Materials’ Methods: NMR in Battery Research

Improving electrochemical energy storage is one of the major issues of our time. The search for new battery materials together with the drive to improve performance and lower cost of existing and new batteries is not without its challenges. Success in these matters is undoubtedly based on first understanding the underlying chemistries of the materials and the relations between the components involved. A combined application of experimental and theoretical techniques has proven to be a powerful strategy to gain insights into many of the questions that arise from the “how do batteries work and why do they fail” challenge. In this Review, we highlight the application of solid-state nuclear magnetic resonance (NMR) spectroscopy in battery research: a technique that can be extremely powerful in characterizing local structures in battery materials, even in highly disordered systems. An introduction on electrochemical energy storage illustrates the research aims and prospective approaches to reach these. We particularly address “NMR in battery research” by giving a brief introduction to electrochemical techniques and applications as well as background information on both in and ex situ solid-state NMR spectroscopy. We will try to answer the question “Is NMR suitable and how can it help me to solve my problem?” by shortly reviewing some of our recent research on electrodes, microstructure formation, electrolytes and interfaces, in which the application of NMR was helpful. Finally, we share hands-on experience directly from the lab bench to answer the fundamental question “Where and how should I start?” to help guide a researcher’s way through the manifold possible approaches.This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 655444 (O.P.). K.J.G. thanks the Winston Churchill Foundation of the United States and the Herchel Smith Scholarship for financial support

Mechanistic insights into sodium storage in hard carbon anodes using local structure probes

Operando $^{23}$Na solid-state NMR and pair distribution function analysis experiments provide insights into the structure of hard carbon anodes in sodium-ion batteries. Capacity results from "diamagnetic" sodium ions first adsorbing onto pore surfaces, defects and between expanded layers, before pooling into larger quasi-metallic clusters/expanded carbon sheets at lower voltages.J. M. S. acknowledges funding from EPSRC and the European Commission under grant agreement no. 696656 (Graphene Flagship). P. K. A. acknowledges the School of the Physical Sciences of the University of Cambridge for funding through an Oppenheimer Research Fellowship and a Junior Research Fellowship from Gonville and Caius College, Cambridge. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 655444 (O. P.)

Enhanced efficiency of solid-state NMR investigations of energy materials using an external automatic tuning/matching (eATM) robot.

We have developed and explored an external automatic tuning/matching (eATM) robot that can be attached to commercial and/or home-built magic angle spinning (MAS) or static nuclear magnetic resonance (NMR) probeheads. Complete synchronization and automation with Bruker and Tecmag spectrometers is ensured via transistor-transistor-logic (TTL) signals. The eATM robot enables an automated "on-the-fly" re-calibration of the radio frequency (rf) carrier frequency, which is beneficial whenever tuning/matching of the resonance circuit is required, e.g. variable temperature (VT) NMR, spin-echo mapping (variable offset cumulative spectroscopy, VOCS) and/or in situ NMR experiments of batteries. This allows a significant increase in efficiency for NMR experiments outside regular working hours (e.g. overnight) and, furthermore, enables measurements of quadrupolar nuclei which would not be possible in reasonable timeframes due to excessively large spectral widths. Additionally, different tuning/matching capacitor (and/or coil) settings for desired frequencies (e.g. $^{7}$Li and $^{31}$P at 117 and 122MHz, respectively, at 7.05 T) can be saved and made directly accessible before automatic tuning/matching, thus enabling automated measurements of multiple nuclei for one sample with no manual adjustment required by the user. We have applied this new eATM approach in static and MAS spin-echo mapping NMR experiments in different magnetic fields on four energy storage materials, namely: (1) paramagnetic $^{7}$Li and $^{31}$P MAS NMR (without manual recalibration) of the Li-ion battery cathode material LiFePO$_{4}$; (2) paramagnetic $^{17}$O VT-NMR of the solid oxide fuel cell cathode material La$_{2}$NiO$_{4+δ}$; (3) broadband $^{93}$Nb static NMR of the Li-ion battery material BNb$_{2}$O$_{5}$; and (4) broadband static $^{127}$I NMR of a potential Li-air battery product LiIO$_{3}$. In each case, insight into local atomic structure and dynamics arises primarily from the highly broadened (1-25MHz) NMR lineshapes that the eATM robot is uniquely suited to collect. These new developments in automation of NMR experiments are likely to advance the application of in and ex situ NMR investigations to an ever-increasing range of energy storage materials and systems.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 655444 (O.P.). D.M.H. acknowledges funding from the Cambridge Commonwealth Trusts. J.L. gratefully acknowledges Trinity College, Cambridge (UK) for funding. K.J.G. gratefully acknowledges funding from the Winston Churchill Foundation of the United States and the Herchel Smith Scholarship. M.B. is the CEO of NMR Service GmbH (Erfurt, Germany), which manufactures the eATM device; M.B. acknowledges funding of the Central Innovation Programme for small and medium-sized enterprises (SMEs; Zentrales Innovationsprogramm Mittelstand, ZIM) of the German Federal Ministry of Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie, BMWi) under the Grant No. KF 2845501UWF. DFT calculations were performed on (1) the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council and (2) the Center for Functional Nanomaterials cluster, Brookhaven National Laboratory, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10886

Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory and Solid-State NMR Approach

