AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy.

Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

Transport coefficient approach for characterizing nonequilibrium dynamics in soft matter.

Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details. We introduce an approach for extracting the transport coefficient, denoted as [Formula: see text], from the XPCS studies. This coefficient is a fundamental parameter in nonequilibrium statistical mechanics and is crucial for characterizing transport processes within a system. Our method unifies the Green-Kubo formulas associated with various transport coefficients, including gradient flows, particle-particle interactions, friction matrices, and continuous noise. We achieve this by integrating the collective influence of random and systematic forces acting on the particles within the framework of a Markov chain. We initially validated this method using molecular dynamics simulations of a system subjected to changes in temperatures over time. Subsequently, we conducted further verification using experimental systems reported in the literature and known for their complex nonequilibrium characteristics. The results, including the derived [Formula: see text] and other relevant physical parameters, align with the previous observations and reveal detailed dynamical information in nonequilibrium states. This approach represents an advancement in XPCS analysis, addressing the growing demand to extract intricate nonequilibrium dynamics. Further, the methods presented are agnostic to the nature of the material system and can be potentially expanded to hard condensed matter systems.

Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields.

Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.

Kinetics of Shear-Induced Structural Ordering in Dense Colloids.

The macroscopic rheological response of a colloidal solution is highly correlated with the local microscopic structure, as revealed by an in situ Rheo-SAXS experiment with a high temporal resolution. Oscillatory shear can induce a strain-controlled ordering-to-disorder transition, resulting in a shear-thickening process that is different from the normal shear-thickening behavior that is driven by hydrodynamics and particle friction. We reveal that there is a complex time-dependent kinetics toward structural ordering under different applied strains. When the strain amplitude reaches a critical value that starts to induce disordering in the system, the pathway toward the dynamic equilibrium can also become highly non-monotonic. Within the same oscillatory cycle, there is a strong correlation of ordering with different phases of the oscillation, with the system oscillating between two dynamic metastable states.

Exploring nanofibrous networks with x-ray photon correlation spectroscopy through a digital twin.

We demonstrate a framework of interpreting data from x-ray photon correlation spectroscopy experiments with the aid of numerical simulations to describe nanoscale dynamics in soft matter. This is exemplified with the transport of passive tracer gold nanoparticles in networks of charge-stabilized cellulose nanofibers. The main structure of dynamic modes in reciprocal space could be replicated with a simulated system of confined Brownian motion, a digital twin, allowing for a direct measurement of important effective material properties describing the local environment of the tracers.

Characteristics in gut microbiome is associated with chemotherapy-induced pneumonia in pediatric acute lymphoblastic leukemia.

BACKGROUND: Children with acute lymphoblastic leukemia (ALL) undergoing chemotherapy experience a relatively high risk of infection. And the disturbance of gut microbiota is generally believed to impair intestinal barrier function and may induce bacterial infections and inflammation. The study aimed to investigate the alterations in the gut microbiota and assess its relationship with chemotherapy-induced pneumonia in pediatric ALL patients. METHODS: We conducted a case-control study with 14 cases affected by pneumonia and 44 unaffected subjects and characterized the physiological parameters and gut microbiota by microarray-based technique. RESULTS: There were significant differences in α- and ß-diversity in the affected group compared with the control group. At species level, the LEfSe analysis revealed that Enterococcus malodoratus, Ochrobactrum anthropi and Actinomyces cardiffensis were significantly abundant in the affected subjects. A receiver operating characteristic (ROC) curve yielded the area under the curve (AUC) of 0.773 for classification between the two groups. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in the bacterial secretion system were more enriched in the affected group than in the control group. CONCLUSIONS: Gut microbiota alteration was associated with chemotherapy-induced pneumonia in pediatric ALL patients, which provided a new perspective on the personalized clinical care of pediatric ALL.

Understanding ion-induced assembly of cellulose nanofibrillar gels through shear-free mixing and in situ scanning-SAXS.

