搜索结果：Accounts of materials research

Metallophthalocyanine-based metal-organic frameworks (MPc-based MOFs) have recently emerged as a class of two-dimensional (2D) materials with unique tunability for control over both structural properties and growing applications. MPc-based MOFs possess a unique set of structural characteristics due to the combination of a two-dimensional, sheet-like, porous structure and a modular, bimetallic molecularly precise chemical composition that result in emergent properties, such as electrical conductivity, modular surface chemistry, and tunable stacking properties. This combination of physical, chemical, and structural modularity has led to the promising demonstrations of MPc-based MOFs within a wide range of applications, including chemical sensing, catalysis, energy storage, and magnetoresistivity. While recent research regarding structure-property relationships of these materials has significantly advanced this field, the exploration of this class of 2D conductive MOFs has been limited by factors including the synthetic accessibility of both the functionalized MPc monomer and the crystalline framework materials, as well as the lack of structural clarity due to limitations in producing sufficiently large ordered crystals suitable for single crystal X-ray diffraction. Systematic investigation of structure-property relationships, enabled by careful control over synthetic parameters and device integration techniques, are essential for advancing the fundamental understanding and capitalizing on the applied potential of this class of materials. This Account summarizes the development of MPc-based MOFs as a privileged class within the realm of conductive 2D framework materials. Furthermore, this Account highlights key contributions from our group, with a particular focus on how chemical modulation within MPc building blocks dictates the resulting MOF structures and their functional performance. Capitalizing on the beneficial properties of the MPc building blocks, the structural modularity of these materials provides unique access to systematic investigations of structure-property relationships. Structure-property related insights make it possible to elucidate the role of the metal within the MPc core, the bridging metal, and the heteroatomic linker on the functional performance of these materials in the context of electronically transduced chemical sensing and electrocatalysis. The multifaceted utility of this class of materials is also highlighted in both energy storage applications and magnetoresistive devices. Through a combination of iterative synthetic efforts, characterization studies, and systematic investigations into electrical devices incorporating MPc-based MOFs, this Account demonstrates that these materials are prime candidates for use in electronically transduced devices where molecular-level control can be leveraged to maximize device performance metrics. Taken together, these achievements establish MPc-based MOFs as a promising class of materials with high potential within the field of functional nanoscience.

Since the advent of the Haber-Bosch process in 1910, the global demand for ammonia (NH3) has surged, driven by its applications in agriculture, pharmaceuticals, and energy. Current methods of NH3 storage, including high-pressure storage and transportation, present significant challenges due to their corrosive and toxic nature. Consequently, research has turned towards metal-organic framework (MOF) materials as potential candidates for NH3 storage due to their potential high adsorption capacities and structural tunability. MOFs are coordination networks composed of metal nodes and organic linkers, offering unprecedented porosity and surface area, and allowing incorporation of various functional groups and metal sites that can enhance NH3 adsorption. However, the stability of MOFs in the presence of NH3 is a significant concern since many degrade upon exposure to NH3, primarily due to ligand displacement and framework collapse. To address this, recent studies have focused on the synthesis and postsynthetic modification of MOFs to enhance both NH3 uptake and stability. In this Account, we summarize recent developments in the design and characterization of MOFs for NH3 storage. The choice of metal centers in MOFs is crucial for stability and performance. High-valence metals such as AlIII and TiIV form strong metal-linker bonds, enhancing the stability of the framework to NH3. The MFM-300 series of materials composed of high-valence 3+ and 4+ metal ions and carboxylic linkers demonstrates high stability and high NH3 uptake capacities. Ligand functionalization is another effective strategy for improving the NH3 adsorption. Polar functional groups such as -NH2, -OH, and -COOH enhance the interaction between the framework and NH3, particularly at low partial pressures, while postsynthetic modification allows fine-tuning of these functionalities to optimize the framework for higher adsorption capacities and stability. For example, MFM-303(Al), incorporating free carboxylic acid groups, exhibits a high NH3 packing density comparable to that of solid NH3. Creating defect sites by removing linkers or adding metal ions increases the number of active sites available for NH3 adsorption and shows promise for enhancing uptake. UiO-66, a stable MOF framework, can be modified to include defect sites, significantly enhancing the level of NH3 uptake. The full characterization of MOFs and especially their interactions with NH3 are vital for understanding and improving their performance. Techniques such as neutron powder diffraction (NPD), inelastic neutron scattering (INS), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), electron paramagnetic resonance (EPR) spectroscopy, and solid-state nuclear magnetic resonance (ssNMR) spectroscopy can elucidate host-guest interactions and binding dynamics between NH3 and the framework structure and afford crucial information for the future design and rational development of new sorbents. This Account highlights our current strategies for the synthesis and characterization of MOFs for NH3 capture, providing an overview of this rapidly evolving field.

This Account presents surface electrochemical nanopatterning as a powerful and underexplored strategy for engineering the electronic and functional properties of electrochemically active materials. By enabling precise, localized manipulation of electronic states at the micro- and nanoscale, this technique offers a unique pathway to unlock and control intrinsic material properties. These capabilities open new frontiers in materials science, with implications ranging from catalysis to the fabrication of advanced, multifunctional devices. Traditional lithographic techniques, such as photolithography, electron beam lithography, and nanoimprinting, mainly focus on shaping surface topography. In contrast, electrochemical nanopatterning introduces a fundamentally different approach: it modifies the material itself. By changing oxidation states, creating or healing defects, and tuning surface chemistry, this method allows for direct control of material properties. Consequently, it greatly expands the range of applications, enabling the development of materials with customized electronic and functional features. This Account focuses specifically on stamp-assisted electrochemical lithography (ECL), a versatile and scalable technique. We start by outlining the fundamental principles of ECL, including the electrochemical processes that drive it, namely oxidation, reduction, and defect generation. Next, we trace its historical development and highlight its advantages over traditional nanofabrication methods, particularly in terms of simplicity, cost-effectiveness, and compatibility with a wide range of materials. Through a curated selection of case studies, we demonstrate how ECL can be used to (i) generate and tune electronic properties, (ii) impart various functional behaviors, and (iii) achieve spatially controlled defect engineering, especially in semiconductors. Crucially, the ability to fabricate large-area samples has allowed us to harness size-dependent properties that were previously inaccessible in electrochemical nanolithography performed via scanning probe techniques, such e catalysis and the in situ fabrication of nanoclusters. These findings dramatically expand the scientific and technological potential of ECL, opening new avenues for innovation and application. The example cases were selected for their relevance to current challenges in materials science and emerging technologies. Notable applications include in situ healing in resistive switching devices, the development of critical-element-free catalysts, and the direct fabrication of active components within devices. Many of these studies were pioneering at the time of publication and have only recently gained broader recognition due to the growing interest in sustainable, low-cost, and scalable nanofabrication techniques. We emphasize ECL's unique capabilities in enabling regenerable resistive switching, spatially selective nanoembedding of functional nanoparticles, and creating functional surface patterns. These features position ECL as a promising tool for bridging the gap between fundamental research and practical device integration. Moreover, the method's compatibility with ambient conditions and its potential for large-area processing make it particularly attractive for industrial applications. In the final section, we discuss the frontier and the perspectives of ECL. We propose strategies to enhance resolution, reproducibility, and integration with existing manufacturing platforms. We also outline future directions, including the development of hybrid patterning approaches. Looking ahead, we envision ECL playing a central role in the development of next-generation materials and devices, particularly in fields where precise control over local properties is essential for both performance and functionality.