The alloying mechanism of high-capacity tin anodes for sodium-ion batteries is investigated using a combined theoretical and experimental approach. Ab initio random structure searching (AIRSS) and high-throughput screening using a species-swap method provide insights into a range of possible sodium-tin structures. These structures are linked to experiments using both average and local structure probes in the form of operando pair distribution function analysis, X-ray diffraction, and 23Na solid-state nuclear magnetic resonance (ssNMR), and ex situ 119Sn ssNMR. Through this approach, we propose structures for the previously unidentified crystalline and amorphous intermediates. The first electrochemical process of sodium insertion into tin results in the conversion of crystalline tin into a layered structure consisting of mixed Na/Sn occupancy sites intercalated between planar hexagonal layers of Sn atoms (approximate stoichiometry NaSn3). Following this, NaSn2, which is predicted to be thermodynamically stable by AIRSS, forms; this contains hexagonal layers closely related to NaSn3, but has no tin atoms between the layers. NaSn2 is broken down into an amorphous phase of approximate composition Na1.2Sn. Reverse Monte Carlo refinements of an ab initio molecular dynamics model of this phase show that the predominant tin connectivity is chains. Further reaction with sodium results in the formation of structures containing Sn-Sn dumbbells, which interconvert through a solid-solution mechanism. These structures are based upon Na5-xSn2, with increasing occupancy of one of its sodium sites commensurate with the amount of sodium added. ssNMR results indicate that the final product, Na15Sn4, can store additional sodium atoms as an off-stoichiometry compound (Na15+xSn4) in a manner similar to Li15Si4.This work was supported by STFCBatteries.org through the STFC Futures Early Career Award (J.M.S.). J.M.S. acknowledges funding from the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies, of the U.S. DOE under Contract no. DE-AC02-05CH11231, under the Batteries for Advanced Transportation Technologies (BATT) Program subcontract no. 7057154, and the European Commission under grant agreement no. 696656 (Graphene Flagship). P.K.A. acknowledges the School of the Physical Sciences of the University of Cambridge for funding through an Oppenheimer Research Fellowship and a Junior Research Fellowship from Gonville and Caius College, Cambridge. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 655444 (O.P.). M.M. and A.J.M. acknowledge the support from the Winton Programme for the Physics of Sustainability. A.J.M. and C.J.P. were supported by Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom (Grant no. EP/G007489/2). C.J.P. is also supported by the Royal Society through a Royal Society Wolfson Research Merit award. Calculations were performed using the Archer facility of the UK national high performance computing service, for which access was obtained via the UKCP consortium and funded by EPSRC grant no. EP/K014560/1

A Functional Role for Modality-Specific Perceptual Systems in Conceptual Representations

Theories of embodied cognition suggest that conceptual processing relies on the same neural resources that are utilized for perception and action. Evidence for these perceptual simulations comes from neuroimaging and behavioural research, such as demonstrations of somatotopic motor cortex activations following the presentation of action-related words, or facilitation of grasp responses following presentation of object names. However, the interpretation of such effects has been called into question by suggestions that neural activation in modality-specific sensorimotor regions may be epiphenomenal, and merely the result of spreading activations from “disembodied”, abstracted, symbolic representations. Here, we present two studies that focus on the perceptual modalities of touch and proprioception. We show that in a timed object-comparison task, concurrent tactile or proprioceptive stimulation to the hands facilitates conceptual processing relative to control stimulation. This facilitation occurs only for small, manipulable objects, where tactile and proprioceptive information form part of the multimodal perceptual experience of interacting with such objects, but facilitation is not observed for large, nonmanipulable objects where such perceptual information is uninformative. Importantly, these facilitation effects are independent of motor and action planning, and indicate that modality-specific perceptual information plays a functionally constitutive role in our mental representations of objects, which supports embodied assumptions that concepts are grounded in the same neural systems that govern perception and action

Dutch modality exclusivity norms : Simulating perceptual modality in space

Perceptual information is important for the meaning of nouns. We present modality exclusivity norms for 485 Dutch nouns rated on visual, auditory, haptic, gustatory, and olfactory associations. We found these nouns are highly multimodal. They were rated most dominant in vision, and least in olfaction. A factor analysis identified two main dimensions: one loaded strongly on olfaction and gustation (reflecting joint involvement in flavor), and a second loaded strongly on vision and touch (reflecting joint involvement in manipulable objects). In a second study, we validated the ratings with similarity judgments. As expected, words from the same dominant modality were rated more similar than words from different dominant modalities; but - more importantly - this effect was enhanced when word pairs had high modality strength ratings. We further demonstrated the utility of our ratings by investigating whether perceptual modalities are differentially experienced in space, in a third study. Nouns were categorized into their dominant modality and used in a lexical decision experiment where the spatial position of words was either in proximal or distal space. We found words dominant in olfaction were processed faster in proximal than distal space compared to the other modalities, suggesting olfactory information is mentally simulated as "close" to the body. Finally, we collected ratings of emotion (valence, dominance, and arousal) to assess its role in perceptual space simulation, but the valence did not explain the data. So, words are processed differently depending on their perceptual associations, and strength of association is captured by modality exclusivity ratings

Sensorimotor input as a language generalisation tool: a neurorobotics model for generation and generalisation of noun-verb combinations with sensorimotor inputs

The paper presents a neurorobotics cognitive model explaining the understanding and generalisation of nouns and verbs combinations when a vocal command consisting of a verb-noun sentence is provided to a humanoid robot. The dataset used for training was obtained from object manipulation tasks with a humanoid robot platform; it includes 9 motor actions and 9 objects placing placed in 6 different locations), which enables the robot to learn to handle real-world objects and actions. Based on the multiple time-scale recurrent neural networks, this study demonstrates its generalisation capability using a large data-set, with which the robot was able to generalise semantic representation of novel combinations of noun-verb sentences, and therefore produce the corresponding motor behaviours. This generalisation process is done via the grounding process: different objects are being interacted, and associated, with different motor behaviours, following a learning approach inspired by developmental language acquisition in infants. Further analyses of the learned network dynamics and representations also demonstrate how the generalisation is possible via the exploitation of this functional hierarchical recurrent network