Helmholtz Institute Jena

We present a femtosecond laser system based on a 49-core, Ytterbium-doped fiber. Phase control of the individual beams enables fast beam-shaping up to the kHz frequency range at 150 W total average power after compression.

Abstract The creation and characterization of high-quality crystalline monolayer transition metal dichalcogenides (TMDCs) are crucial for the development of future electronic device applications. Traditional methods face challenges in achieving the necessary spatial resolution in electronic structure analysis, especially when dealing with identical sample work functions and chemical environments, e.g., those in antiparallel twin domains. Here, we employed momentum-selected (or dark-field) photoelectron emission microscopy (PEEM) via a momentum microscope (PMM) apparatus to successfully characterize domains of one monolayer WS 2 on Au(111) that was not possible with conventional PEEM. The spatial mapping of the selected band structure contribution of a specific domain revealed the existence of many twin domains with a size of around 5–50 μm forming a continuous film of over 500 μm × 500 μm. Simultaneously, i.e., within a single instrument, we verified the one monolayer thickness of the grown film. Our work highlights the potential of PMM as a versatile instrument for surface characterization, paving the way for advancements in materials science and nanotechnology.

Machine learning applications in polymer science are often inefficient due to molecular representations that neglect the inherent hierarchical and statistical nature of macromolecules. This work introduces a structure-aware graph convolutional network (GCN) framework that addresses this limitation by treating polymer samples as statistical ensembles. The approach utilizes a hierarchical graph representation where nodes correspond to monomer units and explicitly integrates molecular mass distribution (MMD) data to account for sample dispersity. A key innovation is an ensemble-based training strategy using topologically realistic graphs generated on-demand via an optimized kinetic Monte Carlo simulation. The model's efficacy was validated on a broad range of tasks. On synthetic data, it achieved more than 98% accuracy in classifying complex polymer architectures. When applied to a large experimental dataset, the model predicts glass transition temperatures (Tg) with high accuracy (R2 = 0.89±0.01). Crucially, a fine-tuning experiment demonstrated that the model could successfully learn the physically / chemically grounded relationship between Tg and molar mass by integrating MMD information. This work establishes a robust and physically realistic paradigm for polymer informatics, enabling more accurate property predictions and paving the way for accelerated in silico material design.

Using light energy to drive chemical transformations is of great relevance, with photosynthesis in nature as a grand example. In artificial light-driven catalysis, part of nature's complex supramolecular architecture can be mimicked through the so-called covalently linked photosensitizer-catalyst (PS-CAT) dyads. We herein report a dyad using an organic donor-acceptor PS, with dipyridophenazine as the acceptor and tert-butylcarbazole as the donor (2 t BuCzDPPZ), that contains a coordination site for a rhodium(iii)Cp* center as the catalyst. The organic PS shows a charge-transfer transition upon visible-light irradiation and has redox properties similar to typically used ruthenium-based PSs. The resulting PS-CAT dyad 2 t BuCzDPPZRhCp* shows - with methoxy-substituted 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzo[d]imidazole (BIH-OMe) as the sacrificial electron donor - photocatalytic activity in light-driven NAD+ reduction with a TON of 3.2 (after 4 h). Femtosecond transient absorption and resonance Raman spectroscopy, as well as time-dependent density functional theory (TDDFT) calculations, shed light on the photophysical properties of the PS and PS-CAT dyad and reveal a high dependency of the photoluminescence quantum yield and excited state properties on solvent polarity - in line with its donor-acceptor structure. This work presents a new design concept for PS-CAT dyads in artificial light-driven catalysis and provides important insight into the interplay between solvation dynamics of organic donor-acceptor systems and their photophysics, paving the way for future design strategies.

The effects of porosity on the nanostructure and physiochemical properties of graphitic carbon nitride (g-C3N4) materials remain poorly understood both experimentally and theoretically. Here, three types of g-C3N4 materials with distinct morphologies, including layered, rod-like, and curved spherical structures, were investigated, showing significant variations in porosity, hydrophilicity, optical bandgap, charge transfer efficiency, and photocatalytic activity for oxygen reduction reaction to produce hydrogen peroxide (H2O2). Under 410 nm irradiation, the most porous material achieves a H2O2 yield of 2.7 mmol∙g-1∙L-1, representing a tenfold increase compared to the bulk g-C3N4. Three theoretical models are applied to investigate curvature effects, quantum size effects, and their combination. The curvature in g-C3N4 leads to an increase in the bandgap. Further, the formation of intrinsic micro-/meso-pores with curved/distorted surfaces is not feasible in g-C3N4 due to strong stacking interactions and the observed mesoporosity arises primarily from the nano-assembly of small crystallites rather than from curved surfaces. These findings deepen our understanding of porosity effects on the structure of g-C3N4 and highlight the importance of nanostructure design in optimizing g-C3N4 for photocatalytic applications.