ChatGPT is a large language model-based chatbot developed by OpenAI. ChatGPT has many potential applications to health care, including enhanced diagnostic accuracy and efficiency, improved treatment planning, and better patient outcomes. However, health care professionals' perceptions of ChatGPT and similar artificial intelligence tools are not well known. Understanding these attitudes is important to inform the best approaches to exploring their use in medicine. Our aim was to evaluate the health care professionals' awareness and perceptions regarding potential applications of ChatGPT in the medical field, including potential benefits and challenges of adoption. We designed a 33-question online survey that was distributed among health care professionals via targeted emails and professional Twitter and LinkedIn accounts. The survey included a range of questions to define respondents' demographic characteristics, familiarity with ChatGPT, perceptions of this tool's usefulness and reliability, and opinions on its potential to improve patient care, research, and education efforts. One hundred and fifteen health care professionals from 21 countries responded to the survey, including physicians, nurses, researchers, and educators. Of these, 101 (87.8%) had heard of ChatGPT, mainly from peers, social media, and news, and 77 (76.2%) had used ChatGPT at least once. Participants found ChatGPT to be helpful for writing manuscripts (n=31, 45.6%), emails (n=25, 36.8%), and grants (n=12, 17.6%); accessing the latest research and evidence-based guidelines (n=21, 30.9%); providing suggestions on diagnosis or treatment (n=15, 22.1%); and improving patient communication (n=12, 17.6%). Respondents also felt that the ability of ChatGPT to access and summarize research articles (n=22, 46.8%), provide quick answers to clinical questions (n=15, 31.9%), and generate patient education materials (n=10, 21.3%) was helpful. However, there are concerns regarding the use of ChatGPT, for example, the accuracy of responses (n=14, 29.8%), limited applicability in specific practices (n=18, 38.3%), and legal and ethical considerations (n=6, 12.8%), mainly related to plagiarism or copyright violations. Participants stated that safety protocols such as data encryption (n=63, 62.4%) and access control (n=52, 51.5%) could assist in ensuring patient privacy and data security. Our findings show that ChatGPT use is widespread among health care professionals in daily clinical, research, and educational activities. The majority of our participants found ChatGPT to be useful; however, there are concerns about patient privacy, data security, and its legal and ethical issues as well as the accuracy of its information. Further studies are required to understand the impact of ChatGPT and other large language models on clinical, educational, and research outcomes, and the concerns regarding its use must be addressed systematically and through appropriate methods.

Lignocellulosic biomass is an ideal feedstock for the next generation of sustainable, high-performance, polymeric materials. Although lignin is a highly available and low-cost source of natural aromatics, it is commonly burned for heat or disposed of as waste. The use of lignin for new materials introduces both challenges and opportunities with respect to incumbent petrochemical-based compounds. These considerations are derived from two fundamental aspects of lignin: its recalcitrant/heterogeneous nature and aromatic methoxy substituents. This Account highlights four key efforts from the Epps group and collaborators that established innovative methods/processes to synthesize polymers from lignin deconstruction products to unlock application potential, with a particular focus on the polymerization of biobased monomer mixtures, development of structure-property-processing relationships for diverse feedstocks, functional benefits of methoxy substituents, and scalability of lignin deconstruction. First, lignin-derivable polymethacrylate systems were probed to investigate the polymerization behavior of methacrylate monomers and predict thermomechanical properties of polymers from monomer mixtures. Notably, the glass transition temperatures (T gs) of lignin-derivable polymethacrylates (∼100-200 °C) were comparable to, or significantly above, those of petroleum-based analogues, such as polystyrene (∼100 °C), and the T gs of the complex, biobased copolymers could be predicted by the Fox equation prior to biomass deconstruction. Second, an understanding of structure-property relationships in polymethacrylates was applied to create performance-advantaged pressure-sensitive adhesives (PSAs) using phenolic-rich bio-oil obtained from the reductive catalytic fractionation of poplar wood. The use of actual lignin-derived monomers as the starting material was an important step because it underscored that nanostructure-forming, multiblock polymers could be readily made despite the complexity of real lignin deconstruction products. This work also highlighted that lignin-based phenolics could be used to make colorless/odorless PSAs, without complex separations/purifications, and still perform as well as commercial adhesives. Third, an intensified reductive catalytic deconstruction (RCD) process was developed to deconstruct lignin at ambient conditions, and the deconstructed products were successfully employed in 3D printing. The reactive distillation-RCD process operated at ambient pressure using a low-volatility and biobased solvent (glycerin) as a hydrogen donor, which reduced capital/operating costs, energy use, and safety hazards associated with conventional RCD. Technoeconomic analysis showed that such optimization could lead to a 60% reduction in cost to make the PSAs described above. Fourth, lignin-derivable bisguaiacols/bissyringols were explored as potential alternatives to petroleum-derived bisphenol A (BPA) in diamine-cured epoxy resins. A distinguishing feature of the lignin monomers (vs. BPA/bisphenol F [BPF]) was the presence of methoxy groups on the aromatic rings, and these methoxy moieties enabled tuning of application-specific properties, such as T g, degradation temperature (T d), and glassy storage modulus (E'), to achieve improved processing and performance. The lignin-derivable thermosets exhibited T gs above 100 °C, T ds above 300 °C, and E's above 2 GPa, all values that were comparable to those of BPA-/BPF-based analogues. Moreover, the methoxy groups on these lignin-derivable compounds sterically hindered hormone receptor binding and could mitigate many of the toxicity concerns associated with BPA/BPF. This Account concludes with suggestions on future research needed to advance lignin-derived materials as sustainable and performance-advantaged alternatives by leveraging recycling/upcycling strategies and scaling-up/commercializing biomass waste.

