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Pushing the experimental resolution boundary in chromatin fibre organisation using multiscale simulations
(doi: 10.1016/j.gde.2026.102464)
Machine Learning Accelerates Crystallization for Structure Determination
(doi: 10.1002/ange.1218503)
Machine Learning Accelerates Crystallization for Structure Determination
(doi: 10.1002/anie.1218503)
Photocatalytic Transfer Hydrogenation Using Plastic Hydrolysates as Hydrogen Donor
(doi: 10.1002/ange.4324362)
Photocatalytic Transfer Hydrogenation Using Plastic Hydrolysates as Hydrogen Donor
(doi: 10.1002/anie.4324362)
Single-particle imaging uncovers reverse electron transfer efficiency between Shewanella oneidensis MR-1 and shaped haematite
(doi: 10.1038/s41929-026-01530-x)
Interfacing Broad-Spectrum Semiconductors with Hydrogenases for Semi-Artificial Solar Reforming of Cellulose.
(doi: 10.1021/jacs.6c03439)
Glutathione-responsive fragmentation of heteronorbornadiene-based thiovinyl sulfones in glioma cells
Optical nanoscopy of spatiotemporal metal stripping cooperativity at single-ion and subparticle resolution
(doi: 10.1038/s41563-026-02567-w)
CyanOperon: An Operon Building Expansion for the CyanoGate MoClo Toolkit.
(doi: 10.1021/acssynbio.6c00162)
Loss of catalytic activity and impaired proteostasis in guanosine nucleotide-depleted LRRK2
(doi: 10.64898/2026.04.21.719846)
Monitoring Redox Pathways and Performance Limitations in Lithium‐Sulfur Batteries Using In Situ
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Li and
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S NMR Spectroscopies
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Li and
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S NMR Spectroscopies
(doi: 10.1002/anie.202525050)
Monitoring Redox Pathways and Performance Limitations in Lithium‐Sulfur Batteries Using In Situ
<sup>7/6</sup>
Li and
<sup>33</sup>
S NMR Spectroscopies
<sup>7/6</sup>
Li and
<sup>33</sup>
S NMR Spectroscopies
(doi: 10.1002/ange.202525050)
Towards the targeted protein degradation of CK2: design and synthesis of CAM4066-based PROTACs
(doi: 10.3762/bjoc.22.47)
Novel Knotted Solenoid fold with order-shifted coil arrangement leads to nontrivial 3<sub>1</sub> topology.
(doi: 10.1073/pnas.2525920123)
Accelerating point defect simulations using data-driven and machine learning approaches
Evaluation of stratospheric transport in three generations of Chemistry-Climate Models
(doi: 10.5194/acp-26-5249-2026)
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