Diversity-oriented synthesis of polymer membranes with ion solvation cages.

Microporous polymers feature shape-persistent free volume elements (FVEs), which are permeated by small molecules and ions when used as membranes for chemical separations, water purification, fuel cells and batteries1-3. Identifying FVEs that have analyte specificity remains a challenge, owing to difficulties in generating polymers with sufficient diversity to enable screening of their properties. Here we describe a diversity-oriented synthetic strategy for microporous polymer membranes to identify candidates featuring FVEs that serve as solvation cages for lithium ions (Li+). This strategy includes diversification of bis(catechol) monomers by Mannich reactions to introduce Li+-coordinating functionality within FVEs, topology-enforcing polymerizations for networking FVEs into different pore architectures, and several on-polymer reactions for diversifying pore geometries and dielectric properties. The most promising candidate membranes featuring ion solvation cages exhibited both higher ionic conductivity and higher cation transference number than control membranes, in which FVEs were aspecific, indicating that conventional bounds for membrane permeability and selectivity for ion transport can be overcome4. These advantages are associated with enhanced Li+ partitioning from the electrolyte when cages are present, higher diffusion barriers for anions within pores, and network-enforced restrictions on Li+ coordination number compared to the bulk electrolyte, which reduces the effective mass of the working ion. Such membranes show promise as anode-stabilizing interlayers in high-voltage lithium metal batteries.

Formation, chemical evolution and solidification of the dense liquid phase of calcium (bi)carbonate.

Metal carbonates, which are ubiquitous in the near-surface mineral record, are a major product of biomineralizing organisms and serve as important targets for capturing anthropogenic CO2 emissions. However, pathways of carbonate mineralization typically diverge from classical predictions due to the involvement of disordered precursors, such as the dense liquid phase (DLP), yet little is known about DLP formation or solidification processes. Using in situ methods we report that a highly hydrated bicarbonate DLP forms via liquid-liquid phase separation and transforms into hollow hydrated amorphous CaCO3 particles. Acidic proteins and polymers extend DLP lifetimes while leaving the pathway and chemistry unchanged. Molecular simulations suggest that the DLP forms via direct condensation of solvated Ca²+⋅(HCO3-)2 complexes that react due to proximity effects in the confined DLP droplets. Our findings provide insight into CaCO3 nucleation that is mediated by liquid-liquid phase separation, advancing the ability to direct carbonate mineralization and elucidating an often-proposed complex pathway of biomineralization.

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation.

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of very large-scale computational discovery carried out through experimental validation remain scarce, especially for materials with product applicability. Here, we demonstrate how this vision became reality by combining state-of-the-art machine learning (ML) models and traditional physics-based models on cloud high-performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. By focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade's worth of collective knowledge in the field as a byproduct. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the NaxLi3-xYCl6 (0≤ x≤ 3) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials that are currently under experimental investigation could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. The showcased screening of millions of materials candidates highlights the transformative potential of advanced ML and HPC methodologies, propelling materials discovery into a new era of efficiency and innovation.

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries.

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure-property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg2+ (with time scales ranging from 0.5 µs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. This observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

Energy storage emerging: A perspective from the Joint Center for Energy Storage Research.

Energy storage is an integral part of modern society. A contemporary example is the lithium (Li)-ion battery, which enabled the launch of the personal electronics revolution in 1991 and the first commercial electric vehicles in 2010. Most recently, Li-ion batteries have expanded into the electricity grid to firm variable renewable generation, increasing the efficiency and effectiveness of transmission and distribution. Important applications continue to emerge including decarbonization of heavy-duty vehicles, rail, maritime shipping, and aviation and the growth of renewable electricity and storage on the grid. This perspective compares energy storage needs and priorities in 2010 with those now and those emerging over the next few decades. The diversity of demands for energy storage requires a diversity of purpose-built batteries designed to meet disparate applications. Advances in the frontier of battery research to achieve transformative performance spanning energy and power density, capacity, charge/discharge times, cost, lifetime, and safety are highlighted, along with strategic research refinements made by the Joint Center for Energy Storage Research (JCESR) and the broader community to accommodate the changing storage needs and priorities. Innovative experimental tools with higher spatial and temporal resolution, in situ and operando characterization, first-principles simulation, high throughput computation, machine learning, and artificial intelligence work collectively to reveal the origins of the electrochemical phenomena that enable new means of energy storage. This knowledge allows a constructionist approach to materials, chemistries, and architectures, where each atom or molecule plays a prescribed role in realizing batteries with unique performance profiles suitable for emergent demands.