Life activities, such as respiration, are accomplished through the continuous shape modulation of cells, tissues, and organs. Developing smart materials with shape-morphing capability is a pivotal step toward life-like systems and emerging technologies of wearable electronics, soft robotics, and biomimetic actuators. Drawing inspiration from cells, smart vesicular systems have been assembled to mimic the biological shape modulation. This would enable the understanding of cellular shape adaptation and guide the design of smart materials with shape-morphing capability. Polymer vesicles assembled by amphiphilic molecules are an example of remarkable vesicular systems. The chemical versatility, physical stability, and surface functionality promise their application in nanomedicine, nanoreactor, and biomimetic systems. However, it is difficult to drive polymer vesicles away from equilibrium to induce shape transformation due to the unfavorable energy landscapes caused by the low mobility of polymer chains and low permeability of the vesicular membrane. Extensive studies in the past decades have developed various methods including dialysis, chemical addition, temperature variation, polymerization, gas exchange, etc., to drive shape transformation. Polymer vesicles can now be engineered into a variety of nonspherical shapes. Despite the brilliant progress, most of the current studies regarding the shape transformation of polymer vesicles still lie in the trial-and-error stage. It is a grand challenge to predict and program the shape transformations of polymer vesicles. An in-depth understanding of the deformation pathway of polymer vesicles would facilitate the transition from the trial-and-error stage to the computing stage. In this Account, we introduce recent progress in the shape transformation of polymer vesicles. To provide an insightful analysis, the shape transformation of polymer vesicles is divided into basic and coupled deformation. First, we discuss the basic deformation of polymer vesicles with a focus on two deformation pathways: the oblate pathway and the prolate pathway. Strategies used to trigger different deformation pathways are introduced. Second, we discuss the origin of the selectivity of two deformation pathways and the strategies used to control the selectivity. Third, we discuss the coupled deformation of polymer vesicles with a focus on the switch and coupling of two basic deformation pathways. Last, we analyze the challenges and opportunities in the shape transformation of polymer vesicles. We envision that a systematic understanding of the deformation pathway would push the shape transformation of polymer vesicles from the trial-and-error stage to the computing stage. This would enable the prediction of deformation behaviors of nanoparticles in complex environments, like blood and interstitial tissue, and access to advanced architecture desirable for man-made applications.

As a ubiquitous feature of the biological world, gradation, in either composition or structure, is essential to many functions and processes. Taking protein gradation as an example, it plays a pivotal role in the development and evolution of human bodies, including stimulation and direction of the outgrowth of peripheral nerves in a developing fetus. It is also critically involved in wound healing by attracting and guiding immune cells to the site of injury or infection. Another good example can be found in the tendon-to-bone enthesis that relies on gradations in composition, structure, and cell phenotype to create a gradual change in mechanical stiffness. It is these unique gradations that eliminate the high level of stress at the interface, enabling the effective transfer of mechanical load from tendon to bone. How to fabricate and utilize graded surfaces and materials has been a constant theme of research in the context of materials science, chemistry, cell biology, and biomedical engineering. In cell biology, for example, graded surfaces are employed to investigate the fundamental mechanisms related to embryo development and to elucidate cell behaviors under chemo-, hapto-, or mechano-taxis. Scaffolds based upon graded materials have also been widely explored to enhance tissue repair or regeneration by accelerating cell migration and/or controlling stem cell differentiation. In this Account, we review our efforts in the fabrication and utilization of functionally graded surfaces. The gradation typically occurs as gradual changes in terms of composition, structure (e.g., pore size or fiber alignment), and/or coverage density of molecular species or larger objects such as particles and cells. Specifically, we focus on two strategies for generating various types of gradations along the surface of a substrate. In the first strategy, the substrate is vertically placed in a container, followed by the addition of a solution containing the functional component at a constant rate. Owing to the variations in contact time, the amount of the component deposited on the substrate naturally takes a gradual change along the vertical direction. In the second strategy, a moving collector or mask is used to control the amount of the component deposited on a substrate during jet printing or electrospray. As for applications, we highlight the following examples: (i) promotion of neurite outgrowth for peripheral nerve repair; (ii) acceleration of cell migration for wound closure; and (iii) mimicking of the structure and/or force transition at the tendon-to-bone enthesis for interfacial tissue engineering. The surface gradation can be presented in a uniaxial or radial fashion, and further integrated with the structural features on the underlying substrate to suit a specific application. In addition to general issues such as diversity of the surface gradation and reproducibility of the fabrication method, we also offer perspectives on new directions for future development. The systems and strategies discussed in this Account are expected to open the door to a range of fundamental inquires while enabling various biological and biomedical applications.

Soft gels, a category of soft materials, consist of polymer networks with small molecules, such as water or other solvents. They possess mechanical flexibility and softness along with tunable physical and chemical functionalities. These gels are capable of responding to external stimuli, such as temperature, pH, light, and electric and magnetic fields, making them highly suitable for applications in drug delivery, tissue engineering, sensors, and soft robotics. As many advantages as soft gels have, there are many more mechanisms to be understood to bridge clear structure-function relationships. There is also a continuous need to facilitate these new functionalities into the device or product technologies. In this Account, we aim to provide an overview of recent progress in functional soft gels with a focus on structural design and innovative fabrication techniques. We start with exploring how structural design can impart diverse functionalities to soft gels. This is followed by a discussion of mechanics with an emphasis on elastic instabilities that are deliberately introduced and controlled to achieve shape morphing. The multilength scale instabilities will be linked with local to global surface deformation and/or macroscopic deformation of gel objects. We then examine how chemical modificationsespecially cross-linking and network formationcontribute to the architecture and functionality of soft gels. These chemical modifications have been harnessed to enrich the designability of the gel to enable extra function or provide dedicated controllability. Manufacturing techniques also play a vital role in establishing structural varieties that enable programmable responses to external stimuli for specific applications. We offer a quick scan on the frontier technologies on fabricating soft gel-based devices with an alignment to the advanced manufacturing trend with novelty structural design. Finally, the applications of functional soft gels were selectively scoped in areas such as sensing, energy and sustainable materials, and biomedical devices. They are well-suited for both diagnostic and therapeutic functions. All the above applications will be enabled by the novel structural design with realization of unique structure-property relationships. Designed structures can be programmed to exhibit specific mechanical behaviors, which, in turn, enable responsive and functional soft gels. Importantly, when a stimulus activates the designated trigger points, the engineered structure responds in the manner that we designed. This interplay within the gel ultimately manifests as a controllable response, highlighting how transformative structural engineering serves as the foundation for achieving multifunctionality. We conclude by highlighting the current challenges and future directions in the development of high-performance functional soft gels through structure-based design.

