Direct identification of interfacial degradation in blue OLEDs using nanoscale chemical depth profiling.

Understanding the degradation mechanism of organic light-emitting diodes (OLED) is essential to improve device performance and stability. OLED failure, if not process-related, arises mostly from chemical instability. However, the challenges of sampling from nanoscale organic layers and interfaces with enough analytical information has hampered identification of degradation products and mechanisms. Here, we present a high-resolution diagnostic method of OLED degradation using an Orbitrap mass spectrometer equipped with a gas cluster ion beam to gently desorb nanometre levels of materials, providing unambiguous molecular information with 7-nm depth resolution. We chemically depth profile and analyse blue phosphorescent and thermally-activated delayed fluorescent (TADF) OLED devices at different degradation levels. For OLED devices with short operational lifetimes, dominant chemical degradation mainly relate to oxygen loss of molecules that occur at the interface between emission and electron transport layers (EML/ETL) where exciton distribution is maximised, confirmed by emission zone measurements. We also show approximately one order of magnitude increase in lifetime of devices with slightly modified host materials, which present minimal EML/ETL interfacial degradation and show the method can provide insight for future material and device architecture development.

Toward Comprehensive Analysis of the 3D Chemistry of Pseudomonas aeruginosa Biofilms.

Bacterial biofilms are structured communities consisting of cells enmeshed in a self-generated extracellular matrix usually attached to a surface. They contain diverse classes of molecules including polysaccharides, lipids, proteins, nucleic acids, and diverse small organic molecules (primary and secondary metabolites) which are organized to optimize survival and facilitate dispersal to new colonization sites. In situ characterization of the chemical composition and structure of bacterial biofilms is necessary to fully understand their development on surfaces relevant to biofouling in health, industry, and the environment. Biofilm development has been extensively studied using confocal microscopy using targeted fluorescent labels providing important insights into the architecture of biofilms. Recently, cryopreparation has been used to undertake targeted in situ chemical characterization using Orbitrap secondary ion mass spectrometry (OrbiSIMS), providing a label-free method for imaging biofilms in their native state. Although the high mass resolution of OrbiSIMS enables more confident peak assignments, it is still very challenging to assign most of the peaks in the spectra due to complexity of SIMS spectra and lack of automatic peak assignment methods. Here, we analyze the same OrbiSIMS depth profile data generated from the frozen-hydrated biofilm, but employ a new untargeted chemical filtering process utilizing mass spectral databases to assign secondary ions to decipher the large number of fragments present in the SIMS spectra. To move towards comprehensive analysis of different chemistries in the sample, we apply a molecular formula prediction approach which putatively assigns 81% of peaks in the 3D OrbiSIMS depth profile analysis. This enables us to catalog over 1000 lipids and their fragments, 3500 protein fragments, 71 quorum sensing-related molecules (2-alkyl-4-quinolones and N-acylhomoserine lactones), 150 polysaccharide fragments, and glycolipids simultaneously from one data set and map these separated molecular classes spatially through a Pseudomonas aeruginosa biofilm. Assignment of different chemistries in this sample facilitates identification of differences between biofilms grown on biofilm-promoting and biofilm-resistant polymers.

Visualisation of drug distribution in skin using correlative optical spectroscopy and mass spectrometry imaging.

A correlative methodology for label-free chemical imaging of soft tissue has been developed, combining non-linear optical spectroscopies and mass spectrometry to achieve sub-micron spatial resolution and critically improved drug detection sensitivity. The approach was applied to visualise the kinetics of drug reservoir formation within human skin following in vitro topical treatment with a commercial diclofenac gel. Non-destructive optical spectroscopic techniques, namely stimulated Raman scattering, second harmonic generation and two photon fluorescence microscopies, were used to provide chemical and structural contrast. The same tissue sections were subsequently analysed by secondary ion mass spectrometry, which offered higher sensitivity for diclofenac detection throughout the epidermis and dermis. A method was developed to combine the optical and mass spectrometric datasets using image registration techniques. The label-free, high-resolution visualisation of tissue structure coupled with sensitive chemical detection offers a powerful method for drug biodistribution studies in the skin that impact directly on topical pharmaceutical product development.

Quantitative and Qualitative Analyses of Mass Spectra of OEL Materials by Artificial Neural Network and Interface Evaluation: Results from a VAMAS Interlaboratory Study.

