Foto: Forschungsprogramm Energieeffizienz, Materialien und Ressourcen ©Copyright: BengsEnergy Efficient Processes

Energy > Energy Efficiency, Materials and Resources - All Topics

Foto: Measuring liquid metal flows ©Copyright: HZDR/Frank BierstedtIndustrial processes contribute to the total German energy consumption in the form of electricity and heat with about 29 %. Within the industrial sector, the largest consumers are the chemical and petrochemical industries (38 %), as well as the metal producing industries (31 %).* Reference: AG Energiebilanzen e.V., Energy Balance 2000 to 2015 (2017).

Within the frame of German "Energiewende", higher efficiency as well as adaptivity to fluctuating energy and raw materials supply are a grand challenge for industry in terms of economy, sustainability, and competitiveness. HZDR contributes to these goals by conducting research with a strong focus on energy-intensive industrial processes. Research activities comprise the topics Multiphase and Thermal Processes and Liquid Metal Processes.

Experimental research is carried out at unique experimental facilities, such as TOPFLOW, DRESDYN, and LIMMCAST. These are operated at near-industrial conditions and equipped with proprietary measurement and imaging techniques (e.g. wire-mesh sensors, ultrafast X-ray tomography, gamma-ray tomography, contactless inductive flow tomography, ultrasound Doppler velocimetry).

Methods for multiphase computational fluid dynamics (CFD) are developed for the device scale with own modelling concepts for polydisperse (iMUSIG) and separated (AIAD) two-phase flows, flow regime transitions (GENTOP) as well as multi-physics concepts.

On the micro-scale, research on transport processes at interfaces is performed. Findings contribute to the optimization of industrial processes such as extraction, absorption, distillation, electrochemistry, and minerals flotation.

Focusing on industrial applications, innovative industrial processing strategies and technologies are developed: magnetic actuation of melts, process intensification methods, and new sensor and process control strategies. Eventually, system analyses are meant to assess the efficacy of new methods.

The HZDR scientists cooperate closely with leading national and international academic and industrial partners in the fields of technical chemistry, biochemistry, metallurgy, and materials technology. The two Helmholtz Research Alliances "Energy Efficient Multiphase Processes" and "Liquid Metal Technologies" were successfully completed recently.


Objectives

  • to gain an in-depth understanding of transport processes from the molecular and interface level to the device scale at industry-relevant process conditions
  • to derive validated physics-based models for flow, heat and mass transfer and to develop advanced computational methods and tools for supporting process design
  • to develop and implement methods of process instrumentation, intensification and control.