Comprehensive, comparable, and timely estimates of demographic metrics-including life expectancy and age-specific mortality-are essential for evaluating, understanding, and addressing trends in population health. The COVID-19 pandemic highlighted the importance of timely and all-cause mortality estimates for being able to respond to changing trends in health outcomes, showing a strong need for demographic analysis tools that can produce all-cause mortality estimates more rapidly with more readily available all-age vital registration (VR) data. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is an ongoing research effort that quantifies human health by estimating a range of epidemiological quantities of interest across time, age, sex, location, cause, and risk. This study-part of the latest GBD release, GBD 2023-aims to provide new and updated estimates of all-cause mortality and life expectancy for 1950 to 2023 using a novel statistical model that accounts for complex correlation structures in demographic data across age and time. We used 24 025 data sources from VR, sample registration, surveys, censuses, and other sources to estimate all-cause mortality for males, females, and all sexes combined across 25 age groups in 204 countries and territories as well as 660 subnational units in 20 countries and territories, for the years 1950-2023. For the first time, we used complete birth history data for ages 5-14 years, age-specific sibling history data for ages 15-49 years, and age-specific mortality data from Health and Demographic Surveillance Systems. We developed a single statistical model that incorporates both parametric and non-parametric methods, referred to as OneMod, to produce estimates of all-cause mortality for each age-sex-location group. OneMod includes two main steps: a detailed regression analysis with a generalised linear modelling tool that accounts for age-specific covariate effects such as the Socio-demographic Index (SDI) and a population attributable fraction (PAF) for all risk factors combined; and a non-parametric analysis of residuals using a multivariate kernel regression model that smooths across age and time to adaptably follow trends in the data without overfitting. We calibrated asymptotic uncertainty estimates using Pearson residuals to produce 95% uncertainty intervals (UIs) and corresponding 1000 draws. Life expectancy was calculated from age-specific mortality rates with standard demographic methods. For each measure, 95% UIs were calculated with the 25th and 975th ordered values from a 1000-draw posterior distribution. In 2023, 60·1 million (95% UI 59·0-61·1) deaths occurred globally, of which 4·67 million (4·59-4·75) were in children younger than 5 years. Due to considerable population growth and ageing since 1950, the number of annual deaths globally increased by 35·2% (32·2-38·4) over the 1950-2023 study period, during which the global age-standardised all-cause mortality rate declined by 66·6% (65·8-67·3). Trends in age-specific mortality rates between 2011 and 2023 varied by age group and location, with the largest decline in under-5 mortality occurring in east Asia (67·7% decrease); the largest increases in mortality for those aged 5-14 years, 25-29 years, and 30-39 years occurring in high-income North America (11·5%, 31·7%, and 49·9%, respectively); and the largest increases in mortality for those aged 15-19 years and 20-24 years occurring in Eastern Europe (53·9% and 40·1%, respectively). We also identified higher than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 5-14 years (87·3% higher in GBD 2023 than GBD 2021 on average across countries and territories over the 1950-2021 period) and for females aged 15-29 years (61·2% higher), as well as lower than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 50 years and older (13·2% lower), reflecting advances in our modelling approach. Global life expectancy followed three distinct trends over the study period. First, between 1950 and 2019, there were considerable improvements, from 51·2 (50·6-51·7) years for females and 47·9 (47·4-48·4) years for males in 1950 to 76·3 (76·2-76·4) years for females and 71·4 (71·3-71·5) years for males in 2019. Second, this period was followed by a decrease in life expectancy during the COVID-19 pandemic, to 74·7 (74·6-74·8) years for females and 69·3 (69·2-69·4) years for males in 2021. Finally, the world experienced a period of post-pandemic recovery in 2022 and 2023, wherein life expectancy generally returned to pre-pandemic (2019) levels in 2023 (76·3 [76·0-76·6] years for females and 71·5 [71·2-71·8] years for males). 194 (95·1%) of 204 countries and territories experienced at least partial post-pandemic recovery in age-standardised mortality rates by 2023, with 61·8% (126 of 204) recovering to or falling below pre-pandemic levels. There were several mortality trajectories during and following the pandemic across countries and territories. Long-term mortality trends also varied considerably between age groups and locations, demonstrating the diverse landscape of health outcomes globally. This analysis identified several key differences in mortality trends from previous estimates, including higher rates of adolescent mortality, higher rates of young adult mortality in females, and lower rates of mortality in older age groups in much of sub-Saharan Africa. The findings also highlight stark differences across countries and territories in the timing and scale of changes in all-cause mortality trends during and following the COVID-19 pandemic (2020-23). Our estimates of evolving trends in mortality and life expectancy across locations, ages, sexes, and SDI levels in recent years as well as over the entire 1950-2023 study period provide crucial information for governments, policy makers, and the public to ensure that health-care systems, economies, and societies are prepared to address the world's health needs, particularly in populations with higher rates of mortality than previously known. The estimates from this study provide a robust framework for GBD and a valuable foundation for policy development, implementation, and evaluation around the world. Gates Foundation.