Quantitative analysis of binary mixtures of tris(2-phenylpyridinato)iridium(III) (Ir(ppy)3) and tris(8-hydroxyquinolinato)aluminum (Alq3) by using an artificial neural network (ANN) system to mass spectra was attempted based on the results of a VAMAS (Versailles Project on Advanced Materials and Standards) interlaboratory study (TW2 A31) to evaluate matrix-effect correction and to investigate interface determination. Monolayers of binary mixtures having different Ir(ppy)3 ratios (0, 0.25, 0.50, 0.75, and 1.00), and the multilayers containing these mixtures and pure samples were measured using time-of-flight secondary ion mass spectrometry (ToF-SIMS) with different primary ion beams, OrbiSIMS (SIMS with both Orbitrap and ToF mass spectrometers), laser desorption ionization (LDI), desorption/ionization induced by neutral clusters (DINeC), and X-ray photoelectron spectroscopy (XPS). The mass spectra were analyzed using a simple ANN with one hidden layer. The Ir(ppy)3 ratios of the unknown samples and the interfaces of the multilayers were predicted using the simple ANN system, even though the mass spectra of binary mixtures exhibited matrix effects. The Ir(ppy)3 ratios at the interfaces indicated by the simple ANN were consistent with the XPS results and the ToF-SIMS depth profiles. The simple ANN system not only provided quantitative information on unknown samples, but also indicated important mass peaks related to each molecule in the samples without a priori information. The important mass peaks indicated by the simple ANN depended on the ionization process. The simple ANN results of the spectra sets obtained by a softer ionization method, such as LDI and DINeC, suggested large ions such as trimers. From the first step of the investigation to build an ANN model for evaluating mixture samples influenced by matrix effects, it was indicated that the simple ANN method is useful for obtaining candidate mass peaks for identification and for assuming mixture conditions that are helpful for further analysis.

Understanding the Influence of Li7La3Zr2O12 Nanofibers on Critical Current Density and Coulombic Efficiency in Composite Polymer Electrolytes.

Composite polymer electrolytes (CPEs) are attractive materials for solid-state lithium metal batteries, owing to their high ionic conductivity from ceramic ionic conductors and flexibility from polymer components. As with all lithium metal batteries, however, CPEs face the challenge of dendrite formation and propagation. Not only does this lower the critical current density (CCD) before cell shorting, but the uncontrolled growth of lithium deposits may limit Coulombic efficiency (CE) by creating dead lithium. Here, we present a fundamental study on how the ceramic components of CPEs influence these characteristics. CPE membranes based on poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO-LiTFSI) with Li7La3Zr2O12 (LLZO) nanofibers were fabricated with industrially relevant roll-to-roll manufacturing techniques. Galvanostatic cycling with lithium symmetric cells shows that the CCD can be tripled by including 50 wt % LLZO, but half-cell cycling reveals that this comes at the cost of CE. Varying the LLZO loading shows that even a small amount of LLZO drastically lowers the CE, from 88% at 0 wt % LLZO to 77% at just 2 wt % LLZO. Mesoscale modeling reveals that the increase in CCD cannot be explained by an increase in the macroscopic or microscopic stiffness of the electrolyte; only the microstructure of the LLZO nanofibers in the PEO-LiTFSI matrix slows dendrite growth by presenting physical barriers that the dendrites must push or grow around. This tortuous lithium growth mechanism around the LLZO is corroborated with mass spectrometry imaging. This work highlights important elements to consider in the design of CPEs for high-efficiency lithium metal batteries.

The dietary sweetener sucralose is a negative modulator of T cell-mediated responses.

Artificial sweeteners are used as calorie-free sugar substitutes in many food products and their consumption has increased substantially over the past years1. Although generally regarded as safe, some concerns have been raised about the long-term safety of the consumption of certain sweeteners2-5. In this study, we show that the intake of high doses of sucralose in mice results in immunomodulatory effects by limiting T cell proliferation and T cell differentiation. Mechanistically, sucralose affects the membrane order of T cells, accompanied by a reduced efficiency of T cell receptor signalling and intracellular calcium mobilization. Mice given sucralose show decreased CD8+ T cell antigen-specific responses in subcutaneous cancer models and bacterial infection models, and reduced T cell function in models of T cell-mediated autoimmunity. Overall, these findings suggest that a high intake of sucralose can dampen T cell-mediated responses, an effect that could be used in therapy to mitigate T cell-dependent autoimmune disorders.

