Abstract MXene has emerged as an amazing family of two dimensional (2D) layered materials and drawn great attention from researchers of diverse scientific fields. MXenes are the recent advancements of materials chemistry which include early transition metal carbides, nitrides and carbonitrides produced by exfoliation of selective MAX phases. MAX phase corresponds to the general formula Mn+1AXn (n = 1, 2, 3) where M represents early d-block transition metals, A stands for main group sp elements (specifically groups 13 and 14) and X is either C or N atoms. MXenes have left a prodigious impact on scientific communities with new technological advancements for a plethora of potential applications in the field of catalysis, clean energy, electronics, fuel cells, supercapacitors etc. With high metallic conductivity, hydrophilicity, low diffusion barrier, high ion transport properties, biocompatibility, large surface area and ease of functionalization, the MXenes act as fascinating interface for designing next generation detection systems exploiting their utilization in analytical chemistry. Recent progress in the field of MXenes emphasizing their significant role in analytical sensing has been well discussed in this review. Future perspectives with a motivated research in the field of MXenes based sensors have been focused at the end. The underlying goal of this review is to acquaint the readers with the sensing applications of MXenes and to document the latest advancements made in this area till date.
This review summarizes recent advances in the area of tribology based on the outcome of a Lorentz Center workshop surveying various physical, chemical and mechanical phenomena across scales. Among the main themes discussed were those of rough surface representations, the breakdown of continuum theories at the nano- and microscales, as well as multiscale and multiphysics aspects for analytical and computational models relevant to applications spanning a variety of sectors, from automotive to biotribology and nanotechnology. Significant effort is still required to account for complementary nonlinear effects of plasticity, adhesion, friction, wear, lubrication and surface chemistry in tribological models. For each topic, we propose some research directions.
Oliver T. Unke, Stefan Chmiela, M. Gastegger
et al.
Machine-learned force fields combine the accuracy of ab initio methods with the efficiency of conventional force fields. However, current machine-learned force fields typically ignore electronic degrees of freedom, such as the total charge or spin state, and assume chemical locality, which is problematic when molecules have inconsistent electronic states, or when nonlocal effects play a significant role. This work introduces SpookyNet, a deep neural network for constructing machine-learned force fields with explicit treatment of electronic degrees of freedom and nonlocality, modeled via self-attention in a transformer architecture. Chemically meaningful inductive biases and analytical corrections built into the network architecture allow it to properly model physical limits. SpookyNet improves upon the current state-of-the-art (or achieves similar performance) on popular quantum chemistry data sets. Notably, it is able to generalize across chemical and conformational space and can leverage the learned chemical insights, e.g. by predicting unknown spin states, thus helping to close a further important remaining gap for today’s machine learning models in quantum chemistry. Current machine-learned force fields typically ignore electronic degrees of freedom. SpookyNet is a deep neural network that explicitly treats electronic degrees of freedom, closing an important remaining gap for models in quantum chemistry.
Eftychia G. Karageorgou, Nikoleta Andriana F. Ntereka, Victoria F. Samanidou
ISO 22002-100:2025 introduces stringent and more technically explicit prerequisite programme (PRP) requirements for allergen management, food fraud mitigation, and the control of chemical and packaging-related contaminants across the food, feed, and packaging supply chain. This review examines how advanced chromatographic methods provide the analytical basis required to meet these requirements and to support alignment with GFSI-recognized certification schemes. Recent applications of liquid and gas chromatography coupled with mass spectrometry for allergen quantification, authenticity assessment, and the determination of packaging migrants, auxiliary chemical residues, lubricants, and indoor pest-control pesticides are presented to demonstrate their relevance as verification tools. Across these PRP-related controls, chromatographic methods enable trace-level detection, structural specificity, and reproducible measurement performance, thereby shifting PRP compliance from a documentation-based activity to a process verified through measurable analytical evidence. The review highlights significant progress in method development and simultaneous multi-target analytical approaches while also identifying remaining challenges related to matrix-appropriate validation, harmonization, and analytical coverage for chemical contamination, which is now formally defined as a measurable PRP requirement under ISO 22002-100:2025. Overall, the findings demonstrate that chromatographic analysis has become essential to demonstrating PRP effectiveness under ISO 22002-100:2025, supporting the broader shift toward evidence-based, scientifically robust food safety assurance.
Background:
Early childhood caries (ECC) remains a significant public health concern affecting young children worldwide. Community-based fluoride varnish programs have been widely implemented as a preventive strategy. However, variations in application frequency and program delivery models necessitate an evaluation of their comparative effectiveness in reducing ECC prevalence.
Materials and Methods:
A total of 450 children aged 3–5 years were enrolled and divided into three groups based on the fluoride varnish application frequency: Group A (once every six months), Group B (once every three months), and Group C (once every two months). The study was conducted over one year in community health centers and preschools. Caries prevalence was assessed at baseline and after 12 months using the decayed, missing, and filled teeth (dmft) index. Statistical analysis was performed using paired t-tests and ANOVA to compare mean dmft scores among the groups.
Results:
At baseline, the mean dmft scores were 4.2 ± 1.3 for Group A, 4.0 ± 1.2 for Group B, and 4.1 ± 1.1 for Group C, with no significant differences (P > 0.05). After one year, Group A showed a mean reduction in dmft score to 3.5 ± 1.1, Group B to 2.8 ± 0.9, and Group C to 2.1 ± 0.8, with Group C demonstrating the most significant reduction (P < 0.05). Regular fluoride varnish applications every two months showed the greatest effectiveness in reducing caries incidence.
Conclusion:
Community-based fluoride varnish programs effectively reduce ECC prevalence, with more frequent applications yielding better outcomes. Implementing fluoride varnish every two months may be the most effective strategy for caries prevention in preschool children. These findings highlight the importance of structured fluoride application protocols in community dental health programs.