Organic battery electrode materials are key enablers of different postlithium cell chemistries. As a p-type compound with up to two reversible redox processes at relatively high potentials of 3.5 and 4.1 V vs. Li/Li+, phenothiazine is an excellently suited redox-active group. It can easily be functionalized and incorporated into polymeric structures, a prerequisite to obtain insolubility in liquid battery electrolytes. Phenothiazine tends to exhibit π-interactions (π*-π*-interactions) to stabilize its radical cationic form, which can increase the stability of the oxidized form but can also strongly influence its cycling performance as a battery electrode material. In recent years, we investigated a broad range of phenothiazine-based polymers as battery electrode materials, providing insight into the effect of π-interactions on battery performance, leading to design principles for highly functional phenothiazine-based polymers, and enabling the investigation of full cells. We observed that π-interactions are particularly expressed in "mono"-oxidized forms of poly-(3-vinyl-N-methylphenothiazine) (PVMPT) and are enabled in the battery electrode due to the solubility of oxidized PVMPT in many carbonate-based liquid electrolytes. PVMPT dissolves during charge and is redeposited during discharge as a stable film on the positive electrode, however, still retaining half of its charge. This diminishes its available specific capacity to half of the theoretical value. We followed three different strategies to mitigate dissolution and inhibit the formation of π-interactions in order to access the full specific capacity for the one-electron process: Adjusting the electrolyte composition (type and ratio of cyclic vs. linear carbonate), encapsulating PVMPT in highly porous conductive carbons or cross-linking the polymer to X-PVMPT. All three strategies are excellently suited to pursue full-cell concepts using PVMPT or X-PVMPT as positive electrode material. The extent of π-interactions could also be modified by structural changes regarding the polymer backbone (polystyrene or polynorbornene) or exchanging the heteroatom sulfur in phenothiazine by oxygen in phenoxazine. By changing the molecular design and attaching electron-donating methoxy groups to the phenothiazine units, its second redox process can be reversibly enabled, even in carbonate-based electrolytes. Studies by us as well as others provided a selection of high-performing phenothiazine polymers. Their applicability was demonstrated as positive electrode in full cells of different configurations, including dual-ion battery cells using an inorganic or organic negative electrode, anion-rocking-chair cells as examples of all-organic batteries, or even an aluminum battery with a performance exceeding that of aluminum-graphite battery cells. In changing the design concept to conjugated phenothiazine polymers, a higher intrinsic semiconductivity can result, enabling the use of a lesser amount of the conductive carbon additive in the composite electrode. It also provides a handle to alter the optical properties of the polymers, for instance by designing donor-acceptor type conjugated polymers with visible-light absorption, where we demonstrated an application in a photobattery. This Account provides an overview of these findings, also in the context of other literature in the field. It highlights phenothiazine polymers as versatile electrode materials for next-generation batteries.

The ability to gather information about materials and products, such as their origin, physicochemical properties or history of experienced environmental stimuli, is valuable for quality control, predictive maintenance, delivery tracking, recycling, and more. Integrating additives capable of recording and storing information into materials offers a flexible approach to create "materials intelligence". Common strategies utilize luminescent markers or DNA sequences that enable object identification and environmental impact monitoring. In contrast to optical methods limited to surface-level analysis, magnetic fields penetrate materials, enabling nondestructive readout even from the inside of opaque or multicomponent objects. While magnetic particle technologies have traditionally been used for biosensing and imaging with highly sensitive instruments like magnetic resonance imaging, these methods are unsuitable for quick, on-site analysis of macroscopic objects. During the past decade, magnetic particle spectroscopy (MPS) has emerged as a faster and more accessible characterization technique. MPS measures the magnetic response of particles in ambient conditions under alternating fields, offering high temporal resolution (∼1-10 s) and more geometric freedom than other magnetometry techniques. Magnetic nanoparticles are a widely studied material class that have been synthesized and optimized, e.g., for various MPS-based application scenarios and to obtain fundamental understanding of magnetic particle systems. Supraparticles (SPs) represent the next structural hierarchy level, as they are composed of one or multiple types of (magnetic) nanoparticles in a defined particulate structure. By ingenious control of structure and composition of such SPs, we have shown that various kinds of information can be obtained from them upon readout with MPS. In this Account, we present SP design concepts facilitating to obtain information about environmental stimuli (e.g., temperature, moisture, UV light, chemical gases) based on irreversible spectral magnetic signal changes upon readout with MPS. Initially, the state of the art on nanoparticles, which provide information by stimulus-induced agglomeration, is summarized. Subsequently, SPs consisting of multiple different nanoparticle types and their capabilities to obtain information on environmental stimuli are considered. Specifically, the advantages of using one or more signal transducing magnetic nanoparticle types used in conjunction with one or more nonmagnetic secondary materials susceptible to the desired environmental stimuli (sensitizer) are discussed. Finally, our latest findings on pronounced large-scale SP structure formation (millimeter-scale) through strongly interacting SPs and their implications on the integration of SPs in macroscopic objects of interest are described. Each of the three structural hierarchy levels, namely nanoparticles, SPs, and the macroscopic object of interest, represents an opportunity on the material level to fine-tune magnetic interactions. However, since the magnetic interactions across these three structural hierarchy levels are interdependent, meaning changes at the nanoparticle level influence the interactions of SPs at the macroscopic level, their control and interpretation in MPS remain challenging and prone to misinterpretation. The application of magnetic SPs as information-providing additives for predictive maintenance, material reuse, recycling, and industrial digitization requires a thorough understanding of all three hierarchical levels. Only then can suitable materials and processes be developed, turning challenges into opportunities for transforming passive matter into perceptual, information-providing systems through the integration of magnetic SPs.

Cholesteric liquid crystals (CLCs) are famous for their ability to self-assemble into Bragg reflectors of visible light, yielding intense structural color with a single circular polarization, despite flowing like a liquid. This review focuses on a selection of entirely new opportunities to apply CLCs to solve problems with high societal and industrial relevance, as demonstrated in proof-of-concept experiments with a transition to commercial application underway, in contexts quite far from the more traditional applied role of CLCs as thermometers. We now see a renaissance of applied CLC research resulting in exciting new functional materials taking advantage of CLC photonics, often displaying unique types of responsiveness. This development has been enabled, first, by recent advances in formulating CLC mixtures with reactive mesogens such that they can be processed as a liquid but used as a hard glass or rubber after polymerization and cross-linking, keeping the photonic performance generated by CLC self-assembly intact. Second, the rapid development of advanced liquid processing methods like microfluidic production of multiple emulsions, 3D printing and composite fiber spinning have allowed the CLCs to be processed into unconventional form factors prior to cross-linking. The review focuses, first, on CLC-templated hard spheres exhibiting omnidirectional circularly polarized Bragg reflection, so-called Cholesteric Spherical Reflectors, or CSRs. They can be used to make artificial "fingerprints" for physical objects that act as Physical Unclonable Functions, of great interest in secure authentication, or to print QR-codes or similar machine-readable patterns in a way that they remain invisible to humans while appearing to the intended machines with exceptional contrast. Since each CSR is effectively a pixel of structural color, we can also use them as a versatile solution for coloring without absorption or scattering, also enabling nonspectral colors like shades of gray that are normally not obtainable with structural color. A related application discussed is the camouflage of solar panels using polymerized CLC films to replace their visually obtrusive black appearance with color generated by CLCs, with almost no loss of energy conversion efficiency thanks to its origin in Bragg reflection. We then move to soft rubbery CLC elastomer (CLCE) films and fibers which change their color in response to strain. We highlight a new application opportunity in structural health monitoring, demonstrated by coating CLCE films onto surfaces where we wish to detect crack formation, e.g., in reinforced concrete constructions: the localized strain in the CLCE where a crack appears leads to a strong color change that allows immediate detection of the crack, whereas the crack in the uncoated surface remains invisible until it has grown to much greater width. The colorimetric strain monitoring is also possible with CLCE fibers, where the 1D form factor lends itself to applications in, e.g., fashion, medicine and sports. We end by discussing the key remaining challenges, in particular related to scale-up of production.

