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Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

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Energy & Environmental Materials 2024年第2期7卷 326-333页

作者： Andrew Martin Drew Lilley Raνi Prasher Sumanjeet Kaur Energy Technologies Area Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA Department of Mechanical Engineering UC BerkeleyBerkeleyCA 94720USA

Thermal energy storage(TES)solutions offer opportunities to reduce energy consumption,greenhouse gas emissions,and ***,they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load,which are critical toward zero energy *** materials(TCMs)as a class of TES undergo a solid-gas reversible chemical reaction with water vapor to store and release energy with high storage capacities(600 kWh m^(-3))and negligible self-discharge that makes them uniquely suited as compact,stand-alone units for daily or seasonal ***,TCMs suffer from instabilities at the material(salt particles)and reactor level(packed beds of salt),resulting in poor multi-cycle efficiency and high-levelized cost of *** this study,a model is developed to predict the pulverization limit or Rcrit of various salt hydrates during thermal *** is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy-efficient manufacturing process(solid-state mixing)to make the *** model is experimentally validated on multiple TCM salt hydrates with different water content,and effect of Rcrit on hydration and dehydration kinetics is also investigated.

关键词： high energy density hydration kinetics long-term cycling thermal energy storage thermochemical materials

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

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npj Computational Materials 2023年第1期9卷 2036-2043页

作者： Nathan J.Szymanski Christopher J.Bartel Yan Zeng Mouhamad Diallo Haegyeom Kim Gerbrand Ceder Department of Materials Science&Engineering UC BerkeleyBerkeleyCA 94720USA Materials Sciences Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

Machine learning(ML)has become a valuable tool to assist and improve materials characterization,enabling automated interpretation of experimental results with techniques such as X-ray diffraction(XRD)and electron *** ML models are fast once trained,there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness,which creates broad opportunities for rapid learning and information extraction from ***,we demonstrate such a capability with the development of autonomous and adaptive *** coupling an ML algorithm with a physical diffractometer,this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline *** validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement *** improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house *** findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.

关键词： phase diffraction autonomous

Accurate and efficient exploit capture and classification

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Science China(Information Sciences) 2017年第5期60卷 193-209页

作者： Yu DING Tao WEI Hui XUE Yulong ZHANG Chao ZHANG Xinhui HAN Institute of Computer Science and Technology Peking University Eletrical Engineering and Computer Sciences UC Berkeley

Software exploits, especially zero-day exploits, are major security threats. Every day, security experts discover and collect numerous exploits from honeypots, malware forensics, and underground ***, no easy methods exist to classify these exploits into meaningful categories and to accelerate diagnosis as well as detailed analysis. To address this need, we present Seismo Meter, which recognizes both control-flowhijacking, and data-only attacks by combining approximate control-flow integrity, fast dynamic taint analysis and API sandboxing schemes. Once it detects an exploit incident, Seismo Meter generates a succinct data representation, called an exploit skeleton, to characterize the captured exploit. Seismo Meter then classifies the captured exploits into different exploit families by performing distance computing on the extracted *** evaluate the efficiency of Seismo Meter, we conduct a field test using exploit samples from public exploit databases, such as Metasploit, as well as wild-captured exploits. Our experiments demonstrate that Seismo Meter is a practical system that successfully detects and correctly classifies all these exploit attacks.

关键词： software security exploit classification exploit attack capture control flow integrity JIT security

Subcellular western blotting of single cells

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Microsystems & Nanoengineering 2017年第1期3卷 405-413页

作者： Kevin A.Yamauchi Amy E.Herr Department of Bioengineering University of CaliforniaBerkeleyCA 94720USA The uc berkeley—ucSF Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA

Although immunoassays are the de facto standard for determining subcellular protein localization in individual cells,antibody probe cross-reactivity and fixation artifacts remain confounding *** enhance selectivity while providing single-cell resolution,we introduce a subcellular western blotting technique capable of separately assaying proteins in the 14 pL cytoplasm and 2 pL nucleus of individual *** confer precision fluidic control,we describe a passive multilayer microdevice that leverages the rapid transport times afforded by *** isolating single cells in microwells,we apply single-cell differential detergent fractionation to lyse and western blot the cytoplasmic lysate,whereas the nucleus remains intact in the ***,we lyse the intact nucleus and western blot the nuclear *** index each protein analysis to the originating subcellular compartment,we utilize bi-directional electrophoresis,a multidimensional separation that assays the lysate from each compartment in a distinct region of the separation ***-cell bi-directional electrophoresis eliminates the need for semi-subjective image segmentation algorithms required in *** subcellular,single-cell western blot is demonstrated for six targets per cell,and successfully localizes spliceosome-associated proteins solubilized from large protein and RNA complexes,even for closely sized proteins(a 7 kDa difference).Measurement of NF-κB translocation dynamics in unfixed cells at 15-min intervals demonstrates reduced technical variance compared with *** chemical cytometry assay directly measures the nucleocytoplasmic protein distribution in individual unfixed cells,thus providing insight into protein signaling in heterogeneous cell populations.