Press Releases


Involved HZDR institutes


Collaborations


Contacts


Publications

  • Vanderbruggen, A.; Bachmann, K.; Rudolph, M. et al.
    A Contribution to a Better Understanding of Lithium-Ion Battery Recycling by Using Automated Mineralogy
    World of Metallurgy - Erzmetall 75(2022)3, 144-152
  • Li, W.; Wang, G.; Sui, W. et al.
    Facile and scalable preparation of cage-like mesoporous carbon from lignin-based phenolic resin and its application in supercapacitor electrodes
    Carbon 196(2022)2, 819-827 (10.1016/j.carbon.2022.05.053)
  • Hao, S.; Guanhua, W.; Jing, G. et al.
    Reduction of lignin heterogeneity for improved catalytic performance of lignin nanosphere supported Pd nanoparticles
    Industrial Crops and Products 180(2022)1, 114685 (10.1016/j.indcrop.2022.114685)
  • Ming, L.; Xu, M.; Lijuan, S. et al.
    Effects of surface microbubbles on the adhesion between air bubble/oil droplet and graphite surfaces
    Colloids and Surfaces A: Physicochemical and Engineering Aspects 660(2023) (10.1016/j.colsurfa.2022.130809)
  • Zicheng, C.; Xiangyang, H.; Jing, G. et al.
    Controllable fabrication of nanofibrillated cellulose supported HKUST-1 hierarchically porous membranes for highly efficient removal of formaldehyde in air
    Industrial Crops and Products 186(2022)1, 115269 (10.1016/j.indcrop.2022.115269)
  • Ni, W.; Shuang, Q.; Guanhua, W. et al.
    Acid-promoted lignin reductive depolymerization under mild conditions via a condensation minimizing approach: From organosolv lignin to woody biomass
    Fuel 338(2023)1, 127311 (10.1016/j.fuel.2022.127311)
  • Xu, M.; Vanderbruggen, A.; Kupka, N. et al.
    Influence of MIBC on the surface-air nucleation and bubble-particle loading in graphite froth flotation
    Minerals Engineering 185(2022), 107714 (10.1016/j.mineng.2022.107714)
  • Buchmann, M.; Öktem, G.; Rudolph, M. et al.
    Proposition of a bubble-particle attachment model based on DLVO van der Waals and electric double layer interactions for froth flotation modelling
    Physicochemical Problems of Mineral Processing 58(2022)5, 154812 (10.37190/ppmp/154812)
  • Kurade, M. B.; Mustafa, G.; Zahid, M. T. et al.
    Integrated phycoremediation and ultrasonic-irradiation treatment (iPUT) for the enhanced removal of pharmaceutical contaminants in wastewater
    Chemical Engineering Journal 455(2023), 140884 (10.1016/j.cej.2022.140884)
  • Guarnieri, P.; Thiele, S. T.; Baker, N. et al.
    Unravelling the Deformation of Paleoproterozoic Marbles and Zn-Pb Ore Bodies by Combining 3D-Photogeology and Hyperspectral Data (Black Angel Mine, Central West Greenland)
    Minerals 12(2022)7, 800 (10.3390/min12070800)
  • Rasti, B.; Koirala, B.; Scheunders, P.
    HapkeCNN: Blind Nonlinear Unmixing for Intimate Mixtures Using Hapke Model and Convolutional Neural Network
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5536315 (10.1109/TGRS.2022.3202490)
  • Opara, C. B.; Kamariah, N.; Spooren, J. et al.
    Interesting halophilic sulfur-oxidising bacteria with bioleaching potential: Implications for pollutant mobilisation from mine waste
    Microorganisms 11(2023)1, 222 (10.3390/microorganisms11010222)
  • Neumann-Heyme, H.; Shevchenko, N.; Grenzer, J. et al.
    In-situ measurements of dendrite tip shape selection in a metallic alloy
    Physical Review Materials 6(2022), 063401 (10.1103/PhysRevMaterials.6.063401)
  • Camacho Hernandez, J. N.; Link, G.; Schubert, M. et al.
    Experimental Study of a Compact Microwave Applicator for Evaporation of Airflow-Entrained Droplets
    Materials 15(2022), 6765 (10.3390/ma15196765)
  • Boelens, P.; Bobeth, C.; Hinman, N. et al.
    Peptide functionalized Dynabeads for the magnetic carrier separation of rare-earth fluorescent lamp phosphors
    Journal of Magnetism and Magnetic Materials 563(2022), 169956 (10.1016/j.jmmm.2022.169956)
  • Li, Z.; Lu, F.; Zhang, H. et al.
    The Outcome of the 2021 IEEE GRSS Data Fusion Contest—Track MSD: Multitemporal Semantic Change Detection
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 1643-1655 (10.1109/JSTARS.2022.3144318)
  • Tavakkoli Piralilou, S.; Einali, G.; Ghorbanzadeh, O. et al.