Multi-Step Nucleation of a Crystalline Silicate Framework via a Structurally Precise Prenucleation Cluster.

Hierarchical nucleation pathways are ubiquitous in the synthesis of minerals and materials. In the case of zeolites and metal-organic frameworks, pre-organized multi-ion "secondary building units" (SBUs) have been proposed as fundamental building blocks. However, detailing the progress of multi-step reaction mechanisms from monomeric species to stable crystals and defining the structures of the SBUs remains an unmet challenge. Combining in situ nuclear magnetic resonance, small-angle X-ray scattering, and atomic force microscopy, we show that crystallization of the framework silicate, cyclosilicate hydrate, occurs through an assembly of cubic octameric Q3 8 polyanions formed through cross-linking and polymerization of smaller silicate monomers and other oligomers. These Q3 8 are stabilized by hydrogen bonds with surrounding H2 O and tetramethylammonium ions (TMA+ ). When Q3 8 levels reach a threshold of ≈32 % of the total silicate species, nucleation occurs. Further growth proceeds through the incorporation of [(TMA)x (Q3 8 )⋅n H2 O](x-8) clathrate complexes into step edges on the crystals.

Concentration-dependent ion correlations impact the electrochemical behavior of calcium battery electrolytes.

Ion interactions strongly determine the solvation environments of multivalent electrolytes even at concentrations below that required for practical battery-based energy storage. This statement is particularly true of electrolytes utilizing ethereal solvents due to their low dielectric constants. These solvents are among the most commonly used for multivalent batteries based on reactive metals (Mg, Ca) due to their reductive stability. Recent developments in multivalent electrolyte design have produced a variety of new salts for Mg2+ and Ca2+ that test the limits of weak coordination strength and oxidative stability. Such electrolytes have great potential for enabling full-cell cycling of batteries based on these working ions. However, the ion interactions in these electrolytes exhibit significant and non-intuitive concentration relationships. In this work, we investigate a promising exemplar, calcium tetrakis(hexafluoroisopropoxy)borate (Ca(BHFIP)2), in the ethereal solvents 1,2-dimethoxyethane (DME) and tetrahydrofuran (THF) across a concentration range of several orders of magnitude. Surprisingly, we find that effective salt dissociation is lower at relatively dilute concentrations (e.g. 0.01 M) than at higher concentrations (e.g. 0.2 M). Combined experimental and computational dielectric and X-ray spectroscopic analyses of the changes occurring in the Ca2+ solvation environment across these concentration regimes reveals a progressive transition from well-defined solvent-separated ion pairs to de-correlated free ions. This transition in ion correlation results in improvements in both conductivity and calcium cycling stability with increased salt concentration. Comparison with previous findings involving more strongly associating salts highlights the generality of this phenomenon, leading to important insight into controlling ion interactions in ether-based multivalent battery electrolytes.

Variable Temperature and Pressure Operando MAS NMR for Catalysis Science and Related Materials.

