In this study, a functional experimental model of dye-sensitized solar cells (DSSCs) based on natural anthocyanin dyes was developed, optimized, and evaluated under under simulated solar irradiation using a solar simulator. The photoanode architecture was optimized using a nanostructured TiO₂ film deposited on ST-FTO substrates, followed by controlled thermal treatment to improve adhesion, porosity, and electron transport. The influence of the number of TiO₂ layers on photovoltaic performance was investigated by comparing configurations with one, two, and three layers. In addition, a thin Nb₂O₅ interfacial layer was introduced to reduce electron recombination and improve charge transfer at the TiO₂/conductive substrate interface, while also acting as a light-scattering layer. Natural anthocyanin dyes extracted from various plant sources were used as photosensitizers. The assembled DSSC devices were tested using a solar simulator. The results demonstrated that the photovoltaic performance strongly depends on the photoanode architecture and the type of dye used. Increasing the number of TiO₂ layers enhanced the generated power due to improved dye adsorption and larger active surface area, while the introduction of the Nb₂O₅ layer significantly reduced recombination processes and improved charge transport.

The optimized DSSC configuration, consisting of three TiO₂ layers, an intermediate Nb₂O₅ layer, anthocyanin dye extracted from blackberries, an iodide/triiodide electrolyte, and a graphite counter electrode, demonstrated a stable and reproducible photovoltaic response. These results confirm the potential of natural anthocyanin dyes as sustainable sensitizers for environmentally friendly DSSC devices.

Magnesium batteries (Mg-battery) can offer higher volumetric energy density than lithium ion batteries. However, the challenge is to establish the stable electrochemical interface (i.e. electrode-electrolyte interface) that can facilitate Mg²⁺ ion diffusion while impeding electronic transport that can trigger electrolyte decomposition process. Such a designer interface can help us enhance the charge rate, lifetime, operating voltage, and safety of the Mg-battery. However, the main knowledge gap is a predictive understanding of electrochemical interphase formation, especially at Mg-metal anode. Currently, very few non-aqueous solvents were identified as compatible for Mg-battery application due to their ability to withstand both the Mg plating and stripping process. For example, 1-Methoxy-2-(2-methoxyethoxy)ethane (diglyme) being an ethereal solvent, is considered less volatile and reasonably stable against Mg reduction. In order to understand and interpret the reactions and subsequent interphase layer evolution from possible diglyme interaction with Mg-metal anode, in situ X-ray photo electron spectroscopy (XPS) measurements were performed at Pacific Northwest National Laboratory. In the current study, the vapor of diglyme solvent is exposed Mg-metal single crystal substrate and subsequently analyzed using high resolution X-ray photo electron spectroscopy. Detail reaction mechanisms and pathways based on core-level spectra will be discussed in this presentation.

In this study, ab initio density functional theory (DFT) calculations were conducted to comprehensively investigate the structural, mechanical, electronic, and optical properties of the double perovskite oxides Sr2PAlO6 and Sr2PGaO6. The structural analysis, supported by the Goldschmidt tolerance factor, confirms that both compounds adopt a stable perovskite structure. Furthermore, their calculated negative formation energies (−3.059 eV for Sr2PAlO6 and −3.367 eV for Sr2PGaO6) strongly indicate excellent thermodynamic stability, making them promising candidates for practical applications. Mechanical stability is verified through elastic constant calculations, which fully satisfy the Born and Huang mechanical stability criteria for cubic systems. The absence of any imaginary frequencies in the phonon dispersion spectra further confirms the dynamic stability of both structures. In terms of mechanical behavior, these materials demonstrate anisotropic and brittle characteristics, as evidenced by anisotropy factors deviating from unity and Poisson’s ratio values below 0.26. Electronic structure calculations reveal that both Sr2PAlO6 and Sr2PGaO6 exhibit semiconducting behavior with direct band gaps of 2.860 eV and 3.027 eV, respectively. Such values suggest they are suitable for use in optoelectronic devices operating in the visible to ultraviolet range. The optical properties, derived from the complex dielectric function, show strong and broad absorption features across the energy range of 0 to 12 eV, indicating their potential for efficient light-harvesting and energy conversion applications. In conclusion, the combined structural, mechanical, electronic, and optical analyses highlight that Sr2BPO6 (B = Al, Ga) double perovskites are promising multifunctional materials with significant potential for deployment in future optoelectronic and photovoltaic technologies.