During the past decade, cellulose nanofibrils (CNFs) have shown tremendous potential as a building block to fabricate new advanced materials that are both biocompatible and biodegradable. The excellent mechanical properties of the individual CNF can be transferred to macroscale fibers through careful control in hydrodynamic alignment and assembly processes. The optimization of such processes relies on the understanding of nanofibril dynamics during the process, which in turn requires in situ characterization. Here, we use a shear-free mixing experiment combined with scanning small-angle X-ray scattering (scanning-SAXS) to provide time-resolved nanoscale kinetics during the in situ assembly of dispersed cellulose nanofibrils (CNFs) upon mixing with a sodium chloride solution. The addition of monovalent ions led to the transition to a volume-spanning arrested (gel) state. The transition of CNFs is associated with segmental aggregation of the particles, leading to a connected network and reduced Brownian motion, whereby an aligned structure can be preserved. Furthermore, we find that the extensional flow seems to enhance the formation of these segmental aggregates, which in turn provides a comprehensible explanation for the superior material properties obtained in shear-free processes used for spinning filaments from CNFs. This observation clearly highlights the need for different assembly strategies depending on morphology and interactions of the dispersed nanoparticles, where this work can be used as a guide for improved nanomaterial processes.

Shear-free mixing to achieve accurate temporospatial nanoscale kinetics through scanning-SAXS: ion-induced phase transition of dispersed cellulose nanocrystals.

Time-resolved in situ characterization of well-defined mixing processes using small-angle X-ray scattering (SAXS) is usually challenging, especially if the process involves changes of material viscoelasticity. In specific, it can be difficult to create a continuous mixing experiment without shearing the material of interest; a desirable situation since shear flow both affects nanoscale structures and flow stability as well as resulting in unreliable time-resolved data. Here, we demonstrate a flow-focusing mixing device for in situ nanostructural characterization using scanning-SAXS. Given the interfacial tension and viscosity ratio between core and sheath fluids, the core material confined by sheath flows is completely detached from the walls and forms a zero-shear plug flow at the channel center, allowing for a trivial conversion of spatial coordinates to mixing times. With this technique, the time-resolved gel formation of dispersed cellulose nanocrystals (CNCs) was studied by mixing with a sodium chloride solution. It is observed how locally ordered regions, so called tactoids, are disrupted when the added monovalent ions affect the electrostatic interactions, which in turn leads to a loss of CNC alignment through enhanced rotary diffusion. The demonstrated flow-focusing scanning-SAXS technique can be used to unveil important kinetics during structural formation of nanocellulosic materials. However, the same technique is also applicable in many soft matter systems to provide new insights into the nanoscale dynamics during mixing.

Pediatric Acute Lymphoblastic Leukemia Patients Exhibit Distinctive Alterations in the Gut Microbiota.

Previous studies have shown that gut microbiota can affect human immune system in many ways. Our aim was to investigate quantitative differences in fecal bacterial compositions of childhood acute lymphoblastic leukemia (ALL) patients compared to those of healthy children, so as to identify individual bacterial species that are related to the etiology of ALL. We recruited 81 subjects, including 58 patients with ALL and 23 healthy controls. Fecal samples were collected and examined by 16S rRNA quantitative arrays and bioinformatics analysis. Both Principal Coordinates Analysis (PCoA) and Non-metric Multidimensional scaling (NMDS) demonstrated that the microbial composition of ALL patients deviated from the tight cluster of healthy controls. Multiple bacterial species exhibited significant changes (e.g., Roseburia faecis, Edwardsiella tarda, and Fusobacterium naviforme) in the ALL samples. Some of the differentially abundant taxa were correlated with the level of interleukin-10. The ALL cases could be efficiently distinguished from healthy controls by the random forest model based on differential species (area under ROC curve = 0.843). Taken together, the composition of gut microbiota differed from healthy controls to pediatric ALL patients. Our study identified a series of ALL-related species in the gut microbiota, providing a new direction for future studies aiming to understand the host-gut microbiota interplay in ALL pathogenesis.

Cross-Sections of Nanocellulose from Wood Analyzed by Quantized Polydispersity of Elementary Microfibrils.