The characterization of catalytic materials under working conditions is of paramount importance for a realistic depiction and comprehensive understanding of the system. Under such relevant environments, catalysts often exhibit properties or reactivity not observed under standard spectroscopic conditions. Fulfilling such harsh environments as high temperature and pressure is a particular challenge for solid-state NMR where samples spin several thousand times a second within a strong magnetic field. To address concerns about the disparities between spectroscopic environments and operando conditions, novel MAS NMR technology has been developed that enables the probing of catalytic systems over a wide range of pressures, temperatures, and chemical environments. In this Account, new efforts to overcome the technical challenges in the development of operando and in situ MAS NMR will be briefly outlined. Emphasis will be placed on exploring the unique chemical regimes that take advantage of the new developments. With the progress achieved, it is possible to interrogate both structure and dynamics of the environments surrounding various nuclear constituents (1H, 13C, 23Na, 27Al, etc.), as well as assess time-resolved interactions and transformations.Operando and in situ NMR enables the direct observation of chemical components and their interactions with active sites (such as Brønsted acid sites on zeolites) to reveal the nature of the active center under catalytic conditions. Further, mixtures of such constituents can also be assessed to reveal the transformation of the active site when side products, such as water, are generated. These interactions are observed across a range of temperatures (-10 to 230 °C) and pressures (vacuum to 100 bar) for both vapor and condensed phase analysis. When coupled with 2D NMR, computational modeling, or both, specific binding modes are identified where the adsorbed state provides distinct signatures. In addition to vapor phase chemical environments, gaseous environments can be introduced and controlled over a wide range of pressures to support catalytic studies that require H2, CO, CO2, etc. Mixtures of three phases may also be employed. Such reactions can be monitored in situ to reveal the transformation of the substrates, active sites, intermediates, and products over the course of the study. Further, coupling of operando NMR with isotopic labeling schemes reveals specific mechanistic insights otherwise unavailable. Examples of these strategies will be outlined to reveal important fundamental insights on working catalyst systems possible only under operando conditions. Extension of operando MAS NMR to study the solid-electrolyte interface and solvation structures associated with energy storage systems and biomedical systems will also be presented to highlight the versatility of this powerful technique.

Monitoring solvent dynamics and ion associations in the formation of cubic octamer polyanion in tetramethylammonium silicate solutions.

NMR methods were utilized to monitor the in situ structural and dynamic changes of various species in highly alkaline tetramethylammonium (TMA) silicate solutions. Quantitative 29Si NMR, 1H, 2H, and 17O relaxation NMR, and 1H and 29Si diffusion NMR of silicates, TMA, H2O and D2O demonstrate that the growth of the cubic octamer Q38 is accompanied by reduced water mobility and increasing TMA coordination number per Q38, which reaches an equilibrium value of 4.5 at 15 °C. Temperature-dependent measurements further reveal that the increased control over speciation by TMA at lower temperatures results from the more stable ion associations via slower solvent motions.

A novel high-temperature MAS probe with optimized temperature gradient across sample rotor for in-situ monitoring of high-temperature high-pressure chemical reactions.

We present a novel nuclear magnetic resonance (NMR) probe design focused on optimizing the temperature gradient across the sample for high temperature magic angle spinning (MAS) experiments using standard rotors. Computational flow dynamics (CFD) simulations were used to assess and optimize the temperature gradient across the sample under MAS conditions. The chemical shift and linewidth of 207Pb direct polarization in lead nitrate were used to calibrate the sample temperature and temperature gradient, respectively. A temperature gradient of less than 3 °C across the sample was obtained by heating bearing gas flows and adjusting its temperature and flow rate during variable temperature (VT) experiments. A maximum temperature of 350 °C was achieved in this probe using a Varian 5 mm MAS rotor with standard Vespel drive tips and end caps. Time-resolved 13C and 1H MAS NMR experiments were performed at 325 °C and 60 bar to monitor an in-situ mixed phase reverse water gas shift reaction, industrial synthesis of CH3OH from a mixture of CO2 and H2 with a Cu/ZnO/Al2O3 catalyst, demonstrating the first in-situ NMR monitoring of a chemical system at temperatures higher than 250 °C in a pressurized environment. The combination of this high-temperature probe and high-pressure rotors will allow for in-situ NMR studies of a great variety of chemical reactions that are inaccessible to conventional NMR setup.

Mechanism by which Tungsten Oxide Promotes the Activity of Supported V2 O5 /TiO2 Catalysts for NOX Abatement: Structural Effects Revealed by 51 V MAS NMR Spectroscopy.

