compound. In depth examination of these extreme superhydrides offers key insights for elucidating and further exploring phonon mediated superconductivity above room temperature in hydrogen rich and other low Z materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Relativistic coupled‐cluster and equation‐of‐motion coupled‐cluster methods

Abstract The development of relativistic coupled‐cluster (CC) and equation‐of‐motion coupled‐cluster (EOM‐CC) methods is reviewed. An emphasis is placed on recent efforts to improve the computational efficiency of CC and EOM‐CC calculations with non‐perturbative treatments of spin‐orbit coupling (SO‐CC and EOM‐CC) by partially recovering spin symmetry in the formulations. Example calculations of electronic ground state as well as valence‐excited and core‐excited states for molecules containing heavy elements are presented to demonstrate the applicability and usefulness of the SO‐CC and EOM‐CC methods. Future directions for the development of the SO‐CC and EOM‐CC methods are also discussed. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Methods for Modeling Electrospray Microdroplet Chemistry for Improved Quantitative Mass Spectrometry

This project aimed at enhancing the quantitative analysis capabilities of electrospray ionization mass spectrometry (ESI-MS) by developing advanced computational methods. The primary focus was to integrate continuum and molecular dynamics simulations to study the behavior of microdroplets in the ESI process, from formation to evaporation. Through this research, we sought to bridge significant length and time scales to provide a comprehensive understanding of how analyte concentrations evolve from bulk solutions into gas-phase ions. This understanding is crucial for addressing challenges such as ionization efficiency, solvent effects, and ion suppression, which currently limit the accuracy of quantitative ESI-MS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Importance of Dispersion in the Molecular Geometries of Mn(III) Spin-Crossover Complexes

The computational investigation of the molecular geometries of a pair of manganese(III) spin-crossover complexes is reported. For the geometry of the quintet high-spin state, density functionals significantly overestimate Mn–Namine bond distances, although the geometry for the triplet intermediate-spin state is well described. Here, comparisons with several wave function-based methods demonstrate that this error is due to the limited ability of commonly used density functionals to recover dispersion beyond a certain extent. Among the methods employed for geometry optimization, restricted open-shell Møller–Plesset perturbation theory (MP2) appropriately describes the high-spin geometry but results in a slightly shorter Mn–O distance in both spin states. On the other hand, extended multistate complete active space second-order perturbation theory (XMS-CASPT2) provides a good description of the geometry for the intermediate-spin state but also sufficiently recovers dispersion, performing well for the high-spin state. Despite the fact that the electronic structure of both spin states is dominated by one-electron configuration, XMS-CASPT2 offers a balanced approach, leading to molecular geometries with much better agreement with experiment than MP2 and DFT. A scan along the Mn–N amine bond demonstrates that for these complexes coupled cluster methods (i.e., DLPNO-CCSD(T)) also yield bond distances in agreement with experiment while multiconfiguration pair density functional theory (MC-PDFT) is unable to recover dispersion well enough, analogous to single-reference DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Embedding hard physical constraints in neural network coarse-graining of three-dimensional turbulence

In recent years, deep learning approaches have shown much promise in modeling complex systems in the physical sciences. A major challenge in deep learning of partial differential equations is enforcing physical constraints and boundary conditions. In this work, we propose a general framework to directly embed the notion of an incompressible fluid into convolutional neural networks, and apply this to coarse-graining of turbulent flow. These physics-embedded neural networks leverage interpretable strategies from numerical methods and computational fluid dynamics to enforce physical laws and boundary conditions by taking advantage the mathematical properties of the underlying equations. Here, we demonstrate results on three-dimensional fully developed turbulence, showing that this technique drastically improves local conservation of mass, without sacrificing performance according to several other metrics characterizing the fluid flow.

97 MATHEMATICS AND COMPUTING↗

Asymptotic preserving methods for fluid electron-fluid models in the large magnetic field limit with mathematically guaranteed properties (Final Report)

The current manuscript is a final report on the activities carried out under the Project LDRD-CIS #226834. In scientific terms, the work reported in this manuscript is a continuation of the efforts started with Project LDRD-express #223796 with final report of activities SAND2021-11481, see [83]. In this section we briefly explain what pre-existing developments motivated the current body of work and provide an overview of the activities developed with the funds provided. The overarching goal of the current project LDRD-CIS #226834 and the previous project LDRD-express #223796 is the development of numerical methods with mathematically guaranteed properties in order to solve the Euler-Maxwell system of plasma physics and generalizations thereof. Even though Project #223796 laid out general foundations of space and time discretization of Euler-Maxwell system, overall, it was focused on the development of numerical schemes for purely electrostatic fluid-plasma models. In particular, the project developed a family of schemes with mathematically guaranteed robustness in order to solve the Euler-Poisson model. This model is an asymptotic limit where only electrostatic response of the plasma is considered. Its primary feature is the presence of a non-local force, the electrostatic force, which introduces effects with infinite speed propagation into the problem. Even though instantaneous propagation of perturbations may be considered nonphysical, there are plenty of physical regimes of technical interest where such an approximation is perfectly valid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