Bio-based nanocellulose has been shown to possess impressive mechanical properties and simplicity for chemical modifications. The chemical properties are largely influenced by the surface area and functionality of the nanoscale materials. However, finding the typical cross-sections of nanocellulose, such as cellulose nanofibers (CNFs), has been a long-standing puzzle, where subtle changes in extraction methods seem to yield different shapes and dimensions. Here, we extracted CNFs from wood with two different oxidation methods and variations in degree of oxidation and high-pressure homogenization. The cross-sections of CNFs were characterized by small-angle X-ray scattering and wide-angle X-ray diffraction in dispersed and freeze-dried states, respectively, where the results were analyzed by assuming that the cross-sectional distribution was quantized with an 18-chain elementary microfibril, the building block of the cell wall. We find that the results agree well with a pseudosquare unit having a size of about 2.4 nm regardless of sample, while the aggregate level strongly depends on the extraction conditions. Furthermore, we find that aggregates have a preferred cohesion of phase boundaries parallel to the (110)-plane of the cellulose fibril, leading to a ribbon shape on average.

Cellulose nanofibrils and nanocrystals in confined flow: Single-particle dynamics to collective alignment revealed through scanning small-angle x-ray scattering and numerical simulations.

Nanostructured materials made through flow-assisted assembly of proteinaceous or polymeric nanosized fibrillar building blocks are promising contenders for a family of high-performance biocompatible materials in a wide variety of applications. Optimization of these processes relies on improving our knowledge of the physical mechanisms from nano- to macroscale and especially understanding the alignment of elongated nanoparticles in flows. Here, we study the full projected orientation distributions of cellulose nanocrystals (CNCs) and nanofibrils (CNFs) in confined flow using scanning microbeam SAXS. For CNCs, we further compare with a simulated system of dilute Brownian ellipsoids, which agrees well at dilute concentrations. However, increasing CNC concentration to a semidilute regime results in locally arranged domains called tactoids, which aid in aligning the CNC at low shear rates, but limit alignment at higher rates. Similarly, shear alignment of CNF at semidilute conditions is also limited owing to probable bundle or flock formation of the highly entangled nanofibrils. This work provides a quantitative comparison of full projected orientation distributions of elongated nanoparticles in confined flow and provides an important stepping stone towards predicting and controlling processes to create nanostructured materials on an industrial scale.

A study of TiO2 nanocrystal growth and environmental remediation capability of TiO2/CNC nanocomposites.

Nanocellulose, which can be derived from any cellulosic biomass, has emerged as an appealing nanoscale scaffold to develop inorganic-organic nanocomposites for a wide range of applications. In this study, titanium dioxide (TiO2) nanocrystals were synthesized in the cellulose nanocrystal (CNC) scaffold using a simple approach, i.e., hydrolysis of a titanium oxysulfate precursor in a CNC suspension at low temperature. The resulting TiO2 nanoparticles exhibited a narrow size range between 3 and 5 nm, uniformly distributed on and strongly adhered to the CNC surface. The structure of the resulting nanocomposite was evaluated by transmission electron microscopy (TEM) and X-ray diffraction (XRD) methods. The growth mechanism of TiO2 nanocrystals in the CNC scaffold was also investigated by solution small-angle X-ray scattering (SAXS), where the results suggested the mineralization process could be described by the Lifshitz-Slyozov-Wagner theory for Ostwald ripening. The demonstrated TiO2/CNC nanocomposite system exhibited excellent performance in dye degradation and antibacterial activity, suitable for a wide range of environmental remediation applications.

Comparison of different extraction methods for polysaccharides from Dendrobium officinale stem.

The purpose of this study was to screen the optimum extraction of polysaccharides (DOP) from Dendrobium officinale stem. Firstly, different methods, including hot water extraction (HWE), cold-pressing (CP), freeze-thawing cold-pressing (FTCP), ultrasonic-assisted hot water extraction (UHWE), microwave-assisted hot water extraction (MHWE) and enzyme-assisted hot water extraction (EHWE), were employed to extract DOP under their respective best parameters. Then, the extraction yield, structure and antioxidant activity of the polysaccharides from different extraction methods were compared under the same condition. The data implied that UHWE and FTCP possessed higher extraction yield than the other extraction methods. Besides, DOPCP and DOPFTCP had higher molecular weight than the other polysaccharide samples. More importantly, DOPFTCP had the highest antioxidant activity. Overall, DOPFTCP exhibit high extraction yield, well-preserved molecular chains and best antioxidant activity, all these indicated FTCP was the most suitable method to extract DOP.