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Paper des Monats
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Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how different fine-tuning strategies influence the prediction of harmonic phonon band structures, thermal properties, and the potential energy surface along imaginary phonon modes. We achieve substantial accuracy improvements with minimal additional data, with as few as 10 additional training structures already yielding significant gains. In addition to existing approaches, we introduce Equitrain, a finetuning framework that implements LoRA-based adaptation. Across 53 materials systems, we show that fine-tuned models consistently outperform both the underlying pretrained model and models trained from scratch. Equitrain achieves the best overall performance, and our results demonstrate that fine-tuning enables accurate phonon predictions.
Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspective, we examine resource considerations across the AI-driven discovery pipeline--from quantum-mechanical (QM) data generation and model training to automated, self-driving research workflows--building on discussions from the ``SusML workshop: Towards sustainable exploration of chemical spaces with machine learning'' held in Dresden, Germany. In this context, the availability of large quantum datasets has enabled rigorous benchmarking and rapid methodological progress, while also incurring substantial energy and infrastructure costs. We highlight emerging strategies to enhance efficiency, including general-purpose machine learning (ML) models, multi-fidelity approaches, model distillation, and active learning. Moreover, incorporating physics-based constraints within hierarchical workflows, where fast ML surrogates are applied broadly and high-accuracy QM methods are used selectively, can further optimize resource use without compromising reliability. Equally important is bridging the gap between idealized computational predictions and real-world conditions by accounting for synthesizability and multi-objective design criteria, which is essential for practical impact. Finally, we argue that sustainable progress will rely on open data and models, reusable workflows, and domain-specific AI systems that maximize scientific value per unit of computation, enabling efficient and responsible discovery of technological materials and therapeutics.
Linear, low-molar-mass poly(trimethylene terephthalate) (PTT) was synthesized via the polycondensation of 1,3-propanediol and dimethyl terephthalate and investigated by matrix-assisted laser desorption/ionization time of flight (MALDI TOF) mass spectrometry, size exclusion chromatography (SEC), differential scanning calorimetry (DSC) and x-ray scattering. The obtained PTT was used in crystalline plaque or powder form for studies of its solid-state polycondensation (SSP). The combination of powder and vacuum increased the number-average molecular weight (Mn) by a factor of three. Interestingly, even-numbered cycles with degrees of polymerization (DPs) between six and 16 were preferentially formed. Annealing after doping with tin catalysts produced three cyclic main reaction products (C10, C12 and C14), which suggest that thermodynamic control of transesterification processes favors the formation of three types of monodisperse extended-ring crystallites (ERC) with thicknesses of 5, 6 of 7 repeat units. Additionally, a predominantly cyclic PTT was prepared, once again demonstrating the formation of even-numbered ERC upon annealing. Crystallinities calculated from WAXS measurements showed satisfactory agreement with those determined by DSC. SAXS measurements confirmed that the crystal thickness defined by ERC is also valid for long chains and large cycles that crystallize with chain folding.
We present analytically convoluted expressions for models commonly used in small-angle X-ray scatteringv(SAXS), specifically for measurements made with instruments operating in line-focus (Kratky-type) or Ultra-SAXS (Bonse-Hart) geometries. Starting with Guinier's approximation for determining the radii of gyration, we discuss power laws, random-coil conformations of macromolecules, and spherical nanoparticles. We provide expressions for the Guinier-Porod model, the Teubner-Strey model (for microemulsions), and the generalized Ornstein-Zernike model (for gels and nanogels1). An example of the Teubner-Strey model is provided. The line-convoluted models discussed here are intended for interpreting data that has not been deconvoluted (i.e., not "desmeared"). Using line-convoluted data allows for lower detection limits and shorter measurement times compared to deconvoluted data, as artifacts introduced by deconvolution can be avoided by applying these models. We suggest utilizing line-convoluted models for high-throughput in-house SAXS analysis, which could enable time-saving routine examinations. For instance, SAXS investigations could help determine whether certain materials should be classified as nanomaterials under the European Commission's regulatory.
