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At least 1,153 records · Page 64

Identifying the Gate-Opening Mechanism in the Flexible Metal–Organic Framework UTSA-300

Atomic-level understanding of the gate-opening phenomenon in flexible porous materials is an important step toward learning how to control, design, and engineer them for applications such as the separation of gases from complex mixtures. Here, we report such mechanistic insight through an in-depth study of the pressure-induced gate-opening phenomenon in our earlier reported metal–organic framework (MOF) Zn(dps) 2 (SiF 6 ) (dps = 4,4'-dipyridylsulfide), also called UTSA-300, using isotherm and calorimetry measurements, in situ infrared spectroscopy, and ab initio simulations. UTSA-300 is shown to selectively adsorb acetylene (C 2 H 2 ) over ethylene (C 2 H 4 ) and ethane (C 2 H 6 ) and undergoes an abrupt gate-opening phenomenon, making this framework a highly selective gas separator of this complex mixture. The selective adsorption is confirmed by pressure-dependent in situ infrared spectroscopy, which, for the first time, shows the presence of multiple C 2 H 2 species with varying strengths of bonding. A rare energetic feature at the gate-opening condition of the flexible MOF is observed in our differential heat energies, directly measured by calorimetry, showcasing the importance of this tool in adsorption property exploration of flexible frameworks and offering an energetic benchmark for further energy-based fundamental studies. Based on the agreement of this feature with ab initio-based adsorption energies of C 2 H 2 in the closed-pore structure UTSA-300a (“a” refers to the activated form), this feature is assigned to the weakening of the H-bond C–H···F formed between C 2 H 2 and fluorine of the MOF. Furthermore, our analysis identifies the weakening of this H-bond, the expansion of the closed-pore MOF upon successive C 2 H 2 coadsorption until its volume is close to that of the open-pore MOF, and the spontaneous gate opening to energetically favor C 2 H 2 adsorption in the open-pore structure as crucial steps in the gate-opening mechanism in this system.

36 MATERIALS SCIENCE↗

Leveraging Nitrogen Linkages in the Formation of a Porous Thorium–Organic Nanotube Suitable for Iodine Capture

We report the synthesis, characterization, and iodine capture application of a novel thorium–organic nanotube, TSN-626, [Th 6 O 4 (OH) 4 (C 6 H 4 NO 2 ) 7 (CHO 2 ) 5 (H 2 O) 3 ]·3H 2 O. The classification as a metal–organic nanotube (MONT) distinguishes it as a rare and reduced dimensionality subset of metal–organic frameworks (MOFs); the structure is additionally hallmarked by low node connectivity. TSN-626 is composed of hexameric thorium secondary building units and mixed O/N-donor isonicotinate ligands that demonstrate selective ditopicity, yielding both terminating and bridging moieties. Because hard Lewis acid tetravalent metals have a propensity to bind with electron donors of rival hardness (e.g., carboxylate groups), such Th–N coordination in a MOF is uncommon. However, the formation of key structural Th–N bonds in TSN-626 cap some of the square antiprismatic metal centers, a position usually occupied by terminal water ligands. TSN-626 was characterized by using complementary analytical and computational techniques: X-ray diffraction, vibrational spectroscopy, N 2 physisorption isotherms, and density functional theory. TSN-626 satisfies design aspects for the chemisorption of iodine. The synergy between accessibility through pores, vacancies at the metal–oxo nodes, and pendent N-donor sites allowed a saturated iodine loading of 955 mg g –1 by vapor methods. Furthermore, the crystallization of TSN-626 diversifies actinide–MOF linker selection to include soft electron donors, and these Th–N linkages can be leveraged for the investigation of metal-to-ligand bonding and unconventional topological expressions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evidence of Long-Range and Short-Range Magnetic Ordering in the Honeycomb Na 3 Mn 2 SbO 6 Oxide

We present a comprehensive study of the synthesis, structure, and magnetic properties of the honeycomb oxide Na 3 Mn 2 SbO 6 supported by neutron diffraction, heat capacity, and magnetization measurements. The refinements of the neutron diffraction patterns (150, 50, and 45 K) using the Rietveld method confirm the monoclinic (S. G. C2/m) structure. Temperature-dependent magnetic susceptibilities measured at varying fields along with the heat capacity measurements demonstrate the coexistence of long-range ordering (∼42 K) and short-range ordering (∼65 K). The field-dependent isothermal magnetization measurements at 5 K indicate a spin-flop transition around 5 T. Rietveld refinements of the low-temperature (below 45 K) neutron diffraction data further confirm the long-range magnetic ordering. In addition, the temperature variation of the lattice parameters obtained from the neutron powder diffraction analysis exhibited a distinct anomaly near the antiferromagnetic transition temperature. The appearance of the concomitant broadened backgrounds in the neutron powder diffraction data collected at 80, 50, and 45 K supports the short-range ordering. The resultant magnetic structure consists of spins that are aligned antiparallel with the nearest neighbors and also with the spins of the adjacent honeycomb layers. The occurrence of a fully ordered magnetic ground state (Neel antiferromagnetic (AFM)) in Na3Mn 2 SbO 6 consolidates the significance of fabricating new honeycomb oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ATCUN-like Copper Site in βB2-Crystallin Plays a Protective Role in Cataract-Associated Aggregation

