StreamSAXS: a Python-based workflow platform for processing streaming SAXS/WAXS data.

StreamSAXS is a Python-based small- and wide-angle X-ray scattering (SAXS/WAXS) data analysis workflow platform with graphical user interface (GUI). It aims to provide an interactive and user-friendly tool for analysis of both batch data files and real-time data streams. Users can easily create customizable workflows through the GUI to meet their specific needs. One characteristic of StreamSAXS is its plug-in framework, which enables developers to extend the built-in workflow tasks. Another feature is the support for both already acquired and real-time data sources, allowing StreamSAXS to function as an offline analysis platform or be integrated into large-scale acquisition systems for end-to-end data management. This paper presents the core design of StreamSAXS and provides user cases demonstrating its utilization for SAXS/WAXS data analysis in offline and online scenarios.

Programming of Supercrystals Using Replicable DNA-Functionalized Colloids.

The development of self-replicating systems is of great importance in research on the origin of life. As the most iconic molecules, nucleic acids have provided prominent examples of the fabrication of self-replicating artificial nanostructures. However, it is still challenging to construct sophisticated synthetic systems that can create large-scale or three-dimensionally ordered nanomaterials using self-replicating nanostructures. By integrating a template system containing DNA-functionalized colloidal seeds with a simplified DNA strand-displacement circuit programmed subsystem to produce DNA-functionalized colloidal copies, we developed a facile enthalpy-mediated strategy to control the replication and catalytic assembly of DNA-functionalized colloids in a time-dependent manner. The replication efficiency and crystal quality of the resulting superlattice structures can be effectively increased by regulating the molar ratio of the template to the copy colloids. By constructing binary systems from two types of gold nanoparticles (or proteins), superlattice structures with different crystal symmetries can be obtained through the replication and catalytic assembly processes. This programmable enthalpy-mediated approach was easily leveraged to achieve the phase transformation and catalytic amplification of colloidal crystals starting from different initial template crystals. This work offers a potential way to construct self-replicating artificial systems that exhibit complicated phase behaviors and can produce large-scale superlattice nanomaterials.

Extraction of cellulose nanofibrils from pine sawdust by integrated chemical pretreatment.

Reducing energy consumption is major challenge in the industrialization of chemical pretreatments for the extraction of cellulose nanofibrils (CNF). In this study, an integrated chemical pretreatment with alkaline/acid-chlorite/TEMPO-oxidant was used for the nano-fibrillation of CNF from pine sawdust (WS). The alkaline and acid-chlorite pretreatments effectively eliminated the non-cellulosic components present in WS, resulting in the delamination of individual cell layers and swelling of the internal structures within the cellulose fiber bundles and cellulose microfibrils that form these layers. The spacing between CNF within the cellulose microfibrils increased from 3.7 nm to 5.5 nm. These loosely packed hierarchical structures facilitated the penetration of the reagent, which led to an increase in the specific surface area during the TEMPO-oxidant reaction and consequently accelerated the reaction rate. The WS was pretreated in a very dilute solution (1 % NaOH and 0.5 % NaClO2) under mild conditions (70 °C for 1 h), which resulted in a significant reduction of the TEMPO reaction time (from 3 h to 30 min) and a lower consumption of the reaction reagent (one fourth of the amount consumed compared to the direct oxidation of WS to achieve the same degree of cellulose nano-fibrillation).

A step towards 6D WAXD tensor tomography.

X-ray scattering/diffraction tensor tomography techniques are promising methods to acquire the 3D texture information of heterogeneous biological tissues at micrometre resolution. However, the methods suffer from a long overall acquisition time due to multi-dimensional scanning across real and reciprocal space. Here, a new approach is introduced to obtain 3D reciprocal information of each illuminated scanning volume using mathematic modeling, which is equivalent to a physical scanning procedure for collecting the full reciprocal information required for voxel reconstruction. The virtual reciprocal scanning scheme was validated by a simulated 6D wide-angle X-ray diffraction tomography experiment. The theoretical validation of the method represents an important technological advancement for 6D diffraction tensor tomography and a crucial step towards pervasive applications in the characterization of heterogeneous materials.