Increasing demand for high-purity fine chemicals and a drive for process intensification of large-scale separations have driven significant work on the development of highly engineered porous materials with promise for sorption-based separations. While sorptive separations in porous materials offer energy-efficient alternatives to longstanding thermal-based methods, the particulate nature of many of these sorbents has sometimes limited their large-scale deployment in high-throughput applications such as gas separations, for which the necessary high feed flow rates and gas velocities accrue prohibitive operational costs. These processability limitations have been historically addressed through powder shaping methods aimed at the fabrication of structured sorbent contactors based on pellets, beads or monoliths, commonly obtained as extrudates. These structures overcome limitations such as elevated pressure drops commonly recorded across powder adsorption beds but often accrue thermal limitations arising from elevated particle density and aggregation, which ultimately cap their maximum separation performance. Furthermore, the harsh mechanical strain to which powder particles are subjected during contactor fabrication, in the form of extrusion/compression forces, can result in partial pore occlusion and framework degradation, further limiting their performance. Here, we present the development of porous fiber sorbents as an alternative sorbent contactor design capable of addressing sorbent processability limitations while enabling an array of performance-maximizing heat integration capabilities. This new sorbent form factor leverages pre-existing know-how from hollow fiber spinning to produce fiber-shaped sorbent contactors through the phase inversion of known polymers in a process known as dry-jet/wet quenching. The process of phase inversion allows microporous sorbent particles to be latched onto a macroporous polymer matrix under mild processing conditions, thus making it compatible with soft porous materials prone to amorphization under traditional pelletization conditions. Sorbent fibers can be created with different geometries through control of the spinning apparatus and process, offering the possibility to produce monolithic and hollow fibers alike, the latter of which can be integrated with thermalization fluid flows. In this Account, we summarize our progress in the field of fiber sorbents from both design and application standpoints. We further guide the reader through the evolution of this field from the early inceptive work on zeolite hollow fibers to recent developments on MOF fibers. We highlight the versatile nature of fiber sorbents, both from the composition, fabrication and structure points of view, and further demonstrate how fiber sorbents offer alternative paths in tackling new and challenging chemical separation challenges like direct air capture (DAC), with a final perspective on the future of the field.

The aim of this study was to develop machine learning (ML) models to explore the relationship between chronic pulmonary embolism (PE) burden and severe pulmonary hypertension (PH) in surgical chronic thromboembolic pulmonary hypertension (CTEPH). CTEPH patients with a preoperative CT pulmonary angiogram and pulmonary endarterectomy between 01/2017 and 06/2022 were included. A mean pulmonary artery pressure of > 50 mmHg was classified as severe. CTs were scored by a blinded radiologist who recorded chronic pulmonary embolism extent in detail, and measured the right ventricle (RV), left ventricle (LV), main pulmonary artery (PA) and ascending aorta (Ao) diameters. XGBoost models were developed to identify CTEPH feature importance and compared to a logistic regression model. There were 184 patients included; 54.9% were female, and 21.7% had severe PH. The average age was 57 ± 15 years. PE burden alone was not helpful in identifying severe PH. The RV/LV ratio logistic regression model performed well (AUC 0.76) with a cutoff of 1.4. A baseline ML model (Model 1) including only the RV, LV, Pa and Ao measures and their ratios yielded an average AUC of 0.66 ± 0.10. The addition of demographics and statistics summarizing the CT findings raised the AUC to 0.75 ± 0.08 (F1 score 0.41). While measures of PE burden had little bearing on PH severity independently, the RV/LV ratio, extent of disease in various segments, total webs observed, and patient demographics improved performance of machine learning models in identifying severe PH. Question Can machine learning methods applied to CT-based cardiac measurements and detailed maps of chronic thromboembolism type and distribution predict pulmonary hypertension (PH) severity? Findings The right-to-left ventricle (RV/LV) ratio was predictive of PH severity with an optimal cutoff of 1.4, and detailed accounts of chronic thromboembolic burden improved model performance. Clinical relevance The identification of a CT-based RV/LV ratio cutoff of 1.4 gives radiologists, clinicians, and patients a point of reference for chronic thromboembolic PH severity. Detailed chronic thromboembolic burden data are useful but cannot be used alone to predict PH severity.

Power semiconductors and chips are essential in modern electronics, driving applications from personal devices and data centers to energy technologies, vehicles, and Internet infrastructure. However, efficient heat dissipation remains a critical challenge, directly affecting their performance, reliability, and lifespan. High-power electronics based on wide- and ultrawide-bandgap semiconductors can exhibit power densities exceeding 10 kW/cm2, hundreds of times higher than digital electronics, posing significant thermal management challenges. Addressing this issue requires advanced materials and interface engineering, alongside a comprehensive understanding of materials physics, chemistry, transport dynamics, and various electronic, thermal, and mechanical properties. Despite progress in thermal management solutions, the complex interplay of phonons, electrons, and their interactions with material lattices, defects, boundaries, and interfaces presents persistent challenges. This Account highlights key advancements in thermal management for power semiconductors and chips, with a focus on our group's recent contributions. Our approach addresses several critical issues: (1) developing materials with ultrahigh thermal conductivity for enhanced heat dissipation, (2) reducing thermal boundary resistance between power semiconductors and emerging 2D materials, (3) improving thermal and mechanical contacts between chips and heat sinks, (4) innovating dynamic thermal management solutions, and (5) exploring novel principles of thermal transport and design for future technologies. Our research philosophy integrates multiscale theoretical predictions with experimental validation to achieve a paradigm shift in thermal management. By leveraging first-principles calculations, the recent studies redefined traditional criteria for high-thermal-conductivity materials. Guided by these insights, we developed boron arsenide and boron phosphide, which exhibit record-high thermal conductivities of up to 1300 W/mK. Through phonon band structure engineering, we reduced TBR in GaN/BAs interfaces by over 8-fold compared to GaN/diamond interfaces. The combination of low TBR and high thermal conductivity significantly reduced hotspot temperatures, setting new benchmarks in thermal design for power electronics. We further explored the anisotropic TBR properties of two-dimensional materials and Moiré patterns in twisted graphene, expanding the thermal design landscape. To address challenges at device-heat sink interfaces, we developed self-assembled boron arsenide composites with a thermal conductivity of 21 W/mK and exceptional mechanical compliance (∼100 kPa). These composites provide promising solutions for thermal management in flexible electronics and soft robotics. In dynamic thermal management, we pioneered the concept of solid-state thermal transistors, enabling electrically controlled heat flow with unparalleled tunability, speed, reliability, and compatibility with integrated circuit fabrication. These innovations not only enhance thermal performance but also enable the exploration of novel transport physics, improving our fundamental understanding of thermal energy transport under extreme conditions. Looking forward, we reflect on remaining challenges and identify opportunities for further advancements. These include scaling up the production of high-performance materials, integrating thermal solutions with existing manufacturing processes, and uncovering new physics to inspire next-generation power electronics technologies. By addressing these challenges, we aim to inspire future codesign strategies that enable the development of more efficient, reliable, sustainable, and high-performance electronic systems.

