Effect of image resolution on automated classification of chest X-rays.

Purpose: Deep learning (DL) models have received much attention lately for their ability to achieve expert-level performance on the accurate automated analysis of chest X-rays (CXRs). Recently available public CXR datasets include high resolution images, but state-of-the-art models are trained on reduced size images due to limitations on graphics processing unit memory and training time. As computing hardware continues to advance, it has become feasible to train deep convolutional neural networks on high-resolution images without sacrificing detail by downscaling.

The Role of SnO Processing on Ionic Distribution in Double-Cation-Double Halide Perovskites.

Moving toward a future of efficient, accessible, and less carbon-reliant energy devices has been at the forefront of energy research innovations for the past 30 years. Metal-halide perovskite (MHP) thin films have gained significant attention due to their flexibility of device applications and tunable capabilities for improving power conversion efficiency. Serving as a gateway to optimize device performance, consideration must be given to chemical synthesis processing techniques.

Correlated mechanochemical maps of primary cell walls using atomic force microscope infrared spectroscopy.

Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact epidermal cell walls.

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data.

Dual-analgesic loaded UHMWPE exhibits synergistic antibacterial effects against Staphylococci.

Total joint arthroplasty is one of the most common surgeries in the United States, with almost a million procedures performed annually. Periprosthetic joint infections (PJI) remain the most devastating complications associated with total joint replacement. Effective antibacterial prophylaxis after primary arthroplasty could substantially reduce incidence rate of PJI.

In with the old, in with the new: machine learning for time to event biomedical research.

The predictive modeling literature for biomedical applications is dominated by biostatistical methods for survival analysis, and more recently some out of the box machine learning approaches. In this article, we show a presentation of a machine learning method appropriate for time-to-event modeling in the area of prostate cancer long-term disease progression. Using XGBoost adapted to long-term disease progression, we developed a predictive model for 118 788 patients with localized prostate cancer at diagnosis from the Department of Veterans Affairs (VA).

Direct Multimodal Nanoscale Visualization of Early Phosphorus-Based Antiwear Tribofilm Formation.

Understanding the mechanism of antiwear (AW) tribofilm formation and how to tune surface chemistry to control functionality is essential for the development of the next generation of oil lubricants. In particular, understanding and optimizing early AW tribofilm formation can increase the energy efficiency of mechanical systems. However, the mechanism for how these films form is not well understood.

Microstructural Evaluation of Phase Instability in Large Bandgap Metal Halide Perovskites.

The optoelectronic performance of organic-inorganic halide perovskite (OIHP)-based devices has been improved in recent years. Particularly, solar cells fabricated using mixed-cations and mixed-halides have outperformed their single-cation and single-halide counterparts. Yet, a systematic evaluation of the microstructural behavior of mixed perovskites is missing despite their known composition-dependent photoinstability.

Role of Decomposition Product Ions in Hysteretic Behavior of Metal Halide Perovskite.

Ion migration is one of the most debated mechanisms and credited with multiple observed phenomena and performance in metal halide perovskites (MHPs) semiconductor devices. However, to date, the migration of ions and their effects on MHPs are not still fully understood, largely due to a lack of direct observations of temporal ion migration. In this work, using direct observation of ion migration , we observe the hysteretic migration behavior of intrinsic ions (, CHNH and I) as well as reveal the migration behavior of CHNH decomposition ions.

Correlating Crystallographic Orientation and Ferroic Properties of Twin Domains in Metal Halide Perovskites.

Metal halide perovskite (MHP) solar cells have attracted worldwide research interest. Although it has been well established that grain, grain boundary, and grain facet affect MHPs optoelectronic properties, less is known about subgrain structures. Recently, MHP twin stripes, a subgrain feature, have stimulated extensive discussion due to the potential for both beneficial and detrimental effects of ferroelectricity on optoelectronic properties.

Enhancing hyperspectral EELS analysis of complex plasmonic nanostructures with pan-sharpening.

Nanoscale hyperspectral techniques-such as electron energy loss spectroscopy (EELS)-are critical to understand the optical response in plasmonic nanostructures, but as systems become increasingly complex, the required sampling density and acquisition times become prohibitive for instrumental and specimen stability. As a result, there has been a recent push for new experimental methodologies that can provide comprehensive information about a complex system, while significantly reducing the duration of the experiment. Here, we present a pan-sharpening approach to hyperspectral EELS analysis, where we acquire two datasets from the same region (one with high spatial resolution and one with high spectral fidelity) and combine them to achieve a single dataset with the beneficial properties of both.

Nanoscale Mass Spectrometry Multimodal Imaging Tip-Enhanced Photothermal Desorption.

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature.

Hysteretic Ion Migration and Remanent Field in Metal Halide Perovskites.