The selective catalytic reduction (SCR) of NOx with NH3 to N2 with supported V2 O5 (-WO3 )/TiO2 catalysts is an industrial technology used to mitigate toxic emissions. Long-standing uncertainties in the molecular structures of surface vanadia are clarified, whereby progressive addition of vanadia to TiO2 forms oligomeric vanadia structures and reveals a proportional relationship of SCR reaction rate to [surface VOx concentration]2 , implying a 2-site mechanism. Unreactive surface tungsta (WO3 ) also promote the formation of oligomeric vanadia (V2 O5 ) sites, showing that promoter incorporation enhances the SCR reaction by a structural effect generating adjacent surface sites and not from electronic effects as previously proposed. The findings outline a method to assess structural effects of promoter incorporation on catalysts and reveal both the dual-site requirement for the SCR reaction and the important structural promotional effect that tungsten oxide offers for the SCR reaction by V2 O5 /TiO2 catalysts.

Improving Lithium-Sulfur Battery Performance under Lean Electrolyte through Nanoscale Confinement in Soft Swellable Gels.

Li-S batteries have been extensively studied using rigid carbon as the host for sulfur encapsulation, but improving the properties with a reduced electrolyte amount remains a significant challenge. This is critical for achieving high energy density. Here, we developed a soft PEO10LiTFSI polymer swellable gel as a nanoscale reservoir to trap the polysulfides under lean electrolyte conditions. The PEO10LiTFSI gel immobilizes the electrolyte and confines polysulfides within the ion conducting phase. The Li-S cell with a much lower electrolyte to sulfur ratio (E/S) of 4 gE/gS (3.3 mLE/gS) could deliver a capacity of 1200 mA h/g, 4.6 mA h/cm2, and good cycle life. The accumulation of polysulfide reduction products, such as Li2S, on the cathode, is identified as the potential mechanism for capacity fading under lean electrolyte conditions.

Calculations of solid-state 43 Ca NMR parameters: A comparison of periodic and cluster approaches and an evaluation of DFT functionals.

We present a computational study of magnetic-shielding and quadrupolar-coupling tensors of 43 Ca sites in crystalline solids. A comparison between periodic and cluster-based approaches for modeling solid-state interactions demonstrates that cluster-based approaches are suitable for predicting 43 Ca NMR parameters. Several model chemistries, including Hartree-Fock theory and 17 DFT approximations (SVWN, CA-PZ, PBE, PBE0, PW91, B3PW91, rPBE, PBEsol, WC, PKZB, BMK, M06-L, M06, M06-2X, M06-HF, TPSS, and TPSSh), are evaluated for the prediction of 43 Ca NMR parameters. Convergence of NMR parameters with respect to basis sets of the form cc-pVXZ (X = D, T, Q) is also evaluated. All DFT methods lead to substantial, and frequently systematic, overestimations of experimental chemical shifts. Hartree-Fock calculations outperform all DFT methods for the prediction of 43 Ca chemical-shift tensors. © 2017 Wiley Periodicals, Inc.

Surface Interactions and Confinement of Methane: A High Pressure Magic Angle Spinning NMR and Computational Chemistry Study.

Characterization and modeling of the molecular-level behavior of simple hydrocarbon gases, such as methane, in the presence of both nonporous and nanoporous mineral matrices allows for predictive understanding of important processes in engineered and natural systems. In this study, changes in local electromagnetic environments of the carbon atoms in methane under conditions of high pressure (up to 130 bar) and moderate temperature (up to 346 K) were observed with 13C magic-angle spinning (MAS) NMR spectroscopy while the methane gas was mixed with two model solid substrates: a fumed nonporous, 12 nm particle size silica and a mesoporous silica with 200 nm particle size and 4 nm average pore diameter. Examination of the interactions between methane and the silica systems over temperatures and pressures that include the supercritical regime was allowed by a novel high pressure MAS sample containment system, which provided high resolution spectra collected under in situ conditions. For pure methane, no significant thermal effects were found for the observed 13C chemical shifts at all pressures studied here (28.2, 32.6, 56.4, 65.1, 112.7, and 130.3 bar). However, the 13C chemical shifts of resonances arising from confined methane changed slightly with changes in temperature in mixtures with mesoporous silica. The chemical shift values of 13C nuclides in methane change measurably as a function of pressure both in the pure state and in mixtures with both silica matrices, with a more pronounced shift when meso-porous silica is present. Molecular-level simulations utilizing GCMC, MD, and DFT confirm qualitatively that the experimentally measured changes are attributed to interactions of methane with the hydroxylated silica surfaces as well as densification of methane within nanopores and on pore surfaces.