关键词： cytometry microfluidic design proteomics single-cell analysis

Classifying handedness in chiral nanomaterials using label error robust deep learning

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npj Computational Materials 2022年第1期8卷 1417-1423页

作者： C.K.Groschner Alexander J.Pattison Assaf Ben-Moshe A.Paul Alivisatos Wolfgang Theis M.C.Scott Department of Materials Science and Engineering UC BerkeleyBerkeleyCAUSA School of Physics and Astronomy University of BirminghamBirminghamUK Department of Chemistry University of CaliforniaBerkeleyBerkeleyCAUSA Materials Sciences Division Lawrence Berkeley National LaboratoryBerkeleyCAUSA Molecular Foundry Lawrence Berkeley National LaboratoryBerkeleyBerkeleyCAUSA

High-throughput scanning electron microscopy(SEM)coupled with classification using neural networks is an ideal method to determine the morphological handedness of large populations of chiral *** labeling removes the time-consuming manual labeling of training data,but introduces label error,and subsequently classification error in the trained neural ***,we evaluate methods to minimize classification error when training from automated labels of SEM datasets of chiral Tellurium *** the mirror relationship between images of opposite handed particles,we artificially create populations of varying label *** analyze the impact of label error rate and training method on the classification error of neural networks on an ideal dataset and on a practical *** the three training methods considered,we find that a pretraining approach yields the most accurate results across label error rates on ideal datasets,where size and other morphological variables are held constant,but that a co-teaching approach performs the best in practical application.

关键词： error chiral remove

Enabling materials informatics for ^(29)Si solid-state NMR of crystalline materials

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npj Computational Materials 2020年第1期6卷 1219-1225页

作者： He Sun Shyam Dwaraknath Handong Ling Xiaohui Qu Patrick Huck Kristin A.Persson Sophia E.Hayes Department of Chemistry Washington UniversitySt.LouisMO 63130USA Lawrence berkeley National Laboratory BerkeleyCA 94720USA Department of Materials Science and Engineering UC BerkeleyBerkeleyCA 94720USA

Nuclear magnetic resonance(NMR)spectroscopy is a powerful tool for obtaining precise information about the local bonding of materials,but difficult to interpret without a well-vetted dataset of reference *** ability to predict NMR parameters and connect them to three-dimensional local environments is critical for understanding more complex,long-range interactions.

关键词： spectra NMR crystalline

Eguchi–Hanson Singularities in U(2)-Invariant Ricci Flow

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Peking Mathematical Journal 2023年第1期6卷 1-141页

作者： Alexander Appleton Department of Mathematics UC BerkeleyBerkeleyCA 94720USA

We show that a Ricci flow in four dimensions can develop singularities modeled on the Eguchi–Hanson *** particular,we prove that starting from a class of asymptotically cylindrical U(2)-invariant initial metrics on T S^(2),a Type II singularity modeled on the Eguchi–Hanson space develops in finite ***,we show that for these Ricci flows the only possible blow-up limits are(i)the Eguchi–Hanson space,(ii)the flat R4/Z2 orbifold,(iii)the 4d Bryant soliton quotiented by Z2,and(iv)the shrinking cylinder R×RP^(3).As a byproduct of our work,we also prove the existence of a new family of Type II singularities caused by the collapse of a two-sphere of self-intersection|k|≥3.

关键词： Ricci Flow Eguchi–Hanson metric Singularity model Four dimensional Blow-up

Validating neural networks for spectroscopic classification on a universal synthetic dataset

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npj Computational Materials 2023年第1期9卷 1325-1336页

作者： Jan Schuetzke Nathan J.Szymanski Markus Reischl Institute for Automation and Applied Informatics Karlsruhe Institute of TechnologyKarlsruhe 76131Germany Department of Materials Science&Engineering Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA Department of Materials Science&Engineering UC BerkeleyBerkeleyCA 94720USA

To aid the development of machine learning models for automated spectroscopic data classification,we created a universal synthetic dataset for the validation of their *** dataset mimics the characteristic appearance of experimental measurements from techniques such as X-ray diffraction,nuclear magnetic resonance,and Raman spectroscopy among *** applied eight neural network architectures to classify artificial spectra,evaluating their ability to handle common experimental *** all models achieved over 98%accuracy on the synthetic dataset,misclassifications occurred when spectra had overlapping peaks or *** found that non-linear activation functions,specifically ReLU in the fully-connected layers,were crucial for distinguishing between these classes,while adding more sophisticated components,such as residual blocks or normalization layers,provided no performance *** on these findings,we summarize key design principles for neural networks in spectroscopic data classification and publicly share all scripts used in this study.

关键词： spectroscopic adding classify

Perspectives and clinical practices of optometrists in Saudi Arabia concerning myopia in children

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International Journal of Ophthalmology(English edition) 2023年第2期16卷 267-273页

作者： Muteb K.Alanazi Essam S.Almutleb Yousef S.Badawood Mohammed A.Kudam Maria Liu Optometry Department College of Applied Medical SciencesKing Saud UniversityRiyadh 11362Saudi Arabia uc berkeley School of Optometry Berkeley 94720CaliforniaUnited States

AIM:To investigate the practice patterns of optometrists in Saudi Arabia regarding myopia ***:An internet-based survey was distributed to all practicing optometrists in Saudi Arabia(n=1886).The survey contained questions related to 1)demographics,2)knowledge about myopia and its associated complications,3)current clinical care,4)type and frequency of myopia treatment prescribed,and 5)potential barriers limiting treatment ***:The completed surveys were collected from 171 optometrists(9.06%response rate,60%male).Knowledge regarding myopia-associated complications was prevalent but somewhat inaccurate among the *** refraction at initial visit was used by 59%of the *** cover test was the most reported binocular vision test(83%),and 38%of optometrists did not perform any ocular *** prescribed single-vision spectacles for children with *** time spent outdoors was selected by 80%of the practitioners who prescribed myopia control treatment as the primary *** support and lack of clinical experience in providing myopia treatment were reported as the most important factors limiting the adoption of myopia management ***:The current optometric practices in Saudi Arabia require further *** appear to be somewhat aware of myopia and the associated ***,most evidence-based myopia treatments are not being locally adopted,primarily because of lack of support,lack of experience,and limited availability.

关键词： myopia myopia management optometry clinical practice Saudi Arabia