The gap in understanding how underlying chemical dynamics impact the functionality of metal halide perovskites (MHPs) leads to the controversy about the origin of many phenomena associated with ion migration in MHPs. In particular, the debate regarding the impact of ion migration on current-voltage (-) hysteresis of MHPs devices has lasted for many years, where the difficulty lies in directly uncovering the chemical dynamics, as well as identifying and separating the impact of specific ions. In this work, using a newly developed time-resolved time-of-flight secondary ion mass spectrometry CHNH and I migrations in CHNHPbI are directly observed, revealing hysteretic CHNH and I migrations.

Nanomechanical sampling of material for nanoscale mass spectrometry chemical analysis.

The ability to spatially resolve the chemical distribution of compounds on a surface is important in many applications ranging from biological to material science. To this extent, we have recently introduced a hybrid atomic force microscopy (AFM)-mass spectrometry (MS) system for direct thermal desorption and pyrolysis of material with nanoscale chemical resolution. However, spatially resolved direct surface heating using local thermal desorption becomes challenging on material surfaces with low melting points, because the material will undergo a melting phase transition due to heat dissipation prior to onset of thermal desorption.

Direct Write of 3D Nanoscale Mesh Objects with Platinum Precursor via Focused Helium Ion Beam Induced Deposition.

The next generation optical, electronic, biological, and sensing devices as well as platforms will inevitably extend their architecture into the 3rd dimension to enhance functionality. In focused ion beam induced deposition (FIBID), a helium gas field ion source can be used with an organometallic precursor gas to fabricate nanoscale structures in 3D with high-precision and smaller critical dimensions than focused electron beam induced deposition (FEBID), traditional liquid metal source FIBID, or other additive manufacturing technology. In this work, we report the effect of beam current, dwell time, and pixel pitch on the resultant segment and angle growth for nanoscale 3D mesh objects.

Two-Photon Up-Conversion Photoluminescence Realized through Spatially Extended Gap States in Quasi-2D Perovskite Films.

A new approach to generate a two-photon up-conversion photoluminescence (PL) by directly exciting the gap states with continuous-wave (CW) infrared photoexcitation in solution-processing quasi-2D perovskite films [(PEA) (MA) Pb Br with n = 5] is reported. Specifically, a visible PL peaked at 520 nm is observed with the quadratic power dependence by exciting the gap states with CW 980 nm laser excitation, indicating a two-photon up-conversion PL occurring in quasi-2D perovskite films. Decreasing the gap states by reducing the n value leads to a dramatic decrease in the two-photon up-conversion PL signal.

Publisher Correction: Reply to: On the ferroelectricity of CHNHPbI perovskites.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

High Resolution Multimodal Chemical Imaging Platform for Organics and Inorganics.

Chemical analysis at the nanoscale is critical to advance our understanding of materials and systems from medicine and biology to material science and computing. Macroscale-observed phenomena in these systems are in the large part driven by processes that take place at the nanoscale and are highly heterogeneous. Therefore, there is a clear need to develop a new technology that enables correlative imaging of material functionalities with nanoscale spatial and chemical resolutions that will enable us to untangle the structure-function relationship of functional materials.

Non-conventional mechanism of ferroelectric fatigue via cation migration.

The unique properties of ferroelectric materials enable a plethora of applications, which are hindered by the phenomenon known as ferroelectric fatigue that leads to the degradation of ferroelectric properties with polarization cycling. Multiple microscopic models explaining fatigue have been suggested; however, the chemical origins remain poorly understood. Here, we utilize multimodal chemical imaging that combines atomic force microscopy with time-of-flight secondary mass spectrometry to explore the chemical phenomena associated with fatigue in PbZrTiO (PZT) thin films.

Quantitative Electromechanical Atomic Force Microscopy.

The ability to probe a material's electromechanical functionality on the nanoscale is critical to applications from energy storage and computing to biology and medicine. Voltage-modulated atomic force microscopy (VM-AFM) has become a mainstay characterization tool for investigating these materials due to its ability to locally probe electromechanically responsive materials with spatial resolution from micrometers to nanometers. However, with the wide popularity of VM-AFM techniques such as piezoresponse force microscopy and electrochemical strain microscopy there has been a rise in reports of nanoscale electromechanical functionality, including hysteresis, in materials that should be incapable of exhibiting piezo- or ferroelectricity.

Multimodal Chemical Imaging for Linking Adhesion with Local Chemistry in Agrochemical Multicomponent Polymeric Coatings.

Seed coatings improve germination and offer higher crop yields through a blend of active ingredients (such as insecticides and fungicides), polymers, waxes, fillers, and pigments. To reach their full potential, fundamental formulation challenges bridging structure and function need to be addressed. In some instances, during industrial-volume packing and transportation, coated seeds do not flow well through elevators, conveyers, and applicators, which may reduce yield and add cost.