Introduction. The pharmaceutical industry is transitioning from quality-by-test (QbT) to quality-by-design (QbD) and quality-by-digital-design (QbDD) paradigms, necessitating built-in quality assurance throughout the product lifecycle [1]. High-fidelity mathematical models are critical for reliable process design, optimisation, and control [2]. However, robust model establishment is challenged by scarce experimental data and inadequate assessment of data information content, hindering parameter estimation and undermining predictive capability [3]. Crystallisation processes exemplify this difficulty, as complex mechanisms (nucleation, growth, agglomeration, polymorphism) yield high-dimensional population balance models with extensive parameter sets, which demands substantial experimental resources yet often yields information-deficient data [4,5].

Methods. We developed ESTANPy, a Python-based web application integrating global sensitivity analysis with sequential orthogonalisation to quantify data information content, diagnose non-estimable parameters, and guide information-rich experimental design.

Results. Applied to a 16-parameter paracetamol batch cooling crystallisation model, ESTANPy identified 10 estimable parameters from preliminary data; estimability-guided model-based design of experiment (MBDoE) subsequently yielded an optimally designed experiment, increasing this to 12 [4]. Compared with traditional full factorial design requiring a minimum of 16 runs, the proposed approach achieves equivalent estimability with 3 runs (more than 80% reduction in experimental burden), whilst markedly curtailing material consumption, energy usage, and environmental impacts.

Conclusions. ESTANPy enables efficient, targeted model development by identifying information-deficient parameters and guiding information-rich experimental design. This capability directly supports QbDD implementation in pharmaceutical processes, delivering substantial reductions in experimental burden without compromising model reliability.

Introduction: The visualization of crystallographic structures is essential for understanding lattice geometry, symmetry, and atomic arrangements. However, traditional two-dimensional depictions often fail to provide the spatial insight required for mastering these concepts. To address this challenge, we developed an immersive and non-immersive Virtual Reality Learning Environment (VRLE) designed to facilitate intuitive exploration of foundational crystallographic principles, including the 14 Bravais lattices, crystallographic directions, planes, plane families, and interstitial sites.

Methods: The application was implemented both as immersive and non-immersive VRLE. The VRLE is structured as a virtual museum consisting of five interactive stations, each dedicated to a specific crystallographic topic. Users can manipulate 3D models through rotation, translation, zooming, selective hiding or highlighting of elements, and guided structural walkthroughs.

Results: The application successfully conveys geometric and structural features that are typically difficult to interpret from traditional representations. Users can examine unit cells and extended lattices, visualize the orientation of crystallographic directions and planes, and explore families of Miller-indexed elements. The dynamic rendering of tetrahedral and octahedral voids provides a clear illustration of their distribution and coordination within the lattice. Preliminary use in educational settings indicates enhanced spatial comprehension and improved conceptual retention.

Conclusions: The immersive and non-immersive VRLE offers an effective and accessible platform for understanding crystallographic principles. Its interactivity, modular structure, and real-time visualization capabilities make it a valuable tool for both guided instruction and independent learning.

Precipitation is an extensively used unit operation that involves mixing concentrated soluble reactants to form a sparingly soluble product. In wastewater treatment, it has recently been employed to recover nutrients from the liquid fraction obtained after dewatering digested sludge in wastewater treatment plants. Phosphorus (P) and nitrogen (N) are precipitated as struvite crystals upon the addition of a concentrated magnesium solution and subsequently used as slow-release fertilisers.

NETmix is a well-established static mixer and reactor. Owing to its distinct geometry, it surpasses most state-of-the-art technology for mixing and heat transfer and has been successfully used for the production of several crystalline compounds, including hydroxyapatite nanocrystals. This success motivated its application for the production of struvite crystals. This process requires mixing three liquid streams: the effluent stream (P and N source); a stream consisting of a concentrated magnesium (Mg) solution; and one consisting of a pH-controlling solution.