    A Google Earth Engine Approach for Wildfire Susceptibility Prediction Fusion with Remote Sensing Data of Different Spatial Resolutions
    Remote Sensing 14(2022), 672 (10.3390/rs14030672)
  • Chang, S.; Ghamisi, P.
    Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5534913 (10.1109/TGRS.2022.3195339)
  • Ghorbanzadeh, O.; Shahabi, H.; Crivellari, A. et al.
    Landslide detection using deep learning and object-based image analysis
    Landslides 19(2022), 929-939 (10.1007/s10346-021-01843-x)
  • Li, H.; Zech, J.; Hong, D. et al.
    Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection
    International Journal of Applied Earth Observation and Geoinformation 110(2022), 102804 (10.1016/j.jag.2022.102804)
  • Song, W.; Gao, Z.; Dian, R. et al.
    Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5617514 (10.1109/TGRS.2022.3143571)
  • Shahi, K. R.; Ghamisi, P.; Rasti, B. et al.
    MS2A-Net: Multiscale Spectral–Spatial Association Network for Hyperspectral Image Clustering
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 6518-6530 (10.1109/JSTARS.2022.3198137)
  • Aslam, B.; Maqsoom, A.; Khalil, U. et al.
    Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan
    Sensors 22(2022), 3107 (10.3390/s22093107)
  • Namdari, S.; Zghair Alnasrawi, A. I.; Ghorbanzadeh, O. et al.
    Time Series of Remote Sensing Data for Interaction Analysis of the Vegetation Coverage and Dust Activity in the Middle East
    Remote Sensing 14(2022), 2963 (10.3390/rs14132963)
  • Huang, L.; Chen, Y.; He, X. et al.
    Supervised Contrastive Learning-Based Classification for Hyperspectral Image
    Remote Sensing 14(2022), 5530 (10.3390/rs14215530)
  • Persello, C.; Wegner, J. D.; Hänsch, R. et al.
    Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities
    IEEE Geoscience and Remote Sensing Magazine 10(2022)2, 172-200 (10.1109/MGRS.2021.3136100)
  • Omid, G.; Khalil, G.; Ghamisi, P.
    The application of ResU-net and OBIA for landslide detection from multi-temporal sentinel-2 images
    Big Earth Data (2022) (10.1080/20964471.2022.2031544)
  • Xu, Y.; Ghamisi, P.
    Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5619815 (10.1109/TGRS.2022.3156392)
  • Das, S.; Pratiher, S.; Kyal, C. et al.
    Sparsity Regularized Deep Subspace Clustering for Multicriterion-Based Hyperspectral Band Selection
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 4264-4278 (10.1109/JSTARS.2022.3172112)
  • Cai, Y.; Zhang, Z.; Ghamisi, P. et al.
    Superpixel Contracted Neighborhood Contrastive Subspace Clustering Network for Hyperspectral Images
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5530113 (10.1109/TGRS.2022.3179637)
  • Seydgar, M.; Rahnamayan, S.; Ghamisi, P. et al.
    Semisupervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5535218 (10.1109/TGRS.2022.3195924)
  • He, Z.; Xia, K.; Ghamisi, P. et al.
    HyperViTGAN: Semisupervised Generative Adversarial Network With Transformer for Hyperspectral Image Classification
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 6053-6068 (10.1109/JSTARS.2022.3192127)
  • Wang, W.; Chen, Y.; Ghamisi, P.
    Transferring CNN With Adaptive Learning for Remote Sensing Scene Classification
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5533918 (10.1109/TGRS.2022.3190934)
  • Zhang, L.; Qian, Y.; Han, J. et al.
    Mixed Noise Removal for Hyperspectral Image With l0-l1−2SSTV Regularization
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 5371-5387 (10.1109/JSTARS.2022.3185657)
  • Yue, J.; Fang, L.; Ghamisi, P. et al.
    Optical Remote Sensing Image Understanding With Weak Supervision: Concepts, methods, and perspectives
    IEEE Geoscience and Remote Sensing Magazine 10(2022)2, 250-269 (10.1109/MGRS.2022.3161377)
  • Lu, M.; Fang, L.; Li, M. et al.
    NFANet: A Novel Method for Weakly Supervised Water Extraction From High-Resolution Remote-Sensing Imagery
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5617114 (10.1109/TGRS.2022.3140323)
  • Ulku, I.; Akagündüz, E.; Ghamisi, P.
    Deep Semantic Segmentation of Trees Using Multispectral Images