Uranium Release from Acidic Weathered Hanford Sediments: Single-Pass Flow-Through and Column Experiments.

The reaction of acidic radioactive waste with sediments can induce mineral transformation reactions that, in turn, control contaminant fate. Here, sediment weathering by synthetic uranium-containing acid solutions was investigated using bench-scale experiments to simulate waste disposal conditions at Hanford's cribs (Hanford, WA). During acid weathering, the presence of phosphate exerted a strong influence over uranium mineralogy and a rapidly precipitated, crystalline uranium phosphate phase (meta-ankoleite [K(UO2)(PO4)·3H2O]) was identified using spectroscopic and diffraction-based techniques. In phosphate-free system, uranium oxyhydroxide minerals such as K-compreignacite [K2(UO2)6O4(OH)6·7H2O] were formed. Single-pass flow-through (SPFT) and column leaching experiments using synthetic Hanford pore water showed that uranium precipitated as meta-ankoleite during acid weathering was strongly retained in the sediments, with an average release rate of 2.67 × 10-12 mol g-1 s-1. In the absence of phosphate, uranium release was controlled by dissolution of uranium oxyhydroxide (compreignacite-type) mineral with a release rate of 1.05-2.42 × 10-10 mol g-1 s-1. The uranium mineralogy and release rates determined for both systems in this study support the development of accurate U-release models for the prediction of contaminant transport. These results suggest that phosphate minerals may be a good candidate for uranium remediation approaches at contaminated sites.

Toward high-resolution NMR spectroscopy of microscopic liquid samples.

A longstanding limitation of high-resolution NMR spectroscopy is the requirement for samples to have macroscopic dimensions. Commercial probes, for example, are designed for volumes of at least 5 µL, in spite of decades of work directed toward the goal of miniaturization. Progress in miniaturizing inductive detectors has been limited by a perceived need to meet two technical requirements: (1) minimal separation between the sample and the detector, which is essential for sensitivity, and (2) near-perfect magnetic-field homogeneity at the sample, which is typically needed for spectral resolution. The first of these requirements is real, but the second can be relaxed, as we demonstrate here. By using pulse sequences that yield high-resolution spectra in an inhomogeneous field, we eliminate the need for near-perfect field homogeneity and the accompanying requirement for susceptibility matching of microfabricated detector components. With this requirement removed, typical imperfections in microfabricated components can be tolerated, and detector dimensions can be matched to those of the sample, even for samples of volume ≪5 µL. Pulse sequences that are robust to field inhomogeneity thus enable small-volume detection with optimal sensitivity. We illustrate the potential of this approach to miniaturization by presenting spectra acquired with a flat-wire detector that can easily be scaled to subnanoliter volumes. In particular, we report high-resolution NMR spectroscopy of an alanine sample of volume 500 pL.

High-resolution microstrip NMR detectors for subnanoliter samples.

We present the numerical optimization and experimental characterization of two microstrip-based nuclear magnetic resonance (NMR) detectors. The first detector, introduced in our previous work, was a flat wire detector with a strip resting on a substrate, and the second detector was created by adding a ground plane on top of the strip conductor, separated by a sample-carrying capillary and a thin layer of insulator. The dimensional parameters of the detectors were optimized using numerical simulations with regards to radio frequency (RF) sensitivity and homogeneity, with particular attention given to the effect of the ground plane. The influence of copper surface finish and substrate surface on the spectral resolution was investigated, and a resolution of 0.8-1.5 Hz was obtained on 1 nL deionized water depending on sample positioning. For 0.13 nmol sucrose (0.2 M in 0.63 nL H2O) encapsulated between two Fluorinert plugs, high RF homogeneity (A810°/A90° = 70-80%) and high sensitivity (expressed in the limit of detection nLODm = 0.73-1.21 nmol s1/2) were achieved, allowing for high-performance 2D NMR spectroscopy of subnanoliter samples.