The purpose of this study was to gain deeper understanding of the experiences of occupational therapists and physiotherapists, working with those with atypical Parkinson's conditions, within the UK. A literature review identified that research into these roles is limited and unrepresentative. A qualitative approach, informed by hermeneutic phenomenology was used to guide the study design. Semi-structured, online interviews, focussed on therapists' experiences of success and challenge, were completed with six physiotherapists, and three occupational therapists, experienced in working within this area of practice. The interviews were recorded and transcribed verbatim and were analysed using Braun and Clarke's reflexive thematic analysis. Four themes were generated and discussed: (1) maintaining hope without giving false hope, (2) maintaining quality of life despite deterioration, (3) maintaining empowerment and choice despite loss of control, (4) maintaining effective working despite variable resources. Participants' accounts of success and challenge reveal a complex landscape of tensions that must be negotiated and balanced within their practice. Insight is gained into some of the mechanisms involved in maintaining a patient's hope, their ability to participate and their sense of identity, despite the devastating losses associated with these conditions. Exploration of participant’s experiences of success and challenge as occupational therapists and physiotherapists working with those with atypical Parkinson’s conditions, reveals some of the mechanisms which underlie their complex practice.Individualised, client centred care, which focuses on quality of life and maintaining patients’ engagement with valued activities, and connection with others can maintain hope despite the progressive nature of these conditions.Building a therapeutic relationship over time, in which patient’s choices and preferences are respected, can facilitate acceptance, and empower patients to make timely and informed decisions at all stages of their condition.Communication and joint working with the wider multidisciplinary team is key to successful and coordinated patient care.Specialist knowledge of these conditions enhance practice and allows for the balance between risk and quality of life to be maintained.

Since its inception in 1974, the Essential Programme on Immunization (EPI) has achieved remarkable success, averting the deaths of an estimated 154 million children worldwide through routine childhood vaccination. However, more recent decades have seen persistent coverage inequities and stagnating progress, which have been further amplified by the COVID-19 pandemic. In 2019, WHO set ambitious goals for improving vaccine coverage globally through the Immunization Agenda 2030 (IA2030). Now halfway through the decade, understanding past and recent coverage trends can help inform and reorient strategies for approaching these aims in the next 5 years. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2023, this study provides updated global, regional, and national estimates of routine childhood vaccine coverage from 1980 to 2023 for 204 countries and territories for 11 vaccine-dose combinations recommended by WHO for all children globally. Employing advanced modelling techniques, this analysis accounts for data biases and heterogeneity and integrates new methodologies to model vaccine scale-up and COVID-19 pandemic-related disruptions. To contextualise historic coverage trends and gains still needed to achieve the IA2030 coverage targets, we supplement these results with several secondary analyses: (1) we assess the effect of the COVID-19 pandemic on vaccine coverage; (2) we forecast coverage of select life-course vaccines up to 2030; and (3) we analyse progress needed to reduce the number of zero-dose children by half between 2023 and 2030. Overall, global coverage for the original EPI vaccines against diphtheria, tetanus, and pertussis (first dose [DTP1] and third dose [DTP3]), measles (MCV1), polio (Pol3), and tuberculosis (BCG) nearly doubled from 1980 to 2023. However, this long-term trend masks recent challenges. Coverage gains slowed between 2010 and 2019 in many countries and territories, including declines in 21 of 36 high-income countries and territories for at least one of these vaccine doses (excluding BCG, which has been removed from routine immunisation schedules in some countries and territories). The COVID-19 pandemic exacerbated these challenges, with global rates for these vaccines declining sharply since 2020, and still not returning to pre-COVID-19 pandemic levels as of 2023. Coverage for newer vaccines developed and introduced in more recent years, such as immunisations against pneumococcal disease (PCV3) and rotavirus (complete series; RotaC) and a second dose of the measles vaccine (MCV2), saw continued increases globally during the COVID-19 pandemic due to ongoing introductions and scale-ups, but at slower rates than expected in the absence of the pandemic. Forecasts to 2030 for DTP3, PCV3, and MCV2 suggest that only DTP3 would reach the IA2030 target of 90% global coverage, and only under an optimistic scenario. The number of zero-dose children, proxied as children younger than 1 year who do not receive DTP1, decreased by 74·9% (95% uncertainty interval 72·1-77·3) globally between 1980 and 2019, with most of those declines reached during the 1980s and the 2000s. After 2019, counts of zero-dose children rose to a COVID 19-era peak of 18·6 million (17·6-20·0) in 2021. Most zero-dose children remain concentrated in conflict-affected regions and those with various constraints on resources available to put towards vaccination services, particularly sub-Saharan Africa. As of 2023, more than 50% of the 15·7 million (14·6-17·0) global zero-dose children resided in just eight countries (Nigeria, India, Democratic Republic of the Congo, Ethiopia, Somalia, Sudan, Indonesia, and Brazil), emphasising persistent inequities. Our estimates of current vaccine coverage and forecasts to 2030 suggest that achieving IA2030 targets, such as halving zero-dose children compared with 2019 levels and reaching 90% global coverage for life-course vaccines DTP3, PCV3, and MCV2, will require accelerated progress. Substantial increases in coverage are necessary in many countries and territories, with those in sub-Saharan Africa and south Asia facing the greatest challenges. Recent declines will need to be reversed to restore previous coverage levels in Latin America and the Caribbean, especially for DTP1, DTP3, and Pol3. These findings underscore the crucial need for targeted, equitable immunisation strategies. Strengthening primary health-care systems, addressing vaccine misinformation and hesitancy, and adapting to local contexts are essential to advancing coverage. COVID-19 pandemic recovery efforts, such as WHO's Big Catch-Up, as well as efforts to bolster routine services must prioritise reaching marginalised populations and target subnational geographies to regain lost ground and achieve global immunisation goals. The Bill & Melinda Gates Foundation and Gavi, the Vaccine Alliance.