Surface Analysis of Pristine and Cycled NMC/Graphite Lithium-Ion Battery Electrodes: Addressing the Measurement Challenges.

Lithium-ion batteries are the most ubiquitous energy storage devices in our everyday lives. However, their energy storage capacity fades over time due to chemical and structural changes in their components, via different degradation mechanisms. Understanding and mitigating these degradation mechanisms is key to reducing capacity fade, thereby enabling improvement in the performance and lifetime of Li-ion batteries, supporting the energy transition to renewables and electrification. In this endeavor, surface analysis techniques are commonly employed to characterize the chemistry and structure at reactive interfaces, where most changes are observed as batteries age. However, battery electrodes are complex systems containing unstable compounds, with large heterogeneities in material properties. Moreover, different degradation mechanisms can affect multiple material properties and occur simultaneously, meaning that a range of complementary techniques must be utilized to obtain a complete picture of electrode degradation. The combination of these issues and the lack of standard measurement protocols and guidelines for data interpretation can lead to a lack of trust in data. Herein, we discuss measurement challenges that affect several key surface analysis techniques being used for Li-ion battery degradation studies: focused ion beam scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and time-of-flight secondary ion mass spectrometry. We provide recommendations for each technique to improve reproducibility and reduce uncertainty in the analysis of NMC/graphite Li-ion battery electrodes. We also highlight some key measurement issues that should be addressed in future investigations.

High spatial resolution ToF-SIMS imaging and image analysis strategies to monitor and quantify early phase separation in amorphous solid dispersions.

Amorphous solid dispersions (ASDs) are formulations with enhanced drug solubility and dissolution rate compared to their crystalline counterparts, however, they can be inherently thermodynamically unstable. This can lead to amorphous phase separation and drug re-crystallisation, phenomena that are typically faster and more dominant at the product's surfaces. This study investigates the use of high-resolution time of flight-secondary ion mass spectrometry (ToF-SIMS) imaging as a surface analysis technique combined with image-analysis for the early detection, monitoring and quantification of surface amorphous phase separation in ASDs. Its capabilities are demonstrated for two pharmaceutically relevant ASD systems with distinct re-crystallisation behaviours, prepared using hot melt extrusion (HME) followed by pelletisation or grinding: (1) paracetamol-hydroxypropyl methylcellulose (PCM-HPMC) pellets with drug loadings of 10%-50% w/w and (2) indomethacin-polyvinylpyrrolidone (IND-PVP) ground material with drug loadings of 20%-85% w/w. PCM-HPMC pellets showed intense phase separation, reaching 100% PCM surface coverage within 1-5 months. In direct comparison, IND-PVP HME ground material was more stable with only a moderate formation of isolated IND-rich clusters. Image analysis allowed the reliable detection and quantification of local drug-rich clusters. An Avrami model was applied to determine and compare phase separation kinetics. The combination of chemical sensitivity and high spatial resolution afforded by SIMS was crucial to enable the study of early phase separation and re-crystallisation at the surface. Compared with traditional methods used to detect crystalline material, such as XRPD, we show that ToF-SIMS enabled detection of surface physical instability already at early stages of drug cluster formation in the first days of storage.

Multimodal imaging of drug and excipients in rat lungs following an inhaled administration of controlled-release drug laden PLGA microparticles.

Controlled-release formulations, in the form of micro- or nanoparticles, are increasingly attractive to the pharmaceutical industry for drug delivery. For respiratory illnesses, controlled-release microparticle formulations provide an opportunity to deliver a higher percentage of an inhaled medicament dose to the lung, thus potentially reducing the therapeutic dose, frequency of dosing, and minimising side-effects. We describe the use of a multimodal approach consisting of MALDI MS imaging, 3D depth profiling TOF-SIMS analysis, and histopathology to monitor the distribution of drug and excipients in sections taken from excised rat lungs following an inhaled administration of drug-laden microparticles. Following a single dose, the administered drug was detected in the lung via both MALDI MS and TOF-SIMS over a range of time points. Both imaging techniques enabled the characterisation of the distribution and retention of drug particles and identified differences in the capabilities of both imaging modalities. Histochemical staining of consecutive sections was used to provide biological context to the findings and will also be discussed in this presentation. We demonstrate how this multimodal approach could be used to help increase our understanding of the use of controlled release microparticles.