Cataract is the leading cause of blindness worldwide, and it is caused by crystallin damage and aggregation. Senile cataractous lenses have relatively high levels of metals, while some metal ions can directly induce the aggregation of human γ-crystallins. Here, for this work, we evaluated the impact of divalent metal ions in the aggregation of human βB2-crystallin, one of the most abundant crystallins in the lens. Turbidity assays showed that Pb 2+ , Hg 2+ , Cu 2+ , and Zn 2+ ions induce the aggregation of βB2-crystallin. Metal-induced aggregation is partially reverted by a chelating agent, indicating the formation of metal-bridged species. Our study focused on the mechanism of copper-induced aggregation of βB2-crystallin, finding that it involves metal-bridging, disulfide-bridging, and loss of protein stability. Circular dichroism and electron paramagnetic resonance (EPR) revealed the presence of at least three Cu 2+ binding sites in βB2-crystallin, one of them with spectroscopic features typical for Cu 2+ bound to an amino-terminal copper and nickel (ATCUN) binding motif, which is found in Cu transport proteins. The ATCUN-like Cu binding site is located at the unstructured N-terminus of βB2-crystallin, and it could be modeled by a peptide with the first six residues in the protein sequence (NH 2 -ASDHQF-). Isothermal titration calorimetry indicates a nanomolar Cu 2+ binding affinity for the ATCUN-like site. An N-truncated form of βB2-crystallin is more susceptible to Cu-induced aggregation and is less thermally stable, indicating a protective role for the ATCUN-like site. EPR and X-ray absorption spectroscopy studies reveal the presence of a copper redox active site in βB2-crystallin that is associated with metal-induced aggregation and formation of disulfide-bridged oligomers. Our study demonstrates metal-induced aggregation of βB2-crystallin and the presence of putative copper binding sites in the protein. Whether the copper-transport ATCUN-like site in βB2-crystallin plays a functional/protective role or constitutes a vestige from its evolution as a lens structural protein remains to be elucidated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of a Large Magnetic Anisotropy and a Field-Induced Magnetic State in SrCo(VO 4 )(OH): A Structure with a Quasi One-Dimensional Magnetic Chain

A new member of the descloizite family, a cobalt vanadate, SrCo(VO 4 )(OH), has been synthesized as large single crystals using high-temperature and high-pressure hydrothermal methods. SrCo(VO 4 )(OH) crystallizes in the orthorhombic crystal system in space group P 2 1 2 1 2 1 with the following unit cell parameters: a = 6.0157(2) Å, b = 7.645(2) Å, c = 9.291(3) Å, V = 427.29(2) Å 3 , and Z = 4. It contains one-dimensional Co–O–Co chains of edge-sharing CoO 6 octahedra along the a -axis connected to each other via VO 4 tetrahedra along the b -axis forming a three-dimensional structure. The magnetic susceptibility of SrCo(VO 4 )(OH) indicates an antiferromagnetic transition at 10 K as well as unusually large spin orbit coupling. Single-crystal magnetic measurements in all three main crystallographic directions displayed a significant anisotropy in both temperature- and field-dependent data. Single-crystal neutron diffraction at 4 K was used to characterize the magnetically ordered state. The Co 2+ magnetic spins are arranged in a staggered configuration along the chain direction, with a canting angle that follows the tipping of the CoO 6 octahedra. The net magnetization along the chain direction, resulting in ferromagnetic coupling of the a -axis spin components in each chain, is compensated by an antiferromagnetic interaction between nearest neighbor chains. A metamagnetic transition appears in the isothermal magnetization data at 2 K along the chain direction, which seems to correspond to a co-alignment of the spin directions of the nearest neighbor chain. We propose a phenomenological spin Hamiltonian that describes the canted spin configuration of the ground state and the metamagnetic transition in SrCo(VO 4 )(OH).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Transferable Force Field for Simulating Adsorption in Metal–Organic Frameworks with Open Metal Sites Based on the 12–6–4 Lennard-Jones Potential

