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Jun 12
Congratulations and Thanks to the attendees and faculty of XRD Session II - Advanced Methods. See all the Educational Opportunities that ICDD can provide you here: icdd.com/icdd-education/ #XRayDiffraction #PowderDiffraction #MaterialsScience
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Jun 11
onlinelibrary.wiley.com/doi/… - Low temperatures and high water/rock ratios in asteroid (101955) Bennu’s history based on X-ray powder diffraction of returned samples #XRayDiffraction #Astrogeology #SpaceResearch
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ICDD HQ is full of XRD attendees and faculty. Last week was Fundamentals (congratulations!) and this week is Advanced Methods. See all the Educational Opportunities that ICDD can provide you here: icdd.com/icdd-education/ #XRayDiffraction #PowderDiffraction #MaterialsScience
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ナノ粒子のXRD測定のため、大型放射光施設 SPring-8に赴きました。 XRD was measured at SPring-8. #SPring8 #nanoparticles #XrayDiffraction
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Pleased to announce that the advanced, state-of-the-art Powder X-ray Diffractometer equipped with a variable temperature attachment was formally inaugurated on 24 April 2026 by Honorable Dr. N. Kalaiselvi, DG, CSIR & Secretary, DSIR. @CSIRIndia #csiriict #XRayDiffraction
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Einstein called X-ray diffraction “the most wonderful thing that I have ever seen.” In this 1912 letter, he even sketches von Laue’s experiment. Up for bid @RRAuction in Remarkable Rarities. Closing tonight! #Einstein #Physics #XRayDiffraction #ScienceHistory
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M​ehmet Topsakal et al.: High-energy synchrotron X-ray multimodal computed tomography: enabling multiscale materials characterization at NSLS-II #XRayDiffraction #XRayImaging @BrookhavenLab @UGrenobleAlpes... #IUCr journals.iucr.org/paper?S160…

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ナノ粒子のXRD測定のため、 島川研(@Shimak_ssclab)のみなさまと国立加速器放射線研究センター (國家同步輻射研究中心, National #Synchrotron Radiation Research Center) #NSRRC 🇹🇼に赴きました。 #nanoparticles #XrayDiffraction
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XDXD: End-to-end crystal structure determination with low resolution X-ray 1. A groundbreaking study introduces XDXD, the first end-to-end deep learning framework that can determine complete atomic models directly from low-resolution single-crystal X-ray diffraction data. This innovation bypasses the need for manual map interpretation and significantly simplifies the process of crystal structure determination. 2. XDXD achieves a remarkable 70.4% match rate for structures with data limited to 2.0 ̊A resolution, with a root-mean-square error (RMSE) below 0.05. This demonstrates its robustness and accuracy, even for complex systems with up to 200 non-hydrogen atoms. 3. The model is trained on a diverse set of 395,117 simulated diffraction patterns and validated on 24,000 experimental structures from the Crystallography Open Database (COD). It shows strong performance across various space groups and chemical compositions, highlighting its broad applicability. 4. A key innovation of XDXD is its diffusion-based generative model, which iteratively refines atomic coordinates. This approach, combined with cross-attention mechanisms, allows the model to effectively leverage geometric information and produce chemically plausible crystal structures. 5. Case studies on small peptides demonstrate XDXD's potential for extension to more complex biological systems, such as proteins and nucleic acids. This suggests that the model could revolutionize structural biology by providing automated structure solutions for previously intractable cases. 6. The study also includes systematic ablation studies that quantify the critical dependence of structure determination performance on diffraction signal quality. Higher-resolution diffraction data significantly enhance predictive accuracy, confirming the importance of rich reciprocal-space information. 7. The authors plan to make the source code publicly accessible via GitHub upon acceptance of their paper, promoting further research and development in this exciting field. 📜Paper: arxiv.org/abs/2510.17936v1 #XrayDiffraction #DeepLearning #CrystalStructure #StructuralBiology #AI #Science
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PRB Editors' Suggestion: #Ultrafast #XRayDiffraction of high-pressure phases in dynamically compressed #TiO2 I. K. Ocampo, R. F. Smith, D. Kim, V. Prakapenka et al. Phys. Rev. B 112, 104103 ➡️ go.aps.org/4ptheFN #EdSugg @APSPhysics #physics #condmat
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🎉 Welcome to Read #LatestPaper #MDPICrystals 📑 The Role of #HydrogenBond Interactions in #CrystalFormation of Pyrrolo-Azines Alcohols 🧑‍🎓 by Marcel Mirel Popa et al. 📌 brnw.ch/21wVUAp #Xraydiffraction #Hirshfeld #DFT #crystalstructure
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📢 #SpecialIssue X-ray Scattering Characterization in Materials Science 📅 30 May 2026 👨‍🔬 Guest Editor: Dr. Yoshiharu Sakurai from Japan Synchrotron Radiation Research Institute (JASRI), Japan 🔗mdpi.com/journal/applsci/spe… #SmallWideAngleXrayScattering #XrayDiffraction #XrayTotalScattering #XrayRamanScattering #ResonanceIneElasticXrayscattering #XrayComptonScattering #EnergyMaterials #QuantumMaterials #SoftMaterials #DisorderedMaterials
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Peter Modregger et al.: Ultimate sensitivity in X-ray diffraction: angular moments versus shot noise #PhotonShotNoise #XRayDiffraction #BraggPeakAnalysis ... #IUCr journals.iucr.org/paper?S160…

