Recent Submissions

  • Impact of membrane biofouling in the sequential development of performance indicators: Feed channel pressure drop, permeability, and salt rejection

    Siebdrath, Nadine; Siddiqui, Amber; Ding, Wei; Kruithof, Joop; Vrouwenvelder, Johannes S. (Journal of Membrane Science, Elsevier BV, 2019-05-18) [Article]
    Biofouling development is affected by a variety of factors that change over the length of reverse osmosis (RO) membrane modules in pressure vessels. Spatially resolved biofouling formation was studied under conditions representative to practice using four one-meter Long Channel Membrane Test Cells (LCMTCs) in series, simulating an industrial pressure vessel. Biofouling was induced by dosing an easily assimilable substrate to the feed water. The impact of biofouling on the sequential decline of RO membrane performance indicators (feed channel pressure drop, permeability and salt rejection) was investigated. Also, the temporal organic carbon (DOC) consumption was assessed spatially over the four test cells. Results showed that all membrane performance indicators were impacted by biofouling formation. The feed channel pressure (FCP) drop increase was impacted earliest and strongest followed by permeability and salt rejection decline, underlining that FCP drop is a sensitive and early biofouling monitoring indicator. Spatially resolved biofouling investigations revealed that most biofouling was formed in the lead sections of membrane installation with a decreasing gradient over length, linked to DOC availability in the system. In this study, FCP drop played a crucial role: the FCP drop increase at the lead test cell of the membrane installation caused performance losses for the downstream test cells. Minimizing the effect of biofouling on membrane performance should be pursued by a combination of strategies involving (i) early detection and preventive cleaning, (ii) substrate limitation for delaying biofouling built-up and (iii) optimized (early) cleaning procedures for more effective biofilm removal.
  • The role of fungi in heterogeneous sediment microbial networks

    Marie Booth, Jenny; Fusi, Marco; Marasco, Ramona; Michoud, Gregoire; Fodelianakis, Stylianos; Merlino, Giuseppe; Daffonchio, Daniele (Scientific Reports, Springer Science and Business Media LLC, 2019-05-17) [Article]
    While prokaryote community diversity and function have been extensively studied in soils and sediments, the functional role of fungi, despite their huge diversity, is widely unexplored. Several studies have, nonetheless, revealed the importance of fungi in provisioning services to prokaryote communities. Here, we hypothesise that the fungal community plays a key role in coordinating entire microbial communities by controlling the structure of functional networks in sediment. We selected a sediment environment with high niche diversity due to prevalent macrofaunal bioturbation, namely intertidal mangrove sediment, and explored the assembly of bacteria, archaea and fungi in different sediment niches, which we characterised by biogeochemical analysis, around the burrow of a herbivorous crab. We detected a high level of heterogeneity in sediment biogeochemical conditions, and diverse niches harboured distinct communities of bacteria, fungi and archaea. Saprotrophic fungi were a pivotal component of microbial networks throughout and we invariably found fungi to act as keystone species in all the examined niches and possibly acting synergistically with other environmental variables to determine the overall microbial community structure. In consideration of the importance of microbial-based nutrient cycling on overall sediment ecosystem functioning, we underline that the fungal microbiome and its role in the functional interactome cannot be overlooked.
  • Net community production in a productive coastal ocean from an autonomous buoyancy-driven glider