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 7589-7604 (10.1109/JSTARS.2022.3203145)
  • Chang, S.; Kopp, M.; Ghamisi, P.
    Sketched Multiview Subspace Learning for Hyperspectral Anomalous Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 60(2022), 5543412 (10.1109/TGRS.2022.3220814)
  • Wu, L.; Fang, L.; Yue, J. et al.
    Deep Bilateral Filtering Network for Point-Supervised Semantic Segmentation in Remote Sensing Images
    IEEE Transactions on Image Processing 31(2022), 7419-7434 (10.1109/TIP.2022.3222904)
  • Ghorbanzadeh, O.; Xu, Y.; Zhao, H. et al.
    The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15(2022), 9927-9942 (10.1109/JSTARS.2022.3220845)
  • Xu, Y.; Ghamisi, P.
    Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes With Point-Level Annotations
    IEEE Transactions on Image Processing 31(2022), 5038-5051 (10.1109/TIP.2022.3189825)
  • Santini, E.; Nepita, I.; Bykov, A. G. et al.
    Interfacial dynamics of adsorption layers as support of biomedical research and diagnostics
    Colloids and Interfaces 6(2022)4, 81 (10.3390/colloids6040081)
  • Javadi, A.; Nourizade, M.; Rahmani, M. et al.
    Interaction of Catalyst Nanoparticles and Pollutant Molecules in Photocatalytic Wastewater Treatment: Novel Characterization via Dynamic Surface Properties
    Chemical Engineering Science (2023) (10.1016/j.ces.2023.118459)
  • Amani, P.; Miller, R.; Javadi, A. et al.
    Pickering foams and parameters influencing their characteristics
    Advances in Colloid and Interface Science 301(2022), 102606 (10.1016/j.cis.2022.102606)
  • Dowlati, S.; Javadi, A.; Miller, R. et al.
    Unfolded Lipase at Interfaces Studied via Interfacial Dilational Rheology: The Impact of Urea
    Colloids and Interfaces 6(2022)4, 56 (10.3390/colloids6040056)
  • Gloaguen, R.; Ajjabou, L.; Ali, S. et al.
    Mineral revolution for the Wellbeing Economy
    Global Sustainability 5(2022), e15 (10.1017/sus.2022.13)
  • Khan, H.; Lehnigk, R.; Rzehak, R.
    Euler-Euler Simulation of Absorption and Desorption in Co- and Counter-current Bubble Column Flows
    Chemical Engineering Science 267(2023), 118313 (10.1016/j.ces.2022.118313)
  • Kappelt, C.; Rzehak, R.
    Investigation of Fluid-dynamics and Mass-transfer in a bubbly mixing layer by Euler-Euler simulation
    Chemical Engineering Science 264(2022), 118147 (10.1016/j.ces.2022.118147)
  • Krause, T.; Keshavarzi, B.; Dressel, J. et al.
    Rsn‐2‐mediated directed foam enrichment of β‐lactamase
    Biotechnology Journal 17(2022)12, 2200271 (10.1002/biot.202200271)
  • Sébastien, A.; Mayur, P.; Leandro, J. et al.
    Investigating Pore‐Opening of Hydrogel Foams at the Scale of Freestanding Thin Films
    Macromolecular Rapid Communications 43(2022)17 (10.1002/marc.202200189)
  • Ivanova, M. E.; Peters, R.; Müller, M. et al.
    Technological Pathways to Produce Compressed and Highly Pure Hydrogen from Solar Power
    Angewandte Chemie - International Edition 2023(2023), e202218850 (10.1002/anie.202218850)
  • Kołczyk-Siedlecka, K.; Socha, R. P.; Yang, X. et al.
    Study on kinetics and mechanism of Re(VII) ion adsorption and desorption using commercially available activated carbon and solutions containing Se(VI) as an impurity
    Hydrometallurgy 215(2023), 105973 (10.1016/j.hydromet.2022.105973)
  • Bashkatov, A.; Hossain, S. S.; Mutschke, G. et al.
    On the Growth Regimes of Hydrogen Bubbles at Microelectrodes
    Physical Chemistry Chemical Physics 24(2022), 26738-26752 (10.1039/D2CP02092K)
  • Akay, Ö.; Bashkatov, A.; Coy, E. et al.
    Electrolysis in Reduced Gravitational Environments: Current Research Perspectives and Future Applications
    NPJ Microgravity 8(2022), 56 (10.1038/s41526-022-00239-y)
  • Keshavarzi, B.; Krause, T.; Schwarzenberger, K. et al.
    Wash water addition on protein foam for removal of soluble impurities in foam fractionation process
    Colloids and Surfaces A: Physicochemical and Engineering Aspects 655(2022)130215 (10.1016/j.colsurfa.2022.130215)
  • Mao, S.; Zhou, T.; Liao, Y. et al.
    Thermal-hydraulic and particle deposition analysis of supercritical CO2 in different tubes