Semi-empirical refinements of crystal structures using 17O quadrupolar-coupling tensors.

We demonstrate a modification of Grimme's two-parameter empirical dispersion force field (referred to as the PW91-D2* method), in which the damping function has been optimized to yield geometries that result in predictions of the principal values of 17O quadrupolar-coupling tensors that are systematically in close agreement with experiment. The predictions of 17O quadrupolar-coupling tensors using PW91-D2*-refined structures yield a root-mean-square deviation (RMSD) (0.28 MHz) for twenty-two crystalline systems that is smaller than the RMSD for predictions based on X-ray diffraction structures (0.58 MHz) or on structures refined with PW91 (0.53 MHz). In addition, 13C, 15N, and 17O chemical-shift tensors and 35Cl quadrupolar-coupling tensors determined with PW91-D2*-refined structures are compared to the experiment. Errors in the prediction of chemical-shift tensors and quadrupolar-coupling tensors are, in these cases, substantially lowered, as compared to predictions based on PW91-refined structures. With this PW91-D2*-based method, analysis of 42 17O chemical-shift-tensor principal components gives a RMSD of only 18.3 ppm, whereas calculations on unrefined X-ray structures give a RMSD of 39.6 ppm and calculations of PW91-refined structures give an RMSD of 24.3 ppm. A similar analysis of 35Cl quadrupolar-coupling tensor principal components gives a RMSD of 1.45 MHz for the unrefined X-ray structures, 1.62 MHz for PW91-refined structures, and 0.59 MHz for the PW91-D2*-refined structures.

Analysis of the bond-valence method for calculating (29) Si and (31) P magnetic shielding in covalent network solids.

(29) Si and (31) P magnetic-shielding tensors in covalent network solids have been evaluated using periodic and cluster-based calculations. The cluster-based computational methodology employs pseudoatoms to reduce the net charge (resulting from missing co-ordination on the terminal atoms) through valence modification of terminal atoms using bond-valence theory (VMTA/BV). The magnetic-shielding tensors computed with the VMTA/BV method are compared to magnetic-shielding tensors determined with the periodic GIPAW approach. The cluster-based all-electron calculations agree with experiment better than the GIPAW calculations, particularly for predicting absolute magnetic shielding and for predicting chemical shifts. The performance of the DFT functionals CA-PZ, PW91, PBE, rPBE, PBEsol, WC, and PBE0 are assessed for the prediction of (29) Si and (31) P magnetic-shielding constants. Calculations using the hybrid functional PBE0, in combination with the VMTA/BV approach, result in excellent agreement with experiment. © 2016 Wiley Periodicals, Inc.

Spin-orbit effects on the (119)Sn magnetic-shielding tensor in solids: a ZORA/DFT investigation.

Periodic-boundary and cluster calculations of the magnetic-shielding tensors of (119)Sn sites in various co-ordination and stereochemical environments are reported. The results indicate a significant difference between the predicted NMR chemical shifts for tin(ii) sites that exhibit stereochemically-active lone pairs and tin(iv) sites that do not have stereochemically-active lone pairs. The predicted magnetic shieldings determined either with the cluster model treated with the ZORA/Scalar Hamiltonian or with the GIPAW formalism are dependent on the oxidation state and the co-ordination geometry of the tin atom. The inclusion of relativistic effects at the spin-orbit level removes systematic differences in computed magnetic-shielding parameters between tin sites of differing stereochemistries, and brings computed NMR shielding parameters into significant agreement with experimentally-determined chemical-shift principal values. Slight improvement in agreement with experiment is noted in calculations using hybrid exchange-correlation functionals.