Metal−organic frameworks (MOFs) that contain coordinatively unsaturated open metal sites (OMSs) provide strong host− guest interactions, making them promising sorbents for low-concentration gas adsorption applications such as direct air capture and atmospheric water harvesting. However, accurately modeling host−guest interactions involving OMSs remains challenging for classical force fields (FFs) based on the 12−6 Lennard−Jones (LJ) potential, as the polarization effect of the guest molecule induced by the positively charged OMS is not considered. Here, we introduce an FF based on the 12−6−4 LJ potential, which incorporates charge−induced dipole interactions and is parametrized against a diverse set of host−guest potential energy surfaces (PESs) obtained from density functional theory (DFT). The resulting FF, trained on a generic trimetallic cluster, performs well in both host−guest binding energetics and gas adsorption isotherms across different OMS-containing MOFs, including MOF-74 series and Cu-BTC. These results highlight the excellent transferability of our approach and its potential to enhance the accuracy and robustness of high-throughput MOF discovery workflows, particularly for gas adsorption and separation in large and diverse MOF databases.

36 MATERIALS SCIENCE↗

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng↗

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗

Phase Change-Driven Negative Activation Energies in Pd/Carbon-Based/Organic Getter Hydrogenation Reactions

In this study, the hydrogenation of 1,4-diphenylbutadiyne (DPB) blended with carbon-supported Pd (DPB–Pd/C) in the form of pellets was investigated by isothermal–isobaric experiments at 1333 Pa of H 2 and in the temperature range of 291–315 K. The extracted kinetics were then used in conjunction with a complementary constant rate of H 2 input experimentation to model the performance of a DPB-catalysis/support system as a function of temperature and H 2 partial pressure. First-principles density functional theory (DFT) calculations were also performed to shed light on the molecular level energetics of DPB and its intermediate states. A seemingly puzzling formation of alternate positive activation energy barrier (higher reaction rate with higher temperature) and negative activation energy barrier (higher reaction rate with lower temperature) zones during the hydrogenation process was discovered. However, this observed phenomenon can be logically explained in terms of the associated phase changes and H 2 transport in the material. This work provides a good illustration of a rarely encountered chemical process with a negative activation energy barrier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural changes in liquid lithium under high-pressure

In this paper, we have experimentally studied the effect of compression on the structure of liquid lithium (Li) by multi-angle energy dispersive X-ray diffraction in a large-volume cupped-Drickamer-Toroidal cell. The structure factors, s(q), of liquid Li have been successfully determined under an isothermal compression at 600 ± 30 K and at pressures up to 11.5 GPa. The first peak position in s(q) is found to increase with increasing pressure and showing an obvious slope change starting at ~7.5 GPa. The slope change is interpreted as a structural change from bcc-like to fcc-like local ordering in liquid Li. At pressures above 8.7 GPa, the liquid Li becomes predominantly fcc-like up to the highest pressure of 11.5 GPa in this study. The observed structural changes in liquid Li are consistent with the recently determined melting curve of Li.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Liquid Water by Climbing up Jacob’s Ladder in Density Functional Theory Facilitated by Using Deep Neural Network Potentials

Within the framework of Kohn–Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric–isothermal ensemble. To generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained by using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed by using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water toward the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. However, some important discrepancies remain. The H-bond network predicted by the SCAN0 functional is still slightly overstructured compared to the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Relationships between Free Volume and Oxygen Absorption in Ionic Liquids

In this report understanding the factors that govern gas absorption in ionic liquids is critical to the development of high-capacity solvents for catalysis, electrochemistry, and gas separations. Here, we report experimental probes of liquid structure that provide insights into how free volume impacts the O 2 absorption properties of ionic liquids. Specifically, we establish that isothermal compressibility - measured rapidly and accurately through small-angle X-ray scattering - reports on the size distribution of transient voids within a representative series of ionic liquids and is correlated with O 2 absorption capacity. Additionally, O 2 absorption capacities are correlated with thermal expansion coefficients, reflecting the beneficial effect of weak intermolecular interactions in ionic liquids on free volume and gas absorption capacity. Molecular dynamics simulations show that the void size distribution - in particular, the probability of forming larger voids within an ionic liquid - has a greater impact on O 2 absorption than the total free volume. These results establish relationships between the ionic liquid structure and gas absorption properties that offer design strategies for ionic liquids with high gas solubilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature Effects in Flexible Adsorption Processes for Amorphous Microporous Polymers