    Powder Technology 413(2023), 118076 (10.1016/j.powtec.2022.118076)
  • Salces, A. M.; Bremerstein, I.; Rudolph, M. et al.
    Joint recovery of graphite and lithium metal oxides from spent lithium-ion batteries using froth flotation and investigation on process water re-use
    Minerals Engineering 184(2022), 107670 (10.1016/j.mineng.2022.107670)
  • Ziauddin, M.; Schleicher, E.; Trtik, P. et al.
    Comparing Wire-Mesh sensor with neutron radiography for measurement of liquid fraction in foam
    Journal of Physics: Condensed Matter 51(2023)1, 015101 (10.1088/1361-648X/ac9d16)
  • Zhu, H.; Yang, B.; Rudolph, M. et al.
    Flotation separation of galena from sphalerite using hyaluronic acid (HA) as an environmental-friendly sphalerite depressant
    Minerals Engineering 187(2022), 107771 (10.1016/j.mineng.2022.107771)
  • Emmerich, H.; Knüpfer, L.; Heitkam, S. et al.
    Ultrasound imaging of liquid fraction in foam
    IEEE Transactions on Instrumentation and Measurement 72(2022), 6500211 (10.1109/TIM.2022.3228582)
  • Rox, H.; Bashkatov, A.; Yang, X. et al.
    Bubble size distribution and electrode coverage at porous nickel electrodes in a novel 3-electrode flow-through cell
    International Journal of Hydrogen Energy 48(2023)8, 2892-2905 (10.1016/j.ijhydene.2022.10.165)
  • Vanderbruggen, A.; Hayagan, N.; Bachmann, K. et al.
    Lithium-Ion Battery Recycling─Influence of Recycling Processes on Component Liberation and Flotation Separation Efficiency
    ACS ES&T Engineering 2(2022)11, 2130-2141 (10.1021/acsestengg.2c00177)
  • Zhang, J.; Ding, W.; Wang, Z. et al.
    Microscopic liquid-gas interface effect on liquid wetting
    Journal of Colloid and Interface Science 630(2023), 813-822 (10.1016/j.jcis.2022.10.062)
  • Xu, M.; Haijun, Z.; Rudolph, M.
    Influences of oil collector on surface air nucleation in fine graphite flotation
    Separation and Purification Technology 303(2022), 122165 (10.1016/j.seppur.2022.122165)
  • Tas-Köhler, S.; Neumann-Kipping, M.; Liao, Y. et al.
    Experimental Investigations and Numerical Assessment of Liquid Velocity Profiles and Turbulence for Single- and Two-phase Flow in a Constricted Vertical Pipe
    International Journal of Multiphase Flow 157(2022), 104224 (10.1016/j.ijmultiphaseflow.2022.104224)
  • Werner, D.; Mütze, T.; Peuker, U.
    Influence of Pretreatment Strategy on the Crushing of Spent Lithium-Ion Batteries
    Metals 12(2022)11, 1839 (10.3390/met12111839)
  • Skibinska, K.; Wojtaszek, K.; Krause, L. et al.
    Tuning up catalytical properties of electrochemically prepared nanoconical Co-Ni deposit for HER and OER
    Applied Surface Science 607(2022), 155004 (10.1016/j.apsusc.2022.155004)
  • Yan, H.; Zhang, H.; Liao, Y. et al.
    A single bubble rising in the vicinity of a vertical wall: A numerical study based on volume of fluid method
    Ocean Engineering 263(2022), 112379 (10.1016/j.oceaneng.2022.112379)
  • Hossain, S. S.; Bashkatov, A.; Yang, X. et al.
    The force balance of hydrogen bubbles growing and oscillating on a microelectrode
    Physical Review E 106(2022), 035105 (10.1103/PhysRevE.106.035105)
  • Ugalde, H.; Morris, W.; Madriz Diaz, Y. C. et al.
    Locating skarns with magnetic survey data, Geyer, Erzgebirge: optimizing data acquisition procedures
    Geophysical Prospecting 70(2022), 1273-1292 (10.1111/1365-2478.13231)
  • Garcia, M. M.; Sattar, M. A.; Atmani, H. et al.
    Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation
    Sensors 22(2022), 4443 (10.3390/s22124443)
  • Schmidt, A.; Montenegro, V.; Reuter, M. et al.
    Transient CFD Calculation of Accretion Formation in a Copper Waste Heat Boiler
    Metallurgical and Materials Transactions B 53(2022), 3765-3774 (10.1007/s11663-022-02639-7)
  • Raatz, S.; Huether, J.; Joachimsthaler, C. et al.
    A terminology for downcycling
    Journal of Industrial Ecology (2022) (10.1111/jiec.13289)
  • Lorenz, S.; Thiele, S. T.; Kirsch, M. et al.
    Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland
    Data 7(2022), 104 (10.3390/data7080104)
  • Giester, G.; Lengauer, C. L.; Chanmuang N., C. et al.