Evaluation of Time-of-Flight Secondary Ion Mass Spectrometry Spectra of Peptides by Random Forest with Amino Acid Labels: Results from a Versailles Project on Advanced Materials and Standards Interlaboratory Study.

We report the results of a VAMAS (Versailles Project on Advanced Materials and Standards) interlaboratory study on the identification of peptide sample TOF-SIMS spectra by machine learning. More than 1000 time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of six peptide model samples (one of them was a test sample) were collected using 27 TOF-SIMS instruments from 25 institutes of six countries, the U. S., the U. K., Germany, China, South Korea, and Japan. Because peptides have systematic and simple chemical structures, they were selected as model samples. The intensity of peaks in every TOF-SIMS spectrum was extracted using the same peak list and normalized to the total ion count. The spectra of the test peptide sample were predicted by Random Forest with 20 amino acid labels. The accuracy of the prediction for the test spectra was 0.88. Although the prediction of an unknown peptide was not perfect, it was shown that all of the amino acids in an unknown peptide can be determined by Random Forest prediction and the TOF-SIMS spectra. Moreover, the prediction of peptides, which are included in the training spectra, was almost perfect. Random Forest also suggests specific fragment ions from an amino acid residue Q, whose fragment ions detected by TOF-SIMS have not been reported, in the important features. This study indicated that the analysis using Random Forest, which enables translation of the mathematical relationships to chemical relationships, and the multi labels representing monomer chemical structures, is useful to predict the TOF-SIMS spectra of an unknown peptide.

Method for Molecular Layer Deposition Using Gas Cluster Ion Beam Sputtering with Example Application In Situ Matrix-Enhanced Secondary Ion Mass Spectrometry.

We introduce a technique for the directed transfer of molecules from an adjacent reservoir onto a sample surface inside the vacuum chamber of a ToF-SIMS instrument using gas cluster ion beam (GCIB) sputtering. An example application for in situ matrix-enhanced secondary ion mass spectrometry (ME SIMS) is provided. This protocol has attractive features since most modern SIMS instruments are equipped with a GCIB gun. No solvents are required that would delocalize analytes at the surface, and the transfer of matrix molecules can be interlaced with SIMS depth profiling and 3D imaging sputtering and analysis cycles, which is not possible with conventional ME SIMS strategies. The amount of molecular deposition can be finely tuned, which is important for such a surface sensitive technique as SIMS. To demonstrate the concept, we used 2,5-DHB as a matrix for the enhancement of three drug molecules embedded in a tissue homogenate. By automatic operation of sputter deposition and erosion (cleanup) cycles, depth profiling could be achieved with ME SIMS with good repeatability (<4% RSD). Furthermore, we explored several different matrix compounds, including α-CHCA and aqueous solutions of Brønsted acids (formic acid) and 3-nitrobenzonitrile, a volatile compound known to spontaneously produce ions. The latter two matrix compounds were applied at cryogenic measurement conditions, which extend the range of matrices applicable for ME SIMS. Enhancement ratios range from 2 to 13, depending on the analytes and matrix. The method works in principle, but enhancement ratios for the drug molecules are rather limited at this point. Further study and optimization is needed, and the technique introduced here provides a tool to perform systematic studies of matrix compounds and experimental conditions for their potential for signal enhancement in ME SIMS.

An Experimental and Theoretical Study of Laser Postionization of Femtosecond-Laser-Desorbed Drug Molecules.

Femtosecond laser desorption postionization mass spectrometry using 7.9 eV single-photon ionization (7.9 eV fs-LDPI-MS) detected three of four drug compounds previously found to have very low ionization efficiencies by secondary ion mass spectrometry. Electronic structure calculations of the ionization energies and other properties of these four drug compounds predicted that all display ionization energies below the 7.9 eV photon energy, as required for single-photon ionization. The 7.9 eV fs-LDPI-MS of carbamazepine, imipramine, and verapamil all showed significant precursor (M+) ion signal, but no representative signal was observed for ciprofloxacin. Furthermore, 7.9 eV fs-LDPI-MS displayed higher M+ signals and mostly similar fragment ions compared with 70 eV electron impact mass spectrometry. Ionization and fragmentation patterns are discussed in terms of calculated wave functions for the highest occupied molecular orbitals. The implications for improving lateral resolution and sensitivity of MS imaging of drug compounds are also considered.