Two concentrated streams (Mg and pH-controlling solutions) are separately injected at low flow rate ratios relative to the main feed flow rate (effluent) directly into selected chambers along the NETmix reactor. This work assesses the effect of injection chamber position on the mixing performance of the reactor through the Computational Fluid Dynamics (CFD) simulation of passive tracer mixing experiments.

The topology of injection was found to have significant impact on mixing. Micromixing performance was quantified using the intensity of segregation. For all configurations studied, the intensity of segregation decreased along the NETmix network, indicating progressive homogenisation of the streams. The optimised injection scheme reduced the intensity of segregation by 99.9 %. It also ensured comparable mixing degrees for both tracers (Mg and pH-controlling solutions) at the outlets.

These results are highly relevant for crystalliser design, since mixing directly influences supersaturation, chemical reaction, nucleation and crystal growth during precipitation processes.

Photonic crystal fibers (PCFs) have attracted considerable interest due to their unique microstructured geometry and their ability to manipulate optical properties through structural design. In this work, a novel photonic crystal fiber configuration is proposed and investigated for pressure sensing applications. The structure is based on a silica background with a periodic arrangement of air holes forming a photonic crystal cladding. By engineering the geometrical parameters of the microstructured lattice and selectively infiltrating water into the air holes, the optical behavior of the fiber can be significantly modified.

Numerical simulations were carried out to analyze the influence of pressure variations on the chromatic dispersion characteristics of the proposed structure. The study demonstrates that the infiltration of water into the microstructured regions strongly affects the dispersion profile and shifts the zero-dispersion wavelength of the fiber. This behavior highlights the strong interaction between the guided optical field and the infiltrated medium, which can be exploited for sensing purposes.

Furthermore, the pressure sensitivity of the proposed sensor was evaluated by analyzing the variation in chromatic dispersion at different operating wavelengths. The results indicate that the sensor exhibits enhanced sensitivity at longer wavelengths, demonstrating the potential of the proposed design for high-precision pressure detection.

Compared with previously reported photonic crystal fiber sensors, the engineered structure shows improved sensing performance due to the optimized microstructured design and the interaction between the optical field and the infiltrated liquid. These findings demonstrate that crystal-engineered photonic crystal fibers can provide an effective platform for the development of highly sensitive optical pressure sensors for various scientific and industrial applications.

The presence of impurities during the crystallisation of active pharmaceutical ingredients is a major process engineering challenge because they can affect product purity, safety, efficacy, and consistency.^1,2 In mefenamic acid (MFA) manufacturing, impurities inherited from reaction steps can influence crystal quality attributes.³ Current MFA synthesis relies on Buchwald coupling, whichgenerates benzoic acid through dehalogenation, and relies on excess toxic 2,3-dimethylaniline, both known impurities to affect MFA crystal morphology.

This study leverages state-of-the-art computer-aided retrosynthesis (CAR),^4,5 to develop a greener-by-design and safer multistep synthesis for MFA. The main objective is to identify an effective, greener, and feasible route for the selected API while avoiding the presence of impurities that are toxic and affect crystal quality attributes.

The CAR identified two viable routes. The first is similar to the current synthesis. However, when constrained against toxic and crystallisation-relevant compounds, CAR proposed a one-step route for MFA from safe building blocks, eliminating the need to remove hazardous materials and simplifying the purification to the final crystal product. In addition, as the CAR route avoids 2-chlorobenzoic acid, the formation of benzoic acid impurity that affects the crystal morphology is minimised.

In summary, CAR identified a synthetic route for MFA that eliminated the use of hazardous and toxic compounds, improving the safety and greenness of the reaction. By reducing impurity inheritance upstream, the proposed route offers process advantages, lowering the burden on downstream purification and enabling more robust crystallisation with improved control of final crystal quality.

Acknowledgement:

This project was funded by the UKRI (10038378) and ERC (HORIZON-HLTH-2021-IND-07, 101057430).