Purpose
The purpose of this paper is to outline replacements for conventional Nafion membranes for fuel cells that are plagued by high cost, biofouling and pH induced degradation. It targets the conducting polymer polypyrrole (Ppy) function in developing non-fluorinated polymer electrolyte membranes (PEM) as an adequate and superior replacement.
Design/methodology/approach
This is an integrative review. It critically evaluates and integrates existing scientific evidence on the use of polypyrrole (Ppy) in composite membranes for PEM fuel cells. The study is grounded on the method of how Ppy is used to modify and improve non-fluorinated base membranes’ characteristics.
Findings
The review finds composite membranes with polypyrrole (Ppy) to be very promising. It finds that Ppy enables proton transport channels to be formed at high temperature, enhances thermal and mechanical stability, provides corrosion protection to the bipolar plates and inhibits crossover of methanol. There are also serious limitations found, such as intrinsic low proton conductivity of Ppy, instability and complicated processing.
Originality/value
Originality in this review is the strict critical scrutiny of maximizing polypyrrole as a fuel cell material. It is greater than mere listing of benefits in that it transparently warrants future research requirements. This review stands out for the fact that it has a comprehensive list of ideas on how to improve, e.g. improving proton conductivity without compromising other characteristics, improving resistance to overoxidation and degradation, improving mechanical/thermal properties, making synthesis easy for scaling up and achieving regular morphology with controlled water uptake for engineering efficient membrane composites. The paper’s strength lies in its breadth and integrative approach – the review is not only surveys what has been done but also openly identifies challenges and future research opportunities.
The current work comprises three stages. First, the self-catalyzed polycondensation (SCP) of glycolic acid (GA) was studied in bulk or in suspension at 190°C or at 205°C. Cyclic poly(glycolic acid)s, cPGAs, with number average molecular weights (Mn´s) up 6 700 g mol-1 and dispersities below 2.0 were obtained. These cPGAs possess an unusual molecular weight distribution with a considerable predominance of cycles having degrees of polymerization of 28, 32 and 36. The cycles were formed in the solid state under thermodynamic control which favors the formation of extended-ring crystals. These cPGAs are an off-white, brittle porous mass that is easy to grind, yielding a flowable, crystalline powder suitable for 3D printing with laser sintering (SLS). In the second stage, the influence of non-toxic catalysts such as, Mg, Zn, Ti, Sn(II), Zr and Bi salts or complexes was studied. Compared to the results obtained with self-catalyzed polycondensation in bulk, the best metal catalysts increased the molecular weight by a factor of two to three. However, when compared to the results obtained with self-catalysis in 1,2-dichlorobenzene, the increase was limited to approximately 20%. The third stage examined the influence of 4-toluene sulfonic acid (TSA), which was found to favor the formation of the most perfect crystals with crystallinities up to 84% and the highest reported melting temperatures (up to 245 °C). This indicates the existence of a high Tm morphology, analogous to that of polylactide. Small-angle X-ray scattering (SAXS) measurements indicate that significant growth in crystal thickness is mainly responsible for these effects.
Evaluating the performance of biopolyol-based rigid foams derived from rice straw liquefaction
(2026)
Purpose
The polyurethane sector primarily relies on petrochemical substances, including polyols and isocyanates. Given the swift consumption of fossil fuel resources and the rising concerns about ecological issues and global warming, this study aims to explore the sustainable advancement of polyurethane rigid foam by using renewable biopolyols derived from agricultural waste liquefaction.
Design/methodology/approach
The liquefaction of lignocellulosic biomass involves breaking down complex polymers into smaller molecules using heat, chemicals and catalysts to prepare biopolyol as a renewable feedstock for the polyurethane industry. Spectral analysis of the liquefaction products verified that the process achieved the desired outcome and indicated the presence of hydroxyl groups. The biopolyol analysis demonstrated a biomass conversion rate of up to 87% and a hydroxyl number between 230 and 250 mg KOH/g, suggesting that this biopolyol could serve as a viable alternative to petrochemical polyols.