Cryogenic OrbiSIMS Localizes Semi-Volatile Molecules in Biological Tissues.

OrbiSIMS is a recently developed instrument for label-free imaging of chemicals with micron spatial resolution and high mass resolution. We report a cryogenic workflow for OrbiSIMS (Cryo-OrbiSIMS) that improves chemical detection of lipids and other biomolecules in tissues. Cryo-OrbiSIMS boosts ionization yield and decreases ion-beam induced fragmentation, greatly improving the detection of biomolecules such as triacylglycerides. It also increases chemical coverage to include molecules with intermediate or high vapor pressures, such as free fatty acids and semi-volatile organic compounds (SVOCs). We find that Cryo-OrbiSIMS reveals the hitherto unknown localization patterns of SVOCs with high spatial and chemical resolution in diverse plant, animal, and human tissues. We also show that Cryo-OrbiSIMS can be combined with genetic analysis to identify enzymes regulating SVOC metabolism. Cryo-OrbiSIMS is applicable to high resolution imaging of a wide variety of non-volatile and semi-volatile molecules across many areas of biomedicine.

Correlative Hyperspectral Imaging Using a Dimensionality-Reduction-Based Image Fusion Method.

Chemical imaging techniques are increasingly being used in combination to achieve a greater understanding of a sample. This is especially true in the case of mass spectrometry imaging (MSI), where the use of different ionization sources allows detection of different classes of molecules across a range of spatial resolutions. There has been significant recent effort in the development of data fusion algorithms that attempt to combine the benefits of multiple techniques, such that the output provides additional information that would have not been present or obvious from the individual techniques alone. However, the majority of the data fusion methods currently in use rely on image registration to generate the fused data and therefore can suffer from artifacts caused by interpolation. Here, we present a method for data fusion that does not incorporate interpolation-based artifacts into the final fused data, applied to data acquired from multiple chemical imaging modalities. The method is evaluated using simulated data and a model polymer blend sample, before being applied to biological samples of mouse brain and lung.

Cryo-OrbiSIMS for 3D Molecular Imaging of a Bacterial Biofilm in Its Native State.

Secondary ion mass spectrometry (SIMS) is gaining popularity for molecular imaging in the life sciences because it is label-free and allows imaging in two and three dimensions. The recent introduction of the OrbiSIMS has significantly improved the utility for biological imaging through combining subcellular spatial resolution with high-performance Orbitrap mass spectrometry. SIMS instruments operate in high-vacuum, and samples are typically analyzed in a freeze-dried state. Consequently, the molecular and structural information may not be well-preserved. We report a method for molecular imaging of biological materials, preserved in a native state, by using an OrbiSIMS instrument equipped with cryogenic sample handling and a high-pressure freezing protocol compatible with mass spectrometry. The performance is demonstrated by imaging a challenging sample (>90% water) of a mature Pseudomonas aeruginosa biofilm in its native state. The 3D distribution of quorum sensing signaling molecules, nucleobases, and bacterial membrane molecules is revealed with high spatial-resolution and high mass-resolution. We discover that analysis in the frozen-hydrated state yields a 10 000-fold increase in signal intensity for polar molecules such as amino acids, which has important implications for SIMS imaging of metabolites and pharmaceuticals.

OrbiSIMS Imaging Identifies Molecular Constituents of the Perialgal Vacuole Membrane of Paramecium bursaria with Symbiotic Chlorella variabilis.

The protist (mostly single-celled organisms), Paramecium bursaria, forms an intracellular symbiotic relationship with the single-celled algae, Chlorella variabilis, where P. bursaria provides nutrients (i.e., Ca2+, Mg2+, and K+), carbon dioxide for photosynthesis and protection from viruses, while C. variabilis provides oxygen, carbon fixation, and nutrients. Key to this successful relationship is the perialgal vacuole (PV) membrane, which surrounds C. variabilis and protects it from digestion by P. bursaria. The membrane is fragile and difficult to analyze using conventional methods therefore very little is known about the molecular composition. We used the OrbiSIMS, a new high-resolution mass spectrometer with subcellular resolution imaging, to study the compartmentalization of endosymbionts and elucidate biomolecular interactions between the host and endosymbiont. Ions from the region of interest, close to C. variabilis, and specific to the target samples containing PVs were found based on the chemical mapping and masses of the ions. We show chemical localizations of oligosaccharides in close proximity of C. variabilis endosymbionts in P. bursaria. These oligosaccharides are detected in host-endosymbiont samples containing PV membrane-bound algae and absent in free-living algae and digestive vacuole (DV) membrane-bound algae in P. bursaria.