    Haskell, W.Z.; Hammond, D.E.; Prokopenko, M.G.; Teel, E.N.; Seegers, B.N.; Ragan, M.A.; Rollins, N.; Jones, Burton (Journal of Geophysical Research: Oceans, American Geophysical Union (AGU), 2019-05-17) [Article]
    Net community production (NCP), an analog of carbon export out of the surface ocean, is often estimated using budgets of dissolved oxygen. Accurate estimates of oxygen-based NCP, especially in dynamic coastal regions, require constraints on vertical transport of water with O2 out of equilibrium with the atmosphere, non-steady state change in the oxygen inventory, heating/cooling-driven O2 disequilibrium, and the rate of bubble injection from wave activity. The latter two are typically evaluated by using discrete measurements of the O2/Ar ratio in lieu of O2 only. Because sophisticated sampling and measurement techniques are required to make these measurements, they are often limited in spatiotemporal resolution. However, high-resolution estimates of NCP may be useful in determining small-scale patchiness in export. In this study, we calculated high-resolution NCP in coastal Southern California using dissolved oxygen measurements made by an autonomous buoyancy-driven Slocum glider and an empirical relationship derived using discrete measurements of O2/Ar in the surface mixed layer to remove the influence of bubble injection, which accounted for ~1/4 of the O2 supersaturation observed. Using estimates of vertical transport from wind-speed based parameterizations, previously validated using a 7Be budget, we were able to correct for the physical biases to the signal, which are known to significantly influence dissolved oxygen budgets in this region. Our results agree well with previously published NCP estimates for the study area, but also reveal higher-frequency variability that discrete sampling was unable to resolve, suggesting that this approach may be useful in other regions with well-constrained vertical transport rates.
  • Design and Mechanistic Study of Highly-durable Carbon Coated Cobalt Diphosphide Core-shell Nanostructure Electrocatalyst for the Efficient and Stable Oxygen Evolution Reaction

    Alsabban, Merfat M.; Yang, Xiulin; Wahyudi, Wandi; Fu, Jui-Han; Hedhili, Mohamed N.; Ming, Jun; Yang, Chih-Wen; Nadeem, M. Amtiaz; Idriss, Hicham; Lai, Zhiping; Li, Lain-Jong; Tung, Vincent C.; Huang, Kuo-Wei (ACS Applied Materials & Interfaces, American Chemical Society (ACS), 2019-05-16) [Article]
    Facile synthesis of hierarchically functional, catalytically active, and electrochemically stable nanostructures holds tremendous promise for catalyzing efficient and durable oxygen evolution reaction (OER), yet remains a formidable challenge. Herein, we report the scalable production of core-shell nanostructures comprised of carbon-coated cobalt diphosphide nanosheets, C@CoP2, via three simple steps: (i) electrochemical deposition of Co-species; (ii) gas phase phosphidation, and (iii) carbonization of CoP2 for catalytic durability enhancement. Electrochemical characterizations showed that C@CoP2 delivers an overpotential of 234 mV, retains its initial activity for over 80 hours of continuous operation, and exhibits a fast OER rate of 63.8 mV dec-1 in base.
  • Square-Root Variable Metric based elastic full-waveform inversion – Part 1: Theory and validation

    Liu, Qiancheng; Peter, Daniel; Tape, Carl (Geophysical Journal International, Oxford University Press (OUP), 2019-05-16) [Article]
    Full-waveform inversion (FWI) has become a powerful tool in inverting subsurface geophysical properties. The estimation of uncertainty in the resulting Earth models and parameter trade-offs, although equally important to the inversion result, has however often been neglected or became prohibitive for large-scale inverse problems. Theoretically, the uncertainty estimation is linked to the inverse Hessian (or posterior covariance matrix), which for massive inverse problems becomes impossible to store and compute. In this study, we investigate the application of the square-root variable metric (SRVM) method, a quasi-Newton optimisation algorithm, to FWI in a vector version. This approach allows us to reconstruct the final inverse Hessian at an affordable storage memory cost. We conduct SRVM based elastic FWI on several elastic models in regular, free-surface and practical cases. Comparing the results with those obtained by the state-of-the-art L-BFGS algorithm, we find that the proposed SRVM method performs on a similar, highly-efficient level as L-BFGS, with the advantage of providing additional information such as the inverse Hessian needed for uncertainty quantification.
  • Electron density measurements in shock tube using microwave interferometry