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Akdoğan and Payzant: Thermal expansion of LaB6 from 298 to 998 K #XrayDiffraction #TemperatureCalibration #StandardMaterials ... #IUCr journals.iucr.org/paper?S160…

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14 Jul 2025
Headed to ACA 2025 in Lombard, IL? Visit booth #21 to see the PhotonJetMAX-S mockup and grab a free T-shirt. Wear it and enter our photo contest for a chance to win a $150, $100, or $50 gift card! Post your photo using #ACA2025WithRigaku on LInkedIn by July 28. #ACA2025WithRigaku #ACA2025 #Crystallography #XRayDiffraction #RigakuAsk
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ナノ粒子のXRD測定のため、大型放射光施設 SPring-8に赴きました。 XRD was measured at SPring-8. #SPring8 #nanoparticles #XrayDiffraction
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Article: Sterebellosides A–F, Six New Diterpene Glycosides from the Soft Coral Stereonephthya bellissima, by Anran Fu et al. mdpi.com/1660-3397/23/3/121# #softcoral #Stereonephthyabellissima #diterpeneglycosides #Xraydiffraction #proangiogenic
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𝐗𝐑𝐃 𝐔𝐬𝐞𝐫𝐬 𝐌𝐞𝐞𝐭 𝟐𝟎𝟐𝟓 | 𝐇𝐚𝐧𝐝𝐬-𝐨𝐧 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐨𝐧 𝐗-𝐫𝐚𝐲 𝐃𝐢𝐟𝐟𝐫𝐚𝐜𝐭𝐢𝐨𝐧 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞 The Office of the Dean-Research successfully hosted a two-day immersive workshop on X-ray Diffraction (XRD), led by Prof Laxmi Narayana Patro, Mr Arun Kumar Bandarapu, and Mr K Sumit and coordinated by Mr Ch Srinivas. The event witnessed enthusiastic participation from 80 attendees, including 40 external participants from various institutions. From theoretical insights to practical sessions—including sample analysis and I-STEM facility booking guidance—the workshop provided a rich learning experience. Participants gained hands-on skills in XRD and deepened their understanding of material characterisation techniques, fostering cross-institutional collaboration and research excellence. #SRMUniversityAP #SRMAP #SRMAmaravati #SRM #ResearchAtSRMAP #SRMAPResearch #XRDWorkshop #ResearchInnovation #MaterialCharacterisation #ISTEMIndia #HandsOnTraining #CollaborativeLearning #XRayDiffraction #ResearchCommunity
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🔥 Read our Review Paper 📚 X-ray Diffraction Data Analysis by Machine Learning Methods—A Review 🔗 mdpi.com/2076-3417/13/17/999… 👨‍🔬 by Vasile-Adrian Surdu et al. #Xraydiffraction #phaseidentification
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