Metabolic Imaging at the Single-Cell Scale: Recent Advances in Mass Spectrometry Imaging.

There is an increasing appreciation that every cell, even of the same type, is different. This complexity, when additionally combined with the variety of different cell types in tissue, is driving the need for spatially resolved omics at the single-cell scale. Rapid advances are being made in genomics and transcriptomics, but progress in metabolomics lags. This is partly because amplification and tagging strategies are not suited to dynamically created metabolite molecules. Mass spectrometry imaging has excellent potential for metabolic imaging. This review summarizes the recent advances in two of these techniques: matrix-assisted laser desorption ionization (MALDI) and secondary ion mass spectrometry (SIMS) and their convergence in subcellular spatial resolution and molecular information. The barriers that have held back progress such as lack of sensitivity and the breakthroughs that have been made including laser-postionization are highlighted as well as the future challenges and opportunities for metabolic imaging at the single-cell scale.

Chemical Imaging of Buried Interfaces in Organic-Inorganic Devices Using Focused Ion Beam-Time-of-Flight-Secondary-Ion Mass Spectrometry.

Organic-inorganic hybrid materials enable the design and fabrication of new materials with enhanced properties. The interface between the organic and inorganic materials is often critical to the device's performance; therefore, chemical characterization is of significant interest. Because the interfaces are often buried, milling by focused ion beams (FIBs) to expose the interface is becoming increasingly popular. Chemical imaging can subsequently be obtained using secondary-ion mass spectrometry (SIMS). However, the FIB milling process damages the organic material. In this study, we make an organic-inorganic test structure to develop a detailed understanding of the processes involved in FIB milling and SIMS imaging. We provide an analysis methodology that involves a "clean-up" process using sputtering with an argon gas cluster ion source to remove the FIB-induced damage. The methodology is evaluated for two additive manufactured devices, an encapsulated strain sensor containing silver tracks embedded in a polymeric material and a copper track on a flexible polymeric substrate created using a novel nanoparticle sintering technique.

Construction and testing of an atmospheric-pressure transmission-mode matrix assisted laser desorption ionisation mass spectrometry imaging ion source with plasma ionisation enhancement.

Matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) at atmospheric pressure (AP) is, with a few notable exceptions, overshadowed by its vacuum based forms and AP transmission mode (TM) MALDI-MS lacks the up-take its potential benefits might suggest. The reasons for this are not fully understood and it is clear further development is required to realise the flexibility and power of this ionisation method and geometry. Here we report the build of a new AP-TM-MALDI-MSI ion source with plasma ionisation enhancement. This novel ion source is used to analyse a selection of increasingly complex systems from molecular standards to murine brain tissue sections. Significant enhancement of detected ion intensity is observed in both positive and negative ion mode in all systems, with up to 2000 fold increases observed for a range of tissue endogenous species. The substantial improvements conferred by the plasma enhancement are then employed to demonstrate the acquisition of proof of concept tissue images, with high quality spectra obtained down to 10 × 10 µm pixel size.

Improving Reproducibility in Research: The Role of Measurement Science.

We report on a workshop held 1-3 May 2018 at the National Physical Laboratory, Teddington, U.K., in which the focus was how the world's national metrology institutes might help to address the challenges of reproducibility of research.The workshop brought together experts from the measurement and wider research communities in physical sciences, data analytics, life sciences, engineering, and geological science. The workshop involved 63 participants from metrology laboratories (38), academia (16), industry (5), funding agencies (2), and publishers (2). The participants came from the U.K., the United States, Korea, France, Germany, Australia, Bosnia and Herzegovina, Canada, Turkey, and Singapore.Topics explored how good measurement practice and principles could foster confidence in research findings and how to manage the challenges of increasing volume of data in both industry and research.