    Toujani, Nesrine; Alquaity, Awad Bin Saud; Farooq, Aamir (Review of Scientific Instruments, AIP Publishing, 2019-05-16) [Article]
    Microwave interferometry (MWI) is a nonintrusive diagnostic technique, capable of measuring small quantities of electrons present in a flame plasma. In this paper, a 94 GHz microwave interferometer is characterized and validated to perform robust and reliable measurements of electron concentrations in thermal and nonthermal plasmas in a shock tube. The MWI system is validated first by measuring the refractive index of a dielectric material. Subsequently, the system is used for measuring electron densities during the thermal ionization of argon and krypton in shock tube experiments. The measured activation energies are in good agreement with both the measured values from previous studies and theoretical values. The MWI system is finally used for measuring electron density time-histories in fuel oxidation experiments in the shock tube. The electron density profile of methane combustion shows a peak at the ignition time which agrees with pressure measurements. Experimental electron histories are also in overall agreement with predictions of the methane ion chemistry model.
  • Literature-Based Enrichment Insights into Redox Control of Vascular Biology

    Essack, Magbubah; Salhi, Adil; Stanimirovic, Julijana; Tifratene, Faroug; Bin Raies, Arwa; Hungler, Arnaud; Uludag, Mahmut; Van Neste, Christophe; Trpkovic, Andreja; Bajic, Vladan P.; Bajic, Vladimir B.; Isenovic, Esma R. (Oxidative Medicine and Cellular Longevity, Hindawi Limited, 2019-05-16) [Article]
    In cellular physiology and signaling, reactive oxygen species (ROS) play one of the most critical roles. ROS overproduction leads to cellular oxidative stress. This may lead to an irrecoverable imbalance of redox (oxidation-reduction reaction) function that deregulates redox homeostasis, which itself could lead to several diseases including neurodegenerative disease, cardiovascular disease, and cancers. In this study, we focus on the redox effects related to vascular systems in mammals. To support research in this domain, we developed an online knowledge base, DES-RedoxVasc, which enables exploration of information contained in the biomedical scientific literature. The DES-RedoxVasc system analyzed 233399 documents consisting of PubMed abstracts and PubMed Central full-text articles related to different aspects of redox biology in vascular systems. It allows researchers to explore enriched concepts from 28 curated thematic dictionaries, as well as literature-derived potential associations of pairs of such enriched concepts, where associations themselves are statistically enriched. For example, the system allows exploration of associations of pathways, diseases, mutations, genes/proteins, miRNAs, long ncRNAs, toxins, drugs, biological processes, molecular functions, etc. that allow for insights about different aspects of redox effects and control of processes related to the vascular system. Moreover, we deliver case studies about some existing or possibly novel knowledge regarding redox of vascular biology demonstrating the usefulness of DES-RedoxVasc. DES-RedoxVasc is the first compiled knowledge base using text mining for the exploration of this topic.
  • Detecting Small Faces in the Wild Based on Generative Adversarial Network and Contextual Information

    Zhang, Yongqiang; Ding, Mingli; Bai, Yancheng; Ghanem, Bernard (Pattern Recognition, Elsevier BV, 2019-05-15) [Article]
    Face detection techniques have been developed for decades, and one of the remaining open challenges is detecting small faces in unconstrained conditions. The reason is that tiny faces are often lacking detailed information and blurry. In this paper, we proposed an algorithm to directly generate a clear high-resolution face from a small blurry one by adopting a generative adversarial network (GAN). Toward this end, the basic GAN formulation achieves it by super-resolving and refining sequentially (e.g. SR-GAN and Cycle-GAN). However, we design a novel network to address the problem of super-resolving and refining jointly. Moreover, we also introduce new training losses (i.e. classification loss and regression loss) to promote the generator network to recover fine details of the small faces and to guide the discriminator network to distinguish face vs. non-face and to refine location simultaneously. Additionally, considering the importance of contextual information when detecting tiny faces in crowded cases, the context around face regions is combined to train the proposed GAN-based network for mining those very small faces from unconstrained scenarios. Extensive experiments on the challenging datasets WIDER FACE and FDDB demonstrate the effectiveness of the proposed method in restoring a clear high-resolution face from a small blurry one, and show that the achieved performance outperforms previous state-of-the-art methods by a large margin.
  • Synthesis and Reactivity of [Au(NHC)(Bpin)] Complexes