Findings
Various formulations of biopolyol obtained from rice straw liquefaction, conducted at 160 °C for 2 h, were prepared. Intensive study was conducted on the applicability of using biopolyol in rigid foam refrigerator formulation in comparison to petroleum counterparts. The results obtained from scanning electron microscopy showed that the biopolyol-based foams had a symmetrical cell structure and a significant proportion of sealed cells. Biobased foam demonstrated superior thermal insulation compared to its petrochemical-based equivalent.
Originality/value
These results underscore the feasibility of agricultural waste liquefaction as an eco-friendly approach for synthesizing biopolyols and their application in polyurethane foam production. The study contributes to the development of sustainable materials in the polymer industry and supports the transition toward renewable feedstocks in rigid foam applications. The study, moreover, introduces PEG 400 as a novel liquefaction solvent, offering improved compatibility with rigid polyurethane systems and establishing a new benchmark for sustainable rigid foam production.
Comprehensive Structure–Property Mapping of Tuned Mechanical Flexibility in Organic Cocrystals
(2026)
Mechanically flexible crystals offer unique opportunities for adaptive materials, yet predictive control over their responses remains a major challenge. Here, we present a chemically unified series of 4-nitrophenol-based cocrystals, cocrystallized with bipyridyl linkers of varied geometries, to systematically map structure–property relationships. Subtle variations in interplanar angles and intermolecular interactions, such as π–π stacking and hydrogen bonding, enable tuning of mechanical responses ranging from brittle fracture to different extents of elastic bending and plastic bending or twistability. This design differs from previous strategies that relied primarily on van der Waals interactions or halogen bonding to impart mechanical compliance to organic crystals. Structural analysis, supported by energy framework calculations, explains the divergent mechanical behaviors. Notably, the studied cocrystal series spans all four canonical structure–property quadrants, manifested through mechanical flexibility, photoluminescence activity, or both. This systematic and comparative study highlights the delicate interplay between molecular packing and supramolecular interactions, providing structure–property correlations that inform emerging design principles for multifunctional crystalline materials for targeted applications.
In the Seminar "Capacity building and Knowledge Exchange in Research Management" following three points are presented in detail:
- Example of a successfully completed international project,
- Role of institutional support in project success, and
- Practical challenges and lessons learned from a coordinator‘s perspective.
Accurately distinguishing oxygen evolution reaction (OER) currents from anodic metal dissolution is essential for accurately evaluating metal electrocatalysts, as both processes often overlap in the transpassive potential region.1,2 This study explored multi-principal element alloys (MPEAs) as a pathway toward sustainable electrocatalysis by reducing reliance on noble and critical metals. CrCoNi and CrMnFeCoNi alloys are used as model systems to understand how complex compositions behave when OER and dissolution occur simultaneously, providing a benchmark for designing Co-reduced/free variants within the FeCrNi MPEA family.
To quantitatively separate these pathways, we employ an integrated operando approach: tip-substrate voltammetry in scanning electrochemical microscopy (TSV-SECM) for spatially resolved O2 detection, ICP-MS and UV-Vis spectroscopy for dissolution quantification and chromium speciation, and in-situ electrochemical AFM (EC-AFM) to identify the onset of corrosion and track nanoscale surface evolution. Converting dissolution data into electrochemical charge enables a precise attribution of transpassive currents to either OER or metal dissolution. To further assessmass-transport effects, MPEAs were examined using rotating disk electrode (RDE) methods. Controlled hydrodynamics separate kinetic from diffusion-limited regimes and reveal how dissolution rates, passive-film behavior, and OER activity respond under flow conditions.
Overall, this methodology provides a robust platform for reliably distinguishing catalytic OER performance from corrosion processes while guiding the design of next-generation electrocatalysts that minimize or eliminate Co and other critical and noble metals. Extending these insights to FeCrNi-based systems offers new opportunities for sustainable, high-performance materials capable of operating under technologically relevant anodic conditions.