A collection of atomistic molecular simulations is reported that illustrate the impact of adsorption temperature on species uptake and adsorbate-induced structural rearrangement for amorphous polymers of intrinsic microporosity. Temperature-sensitive structural rearrangement is evaluated by contrasting two methods: standard grand canonical Monte Carlo simulations using a rigid framework approximation and a combined Monte Carlo/molecular dynamics approach that fully incorporates framework flexibility. We report single-component gas phase adsorption isotherms for CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , C 3 H 8 , and CO 2 across a temperature range of 250–400 K for models of an archetypal polymer of intrinsic microporosity, PIM-1. A quadratic model is presented that captures two main mechanisms of temperature-dependent adsorption-induced deformation of PIM-1 up to a relative swelling of 1.15: thermal expansion and an increased propensity to swell as a function of species uptake. Two case studies are reported that highlight the critical role of operating temperature in industrial storage and separation applications. The first study focuses on methane storage and delivery applications using a pressure–temperature swing adsorption application (PTSA). We demonstrate that larger working capacities are accompanied by increased volumetric strain between adsorption–desorption steps. The second case study considers PIM-1 as an adsorbent to separate an exemplar ternary syngas mixture at operating temperatures ranging 300–550 K. Here, a temperature threshold of ~400 K is identified, beyond which adsorption-induced PIM-1 swelling is negligible and the solubility selectivity-loading curve transitions to exhibiting a nearly linear relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Modeling of Bromide and Iodide Hydration with Data-Driven Many-Body Potentials

Ion–water interactions play a central role in determining the properties of aqueous systems in a wide range of environments. However, a quantitative understanding of how the hydration properties of ions evolve from small aqueous clusters to bulk solutions and interfaces remains elusive. Here, we introduce the second generation of data-driven many-body energy (MBnrg) potential energy functions (PEFs) representing bromide–water and iodide–water interactions. The MB-nrg PEFs use permutationally invariant polynomials to reproduce two-body and three-body energies calculated at the coupled cluster level of theory, and implicitly represent all higher-body energies using classical many-body polarization. Further, a systematic analysis of the hydration structure of small Br - (H 2 O) n and I - (H 2 O) n clusters demonstrates that the MBnrg PEFs predict interaction energies in quantitative agreement with “gold standard” coupled cluster reference values. Importantly, when used in molecular dynamics simulations carried out in the isothermal-isobaric ensemble for single bromide and iodide ions in liquid water, the MB-nrg PEFs predict extended X-ray absorption fine structure (EXAFS) spectra that accurately reproduce the experimental spectra, which thus allows for characterizing the hydration structure of the two ions with high level of confidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Rotations, Multiscale Order, Hyperuniformity, and Signatures of Metastability during the Compression/Decompression Cycles of Amorphous Ices

We model, via large-scale molecular dynamics simulations, the isothermal compression of low-density amorphous ice (LDA) to generate high-density amorphous ice (HDA) and the corresponding decompression extending to negative pressures to recover the low-density amorphous phase (LDA HDA ). Both LDA and HDA are nearly hyperuniform and are characterized by a dynamical HBN, showing that amorphous ices are nonstatic materials and implying that nearly hyperuniformity can be accommodated in dynamical networks. In correspondence with both the LDA-to-HDA and the HDA-to-LDA HDA phase transitions, the (partial) activation of rotational degrees of freedom activates a cascade effect that induces a drastic change in the connectivity and a pervasive reorganization of the HBN topology which, ultimately, break the samples’ hyperuniform character. Key to this effect is the rapid rate at which changes occur, and not their magnitude. The inspection of structural properties from the short- to the long-range shows that signatures of metastability are present at all length-scales, hence providing further solid evidence in support of the liquid–liquid critical point scenario. LDA and LDA HDA differ in terms of HBN and structural properties, implying that they are distinct low-density glasses. Our work unveils the role of molecular rotations in the phase transitions between amorphous ices and shows how the unfreezing of rotational degrees of freedom generates a cascade effect that propagates over multiple length-scales. Our findings greatly improve our basic understanding of water and amorphous ices and can potentially impact the field of molecular network-forming materials at large.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modifying Specific Ion Effects: Studies of Monovalent Ion Interactions with Amines

Specific ion effects in the interactions of monovalent anions with amine groups-one of the hydrophilic moieties found in proteins-were investigated using octadecylamine monolayers floating at air–aqueous solution interfaces. Here, we find that at solution pH 5.7, larger monovalent anions induce a nonzero pressure starting at higher areas/molecules, i.e., a wider “liquid expanded” region in the monolayer isotherms. Using X-ray fluorescence at near total reflection (XFNTR), an element- and surface-specific technique, ion adsorption to the amines at pH 5.7 is confirmed to be ion-specific and to follow the conventional Hofmeister series. However, at pH 4, this ion specificity is no longer observed. We propose that at the higher pH, the amine headgroups are only partially protonated, and large polarizable ions such as iodine are better able to boost amine protonation. At the lower pH, on the other hand, the monolayer is fully protonated, and electrostatic interactions dominate over ion specificity. These results demonstrate that ion specificity can be modified by changing the experimental conditions.

36 MATERIALS SCIENCE↗