References:

1. Fysikopoulos et.al. Comput. Chem. Eng., 2019, 122, 275-292.
2. Mustoe, et.al. Int. J. Pharm., 2025, 681, 125625.
3. Li et.al., Chemical Engineering Research and Design, 2023, 202, 126-146.
4. I. Teixeira, B. Benyahia, Chemical Engineering Research and Design, 2025, 216, 367-375.
5. I. Teixeira, et.al., JACS Au, 2024, 4, 4263-4272.

Crystallization is a cornerstone of pharmaceutical manufacturing because it strongly influences product quality attributes.¹ However, identifying suitable crystallization conditions through trial and error requires exploring a large design space, substantial time and resources.^2,3 This work presents an integrated methodology combining solvent selection, high-throughput screening, and AI-driven analysis to optimize the crystallization of meloxicam (MLX).

A multicriteria solvent screening approach based on Hansen solubility parameters and Environmental, Health, and Safety criteria was applied to identify suitable solvents for MLX crystallization. This analysis revealed dimethyl sulfoxide (DMSO) as the most promising solvent. Experimental validation was performed using a high-throughput platform equipped with turbidity measurements and high-resolution imaging. AI-based image analysis enabled real-time monitoring of morphological changes during crystallization. These results confirmed DMSO as the most suitable solvent, providing a favorable balance between solubility, controllable supersaturation, induction time, and acceptable EHS performance.

Cooling crystallization of MLX in DMSO, however, produced elongated agglomerated needles with broad size distributions and fouling, while the relatively low slope of the solubility curve limited yield. To overcome these limitations, the methodology was extended to antisolvent crystallization. Water was identified as the most suitable antisolvent, and a DMSO:H2O system was investigated experimentally. Temperature cycling improved crystal habit, transforming needle shaped crystals into more compact quasi-equant forms, although some agglomeration remained. The addition of polyvinylpyrrolidone further reduced agglomeration and produced well-defined quasi-equant crystals with a smaller particle size.

Overall, this integrated methodology lays a strong foundation for systematic optimization of crystallization procedures toward safer and more sustainable pharmaceutical manufacturing and provides a scalable framework for robust pharmaceutical process development.

Acknowledgement:

This project was funded by the UKRI (10038378) and ERC (HORIZON-HLTH-2021-IND-07, 101057430).

References

1. J. Liu et al., Computer Aided Chemical Engineering, 2021, 50, 1221-1227.
2. W. Li et al., Chemical Engineering Research and Design, 2023, 202, 126-146.
3. X. Yuan et al., Chemical Engineering Journal Advances. 2025, 23, 100823.

Introduction: The ability to predict non-covalent interactions is a major driving force behind the development of multi-component crystals of pharmaceutical compounds. Organoboronic acids have a distinctive hydrogen bonding profile, but their potential as co-formers of a variety of different active pharmaceutical ingredients is still an area of active research. This current work is dedicated to the supramolecular potential of a selection of different boronic acid derivatives as potential tools in the creation of new crystalline forms.

Methods: In order to explore the potential of these compounds as co-formers, a number of experiments were conducted with several different pharmaceutical compounds and a selection of different organoboronic acids, including phenylboronic acid and several phenyl-substituted derivatives thereof. In order to understand the process of molecular assembly, a detailed analysis of the Cambridge Structural Database was conducted to understand the interplay between homosynthons and heterosynthons within the context of boronic acid-based compounds.

Results: The results demonstrate the prevalence of strong self-associating motifs within boronic acids that can significantly impact the API-co-former interplay. The findings indicate that specific steric and electronic characteristics of the organic boronic acid compounds under investigation affect the lattice stability. This study provides a structural rationale for the observed crystallization behavior, emphasizing the role of synthon competition in the design of pharmaceutical co-crystals.

Conclusions: This work provides critical insights into the crystal engineering process mediated by boronic acids and serves to clarify the structural requirements for successful supramolecular synthesis. These results are essential for refining the selection criteria used to identify co-formers in future attempts to optimize the crystallization conditions of new multicomponent pharmaceutical phases.