    Saccoite, Ca2Mn+32F(OH)8·0.5(SO4), a new, microporous mineral from the Kalahari Manganese Fields, South Africa
    Mineralogical Magazine 86(2022)5, 814-820 (10.1180/mgm.2022.60)
  • Apanasevich, P.; Lucas, D.; Sato, Y. et al.
    DNS and Highly-Resolved LES of Heat and Mass Transfer in Two-Phase Counter-Current Condensing Flow
    Flow, Turbulence and Combustion 109(2022), 697-757 (10.1007/s10494-022-00340-y)
  • Liao, Y.; Wang, Q.; Caliskan, U. et al.
    Investigation of particle effects on bubble coalescence in slurry with a chimera MP-PIC and VOF coupled method
    Chemical Engineering Science 265(2023), 118174 (10.1016/j.ces.2022.118174)
  • Matys, S.; Morawietz, L.-M.; Lederer, F. et al.
    Characterization of the binding behavior of specific cobalt- and nickel ion-binding peptides identified by phage surface display
    Separations 9(2022)11, 354 (10.3390/separations9110354)
  • Stergiou, Y.; Hauser, M. J. B.; Wit, A. D. et al.
    Chemical flowers: Buoyancy-driven instabilities under modulated gravity during a parabolic flight
    Physical Review Fluids 7(2022), 110503 (10.1103/PhysRevFluids.7.110503)
  • Banari, A.; Hertel, D.; Schlink, U. et al.
    Simulation of particle resuspension by wind in an urban system
    Environmental Fluid Mechanics (2022) (10.1007/s10652-022-09905-x)
  • Flechsig, S.; Sohr, J.; Schubert, M. et al.
    A new tomography-based approach for the fluid dynamic description of conventional structured packings and sandwich packings
    Chemical Engineering and Processing: Process Intensification 171(2022), 108530 (10.1016/j.cep.2021.108530)
  • Hoang, D. H.; Imhof, R.; Sambrook, T. et al.
    Recovery of fine gold loss to tailings using advanced reactor pneumatic flotation ImhoflotTM
    Minerals Engineering 184(2022), 107649 (10.1016/j.mineng.2022.107649)
  • Staud, R.; Heller, D.; Knüpfer, L. et al.
    A minimal-invasive method for the evaluation of liquid fractions in foams with a point level sensor
    Chemical Engineering & Technology 45(2022)8, 1397-1403 (10.1002/ceat.202200072)
  • Huang, M.; Uhlemann, M.; Eckert, K. et al.
    Pulse reverse plating of copper micro-structures in magnetic gradient fields
    Magnetochemistry 8(2022), 66 (10.3390/magnetochemistry8070066)
  • Birjukov, M.; Zvejnieks, P.; Lappan, T. et al.
    Particle tracking velocimetry in liquid gallium flow around a cylindrical obstacle
    Experiments in Fluids 63(2022)6, 99 (10.1007/s00348-022-03445-2)
  • Glavinic, I.; Galindo, V.; Stefani, F. et al.
    Contactless Inductive Flow Tomography for real-time control of electromagnetic actuators in metal casting
    Sensors 22(2022)11, 4155 (10.3390/s22114155)
  • Eggemann, L.; Rau, F.; Stolten, D.
    The Ecological Potential of Manure Utilisation in Small-Scale Biogas Plants
    Applied Energy 331(2023), 120445 (10.1016/j.apenergy.2022.120445)
  • Yin, J.; Zhang, T.; Krull, B. et al.
    A CFD approach for the flow regime transition in a gas-liquid vane-type separator
    International Journal of Multiphase Flow 159(2023), 104320 (10.1016/j.ijmultiphaseflow.2022.104320)
  • Reinecke, S.; Buntkiel, L.; Kipping, R. et al.
    Process characterization in industrial vessels by flow-following sensor particles
    Measurement Science and Technology 33(2022)9, 095106 (10.1088/1361-6501/ac75af)
  • Keshavarzi, B.; Krause, T.; Sikandar, S. et al.
    Protein Enrichment by Foam Fractionation: Experiment and Modeling
    Chemical Engineering Science (2022) (10.1016/j.ces.2022.117715)
  • Shi, P.; Sommer, A.-E.; Rox, H. et al.
    Euler-Euler / RANS Modeling of Solid-liquid Flow in Stirred Tanks: a Comprehensive Model Validation
    Minerals Engineering 185(2022), 107679 (10.1016/j.mineng.2022.107679)
  • Opara, C. B.; Blannin, R.; Ebert, D. et al.
    Bioleaching of metal(loid)s from sulfidic mine tailings and waste rock from the Neves Corvo mine, Portugal, by an acidophilic consortium
    Minerals Engineering 188(2022), 107831 (10.1016/j.mineng.2022.107831)
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    On the prospects of magnetic-field-assisted electrodeposition of nano-structured ferromagnetic layers
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