Nanocellulose in anionic and cationic form can be extracted from biomass using a top-down approach, and the surface chemistry can be tuned to have selective interactions toward water pollutants under aqueous conditions. The versatility of the surface functionalization potential of nanocellulose and its processability into membranes, hydrogel beads, 3D printed filters, electrospun webs, etc., have resulted in promising performance in water treatment. Nanocellulose interactions with pollutants and adsorption can involve multiple mechanisms such as electrostatic interactions, complexation, hydrophobic interactions, hydrogen bonding, precipitation, or nucleation and growth depending on time scales. This is, however, not fully understood, predominantly due to challenges related to characterization under aqueous conditions. In this context, we explored liquid phase atomic force microscopy (AFM), colloidal probe force spectroscopy, and in situ synchrotron scattering methods as advanced characterization tools to extract reliable information on interactions of nanocellulose with metal ions, dyes, pesticides, pharmaceuticals, humic acid, nitrates, PFAS, microplastics, proteins, bacteria, etc., under aqueous conditions. AFM provides information on structure and nanomechanics data on length scales of 1 nm to microns as well as molecular level interactions, whereas scattering methods can detect structures in the range of 1 Å-100 nm. This Account summarizes the research using these techniques under in operando conditions to understand reactions and interactions under aqueous conditions for nanocellulose based systems in the context of water treatment. The use of these techniques to understand the adsorption process, membrane structure, and interactions in wet environments, as well as the synthesis of water treatment materials in aqueous media, is included in this Account. In addition to our work, other relevant reports in the literature are also summarized to demonstrate the possibilities and challenges in this approach. Literature review showed only 6 studies on using AFM/force spectroscopy (4 from our group) and only 3 studies (from our group) on scattering methods on nanocellulose in water treatment, which indicates the challenges and limitations of this approach and also the need for expanding this field. Our works in this field have demonstrated that the advanced characterization methodologies discussed here, viz., atomic force microscopy and X-ray scattering, have significant potential to provide information on nano, molecular, and atomic scales. It is worth mentioning that in order to compensate for the interference with water, which can reduce the accuracy of the data, careful tailoring of experimental design and method development is needed. We also infer that these methodologies and tools, developed to evaluate how the nanocellulose surface interacts/reacts with other hybrid components, biomolecules, and pollutants, can be extended to understand materials and devices (e.g., biomedical implants, conductive material, catalysts, sensors, etc.) driven by surface charge under in situ and in operando conditions.

Lower respiratory infections (LRIs) remain the world's leading infectious cause of death. This analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides global, regional, and national estimates of LRI incidence, mortality, and disability-adjusted life-years (DALYs), with attribution to 26 pathogens, including 11 newly modelled pathogens, across 204 countries and territories from 1990 to 2023. With new data and revised modelling techniques, these estimates serve as an update and expansion to GBD 2021. Through these estimates, we also aimed to assess progress towards the 2025 Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) target for pneumonia mortality in children younger than 5 years. Mortality from LRIs, defined as physician-diagnosed pneumonia or bronchiolitis, was estimated using the Cause of Death Ensemble model with data from vital registration, verbal autopsy, surveillance, and minimally invasive tissue sampling. The Bayesian meta-regression tool DisMod-MR 2.1 was used to model overall morbidity due to LRIs. DALYs were calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs) for all locations, years, age groups, and sexes. We modelled pathogen-specific case-fatality ratios (CFRs) for each age group and location using splined binomial regression to create internally consistent estimates of incidence and mortality proportions attributable to viral, fungal, parasitic, and bacterial pathogens. Progress was assessed towards the GAPPD target of less than three deaths from pneumonia per 1000 livebirths, which is roughly equivalent to a mortality rate of less than 60 deaths per 100 000 children younger than 5 years. In 2023, LRIs were responsible for 2·50 million (95% uncertainty interval [UI] 2·24-2·81) deaths and 98·7 million (87·7-112) DALYs, with children younger than 5 years and adults aged 70 years and older carrying the highest burden. LRI mortality in children younger than 5 years fell by 33·4% (10·4-47·4) since 2010, with a global mortality rate of 94·8 (75·6-116·4) per 100 000 person-years in 2023. Among adults aged 70 years and older, the burden remained substantial with only marginal declines since 2010. A mortality rate of less than 60 deaths per 100 000 for children younger than 5 years was met by 129 of the 204 modelled countries in 2023. At a super-regional level, sub-Saharan Africa had an aggregate mortality rate in children younger than 5 years (hereafter referred to as under-5 mortality rate) furthest from the GAPPD target. Streptococcus pneumoniae continued to account for the largest number of LRI deaths globally (634 000 [95% UI 565 000-721 000] deaths or 25·3% [24·5-26·1] of all LRI deaths), followed by Staphylococcus aureus (271 000 [243 000-298 000] deaths or 10·9% [10·3-11·3]), and Klebsiella pneumoniae (228 000 [204 000-261 000] deaths or 9·1% [8·8-9·5]). Among pathogens newly modelled in this study, non-tuberculous mycobacteria (responsible for 177 000 [95% UI 155 000-201 000] deaths) and Aspergillus spp (responsible for 67 800 [59 900-75 900] deaths) emerged as important contributors. Altogether, the 11 newly modelled pathogens accounted for approximately 22% of LRI deaths. This comprehensive analysis underscores both the gains achieved through vaccination and the challenges that remain in controlling the LRI burden globally. Furthermore, it demonstrates persistent disparities in disease burden, with the highest mortality rates concentrated in countries in sub-Saharan Africa. Globally, as well as in these high-burden locations, the under-5 LRI mortality rate remains well above the GAPPD target. Progress towards this target requires equitable access to vaccines and preventive therapies-including newer interventions such as respiratory syncytial virus monoclonal antibodies-and health systems capable of early diagnosis and treatment. Expanding surveillance of emerging pathogens, strengthening adult immunisation programmes, and combating vaccine hesitancy are also crucial. As the global population ages, the dual challenge of sustaining gains in child survival while addressing the rising vulnerability in older adults will shape future pneumonia control strategies. Gates Foundation.