Abstract Artificial electric skin with multi‐intensity pain‐evaluating capabilities offers promising opportunities for the construction of friendly human‐robot interaction. However, realizing a stepwise sensing system generally requires lateral integration of diverse materials, which is prone to delamination and thus operation failure. Here, a fully soft, monolithic hydrogel‐based artificial fingertip (HBAF), fabricated via digital light processing (DLP) 3D printing, enabling robotic fingertips to distinguish objects in varying sizes is proposed. To enhance the mechanical and conductive properties of a printed hydrogel, a two‐step post‐processing method is developed to introduce a secondary functional network into a high‐resolution soft model. This modification can increase stretchability by three‐fold and conductivity by 1.78‐fold compared to the original printed hydrogel. Notably, the integration challenge between the hydrogel‐based sensor and the robotic body part is addressed by growing a polydopamine gel layer at the interface of the 3D model's base to enhance contact. Furthermore, the HBAF's size parameters can be programmed to achieve distinct pain thresholds, demonstrating its potential for personalized bionic sensors in artificial limbs and enhancing safety in collaborative robotics.

The hydrothermal synthesis of the new aluminum metal-organicframework(Al-MOF) CAU-63 [Al7(OH)12O3(2,4-HPydc)3] and two new Al coordination polymers(CPs) Al-Pydc-CP1 [Al2(OH)5(2,4-HPydc)]and Al-Pydc-CP2 [Al­(OH)­(H2O)­(2,4-Pydc)] linkedby anions of lutidinic acid (pyridine-2,4-dicarboxylic acid, 2,4-H2Pydc) is reported. High-throughput investigations of the Al3+/2,4-H2Pydc/NaOH/H2O system were carriedout to determine the fields of formation. An increase of the molarratio of metal to linker was found to be the key parameter for theformation of higher condensed inorganic building units (IBU), changingfrom dimeric to one- and two-dimensional structures. The crystal structureswere determined by 3D electron diffraction with subsequent Rietveldrefinement against powder X-ray diffraction data. The pyridine nitrogenatoms of the linker molecules coordinate to aluminum ions in all threecompounds, resulting in crystal structures deviating from the typicallyobserved MIL-53 and CAU-10 type frameworks. The coordination polymers Al-Pydc-CP1 and Al-Pydc-CP2 contain edge-sharingAl–O/N polyhedra leading to dimeric and helical IBUs, whilein CAU-63, tetrameric [Al4O14N2] units are bridged by Al3+ ions, leading to ahoneycomb Al–O–N network with organic moieties interconnectingthe layers. This linkage results in channel-like ultramicropores,which are accessible to H2O and NH3 moleculesbut too small to adsorb N2 and even CO2.

Abstract Hydrogen peroxide (H2O2) is a versatile chemical, valued as both a promising energy carrier and a widely used oxidizing agent in disinfection and organic synthesis. The light‐driven catalytic oxygen reduction reaction (ORR) using carbon nitrides (CNx) is based on the conversion of solar into chemical energy and thus offers a sustainable pathway for decentralized H2O2 production. This study presents a novel synthetic strategy for producing ionic derivatives of CNx, specifically poly(heptazine imides) (PHIs) with higher specific surface areas, using an ordered mesoporous silica material (SBA‐15) as a template. The templated PHIs exhibit enhanced porosity, controlled incorporation of transition metals, improved visible‐light absorption, tunable hydrophilicity and more efficient charge separation compared to bulk CNx. PHIs containing iron, cobalt or nickel accelerate H2O2 decomposition, whereas templated potassium PHI (KPHI) achieves a 2.1‐fold increase in H2O2 production with ethanol as a hole scavenger under visible light irradiation (455 nm, 50 mW·cm−2) compared to bulk KPHI (KPHI_b). A high H2O2 production rate of 19.0 mmol·L−1·h−1 (i.e., 76.2 mmol·g−1·h−1) under the same irradiation condition is achieved with KPHI in a 90 vol.% methanol solution and an optimal photonic yield of 12.8% is obtained with KPHI at 365 nm.