A Study of Through-Space and Through-Bond JPP Coupling in a Rigid Nonsymmetrical Bis(phosphine) and Its Metal Complexes.

A series of representative late d-block metal complexes bearing a rigid bis(phosphine) ligand, iPr2P-Ace-PPh2 (L, Ace = acenaphthene-5,6-diyl), was prepared and fully characterized by various techniques, including multinuclear NMR and single-crystal X-ray diffraction. The heteroleptic nature of the peri-substituted ligand L allows for the direct observation of the JPP couplings in the 31P{1H} NMR spectra. Magnitudes of JPP are correlated with the identity and geometry of the metal and the distortions of the ligand L. The forced overlap of the phosphine lone pairs due to the constraints imposed by the rigid acenaphthene skeleton in L results in a large 4 JPP of 180 Hz. Sequestration of the lone pairs, either via oxidation of the phosphine or via metal chelation, results in distinct changes in the magnitude of JPP. For tetrahedral d10 complexes ([LMCl2], M = Zn, Cd, Hg), the JPP is comparable to or larger than (193-309 Hz) that in free ligand L, although the P···P separation in these complexes is increased by ca. 0.4 Å (compare to free ligand L). The magnitude of JPP diminishes to 26-117 Hz in square planar d8 complexes ([LMX2], M = Ni, Pd, Pt; X = Cl, Br) and the octahedral Mo0 complex ([LMo(CO)4], 33 Hz). Coupling deformation density calculations indicate the through-space interaction dominates in free L, while in metal complexes the main coupling pathway is via the metal atom.

Computer-Vision-Based Approach to Classify and Quantify Flaws in Li-Ion Electrodes.

X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the extraction of useful metrics that can ultimately inform the mechanisms behind cycle life degradation. This work presents a novel approach that combines two convolutional neural networks to first locate and segment each particle in a nano-CT LiNiMnCoO2 (NMC) electrode dataset, and successively classifies each particle according to the presence of flaws or cracks within its internal structure. Metrics extracted from the computer vision segmentation are validated with respect to traditional threshold-based segmentation, confirming that flawed particles are correctly identified as single entities. Successively, slices from each particle are analyzed by a pre-trained classifier to detect the presence of flaws or cracks. The models are used to quantify microstructural evolution in uncycled and cycled NMC811 electrodes, as well as the number of flawed particles in a NMC622 electrode. As a proof-of-concept, a 3-phase segmentation is also presented, whereby each individual flaw is segmented as a separate pixel label. It is anticipated that this analysis pipeline will be widely used in the field of battery research and beyond.

Operando Bragg Coherent Diffraction Imaging of LiNi0.8Mn0.1Co0.1O2 Primary Particles within Commercially Printed NMC811 Electrode Sheets.

Due to complex degradation mechanisms, disparities between the theoretical and practical capacities of lithium-ion battery cathode materials persist. Specifically, Ni-rich chemistries such as LiNi0.8Mn0.1Co0.1O2 (or NMC811) are one of the most promising choices for automotive applications; however, they continue to suffer severe degradation during operation that is poorly understood, thus challenging to mitigate. Here we use operando Bragg coherent diffraction imaging for 4D analysis of these mechanisms by inspecting the individual crystals within primary particles at various states of charge (SoC). Although some crystals were relatively homogeneous, we consistently observed non-uniform distributions of inter- and intracrystal strain at all measured SoC. Pristine structures may already possess heterogeneities capable of triggering crystal splitting and subsequently particle cracking. During low-voltage charging (2.7-3.5 V), crystal splitting may still occur even during minimal bulk deintercalation activity; and during discharging, rotational effects within parallel domains appear to be the precursor for the nucleation of screw dislocations at the crystal core. Ultimately, this discovery of the central role of crystal grain splitting in the charge/discharge dynamics may have ramifications across length scales that affect macroscopic performance loss during real-world battery operation.

Resolving Li-Ion Battery Electrode Particles Using Rapid Lab-Based X-Ray Nano-Computed Tomography for High-Throughput Quantification.

Vast quantities of powder leave production lines each day, often with strict control measures. For quality checks to provide the most value, they must be capable of screening individual particles in 3D and at high throughput. Conceptually, X-ray computed tomography (CT) is capable of this; however, achieving lab-based reconstructions of individual particles has, until now, relied upon scan-times on the order of tens of hours, or even days, and although synchrotron facilities are potentially capable of faster scanning times, availability is limited, making in-line product analysis impractical. This work describes a preparation method and high-throughput scanning procedure for the 3D characterization of powder samples in minutes using nano-CT by full-filed transmission X-ray microscopy with zone-plate focusing optics. This is demonstrated on various particle morphologies from two next-generation lithium-ion battery cathodes: LiNi0.8Mn0.1Co0.1O2 and LiNi0.6Mn0.2Co0.2O2; namely, NMC811 and NMC622. Internal voids are detected which limit energy density and promote degradation, potentially impacting commercial application such as the drivable range of an electric vehicle.