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Iron gall Inks corrosion causes paper degradation (browning, embrittlement) and treatments were developed to tackle this issue. They often include resizing with gelatin to reinforce the paper and its cellulosic fibers (of diameter approx. 10 µm). This work aimed at measuring the distribution of ink components at the scale of individual paper fibers so as to give a better understanding of the impact of gelatin (re-)sizing on iron gall ink corrosion. For this purpose, scanning transmission X-ray microscopy (STXM) was used at the Canadian light source synchrotron (CLS, Saskatoon). This technique combines nano-scale mapping (resolution of 30 nm) and near edge X-ray absorption fine structure (NEXAFS) analysis. Fe L-edge measurements enabled to map iron distribution and to locate iron(II) and iron(III) rich areas. N K-edge measurement made it possible to map gelatin distribution. C K-edge measurements allowed mapping and discrimination of cellulose, gallic acid, iron gall ink precipitate and gelatin. Three fibers were studied: an inked fiber with no size, a sized fiber that was afterwards inked and an inked fiber sprayed with gelatin. Analysis of gelatin and ink ingredients distribution indicated a lower amount of iron inside the treated cellulosic fiber, which may explain the beneficial effect of gelatin on iron gall ink corrosion.

Official discourses of Development are being redefined. If the key geopolitical contexts shaping the post‐war Development project were decolonisation and the Cold War, the defining world‐historical transformations shaping the emerging vision of Development are the expansion of state capitalism and the rise of China. The IMF, the World Bank, the OECD, the G20, other multilaterals, and bilateral partners are increasingly taking stock of the rise of state capitalism, and acting as ideational vectors of this emerging regime. However, this new “state capitalist normal” is also portrayed as carrying risks. There is anxiety regarding the direction the political form of global capital accumulation is heading: with the unchecked proliferation of state capitalism possibly blunting competition, politicising economic relations, and intensifying geoeconomic tensions. This anxiety underwrites the current re‐articulation of Development, one which embraces the state as promoter, supervisor, and owner of capital; even as it critiques China’s use of similar instruments.

Funder: CSC Cambridge Scholarship, In this study, we evaluate the suitability of using DC-biased aluminium resonators as low-frequency kinetic inductance detectors capable of operating in the frequency range of 50–120 GHz. Our analysis routine for supercurrent-biased resonators is based on the Usadel equations and gives outputs including density of states, complex conductivities, transmission line properties, and quasiparticle lifetimes. Results from our analysis confirm previous experimental observations on resonant frequency tuneability and retention of high quality factor. Crucially, our analysis suggests that DC-biased resonators demonstrate significantly suppressed superconducting density of states gap. Consequently these resonators have lower frequency detection threshold and are suitable materials for low-frequency kinetic inductance detectors.

We investigated the use of dielectric layers produced by atomic layer deposition (ALD) as an approach to strain mitigation in composite silicon/superconductor devices operating at cryogenic temperatures. We show that the addition of an ALD layer acts to reduce the strain of spins closest to silicon/superconductor interface where strain is highest. We show that appropriately biasing our devices at the hyperfine clock transition of bismuth donors in silicon, we can remove strain broadening and that the addition of ALD layers left T 2 (or temporal inhomogeneities) unchanged in these natural silicon devices.

Over the past decades, paper-based lateral flow immunoassays (LFIAs) have been extensively developed for rapid, facile, and low-cost detection of a wide array of target analytes in a point-of-care manner. Conventional home pregnancy tests are the most significant example of LFAs, which detect elevated concentrations of human chorionic gonadotrophin (hCG) in body fluids to identify early pregnancy. In this work, we have upgraded these platforms to a higher version by developing a customized microfluidic paper-based analytical device (μPAD), as the new generation of paper-based point-of-care platforms, for colorimetric immunosensing. This will offer a cost-efficient and environmentally friendly alternative platform for paper-based immunosensing, eliminating the need for nitrocellulose (NC) membrane as the substrate material. The performance of the developed platform is demonstrated by detection of hCG (as a model case) in urine samples and subsequently indicating positive or negative pregnancy. A dual-functional silane-based composite was used to treat filter paper in order to enhance the colorimetric signal intensity in the detection zones of μPADs. In addition, microfluidic pathways were designed in a manner to provide the desired regulated fluid flow, generating sufficient incubation time (delays) at the designated detection zones, and consequently enhancing the obtained signal intensity. The presented approaches allow to overcome the existing limitations of μPADs in immunosensing and will broaden their applicability to a wider range of assays. Although, the application of the developed hCG μPAD assay is mainly in qualitative (i.e., positive or negative) detection of pregnancy, the semi-quantitative measurement of hCG was also investigated, indicating the viability of this assay for sensitive detection of the target hCG analyte within the related physiological range (i.e., 10–500 ng/mL) with a LOD value down to 10 ng/mL.

Calculating polarizabilities of large clusters with first-principles techniques is challenging because of the unfavorable scaling of computational cost with cluster size. To address this challenge, we demonstrate that polarizabilities of large hydrogenated silicon clusters containing thousands of atoms can be efficiently calculated with machine learning methods. Specifically, we construct machine learning models based on the smooth overlap of atomic positions (SOAP) descriptor and train the models using a database of calculated random-phase approximation polarizabilities for clusters containing up to 110 silicon atoms. We first demonstrate the ability of the machine learning models to fit the data and then assess their ability to predict cluster polarizabilities using k-fold cross validation. Finally, we study the machine learning predictions for clusters that are too large for explicit first-principles calculations and find that they accurately describe the dependence of the polarizabilities on the ratio of hydrogen to silicon atoms and also predict a bulk limit that is in good agreement with previous studies.

Cellulose is a naturally occurring organic polymer extracted mainly from lignocellulosic biomass of terrestrial origin. However, the increasing production of seaweeds for growing global market demands has developed the opportunity to use it as an additional cellulose source. This review aims to prepare comprehensive information to understand seaweed cellulose and its possible applications better. This is the first review that summarizes and discusses the cellulose from all three types (green, red, and brown) of seaweeds in various aspects such as contents, extraction strategies, and cellulose-based products. The seaweed cellulose applications and future perspectives are also discussed. Several seaweed species were found to have significant cellulose content (9-34% dry weight). The review highlights that the properties of seaweed cellulose-based products were comparable to products prepared from plant-based cellulose. Overall, this work demonstrates that cellulose could be economically extracted from phycocolloids industrial waste and selected cellulose-rich seaweed species for various commercial applications.

In this work, ZnO nanorods (ZnO NRs) with different sizes were hydrothermally grown on the surface of Whatman filter paper for the fabrication of a microfluidic paper-based device (μPAD) for the simultaneous detection of glucose and uric acid. As dual enzymatic reaction was employed for the colorimetric detection in this μPAD, the presence of ZnO NRs promoted the enzyme immobilization thus significantly enhancing the colorimetric signal. The coffee ring effect was effectively conquered by the uniform distribution of ZnO NR as well as a specialized double-layered μPAD design. Meanwhile, two color indicators with distinct colors were used to provide complementary results to better quantify the concentration of the analytes by naked eye. As a result, two linear calibration curves were obtained for the detection of glucose (0.01–10 mmol L−1) and uric acid (0.01–5 mmol L−1), along with a LOD of 3 μmol L−1 for glucose and 4 μmol L−1 for uric acid, respectively. The practical usefulness of the proposed μPAD was further validated by the simultaneous analysis of glucose and uric acid in serum samples and urine samples.