    Nolan, Steven P; Zinser, Caroline; Falivene, Laura; Nahra, Fady; Brill, Marcel; Cordes, David Bradford; Slawin, Alexandra; Cavallo, Luigi; Cazin, Catherine (Chemical Communications, Royal Society of Chemistry (RSC), 2019-05-15) [Article]
    A new class of [Au(NHC)(Bpin)] complexes has been synthesized and their unusual reactivity was investigated using computational and experimental methods. The gold-boryl complexes exhibit unexpected high stability and reactivity.
  • Robust Full-Waveform Inversion with Radon-Domain Matching Filter

    Sun, Bingbing; Alkhalifah, Tariq Ali (GEOPHYSICS, Society of Exploration Geophysicists, 2019-05-15) [Article]
    "Cycle skipping" is a severe issue in Full-Waveform Inversion.One option to overcome it is to extend the search space to allow data comparisons beyond the "point-to-point" subtraction.A matching filter can be computed by deconvolving the measured data from the predicted ones. If the model is correct, the resulting matching filter would be a Dirac delta function in which the energy is focused at zero lag. An optimization problem can be formulated by penalizing this matching filter departure from a Dirac delta function. As the matching filter replaces the local, sample-by-sample, comparison with a global one using deconvolution, it can reduce the “cycle skipping” problem. As the matching filter is computed using the whole trace of the measured and predicted data, it is prone to unwanted cross-talks of different events.We propose to perform the deconvolution in the Radon domain to reduce those kinds of cross-talks and improve the inversion. We first transform both the measured and the predicted data into the τ - p domain using the local Radon transform. We then perform deconvolution for the trace indexed by the same slope value. The main objective of the proposal is to use the slope information embedded in the Radon transform representation to separate the events and reduce the cross-talks in the deconvolution step. As a result, the objective function tends to be more convex and stabilizes the inversion process.The result obtained for the modified Marmousi model demonstrates the proposed Radon-domain matching-filter approach can converge to a meaningful model given data without the low frequencies below 3 Hz and a v(z) initial model.Compared to the conventional time-space matching-filter approach, the Radon-domain approach shows fewer artifacts in the model and better fitting of the measured data.The result corresponding to the Chevron 2014 benchmark dataset also shows the good performance of the proposed approach.
  • Facile production of silver-reduced graphene oxide nanocomposite with highly effective antibacterial performance

    Chen, Long; Li, Zhi; Chen, Mingguang (Journal of Environmental Chemical Engineering, Elsevier BV, 2019-05-14) [Article]
    Reduced graphene oxide (rGO) has broad applications based upon its superior electronic properties. In many cases, an additional antibacterial function of these materials requests physical or chemical modification, such as incorporating silver nanoparticles into rGO to produce silver-reduced graphene oxide (Ag/rGO) composite. Most of the previous methods of preparing Ag/rGO are top-down techniques starting from graphite exfoliation into graphene oxide (GO), to the reduction of a mixture of silver nitrate and GO into the Ag/rGO nanocomposite. This method is flawed by its high cost, tedious treatments, and heavy pollution from generated wastes. Herein, we manifest a novel bottom-up strategy of growing Ag/rGO totally from a cellulose acetate and silver nitrate precursor in one step without tedious solution exfoliation and chemical treatment steps. The produced Ag/rGO nanocomposite maintains highly effective antibacterial activity, which is ascribed to the synergy between the effect of rGO size and incorporated bactericidal silver nanoparticles. Our strategy is promising for industrial production from sustainability and cost-effectiveness perspectives.
  • Reconstructing Cloud Contaminated Pixels Using Spatiotemporal Covariance Functions and Multitemporal Hyperspectral Imagery

    Angel, Yoseline; Houborg, Rasmus; McCabe, Matthew (Remote Sensing, MDPI AG, 2019-05-14) [Article]
    One of the major challenges in optical-based remote sensing is the presence of clouds, which imposes a hard constraint on the use of multispectral or hyperspectral satellite imagery for earth observation. While some studies have used interpolation models to remove cloud affected data, relatively few aim at restoration via the use of multi-temporal reference images. This paper proposes not only the use of image time-series, but also the implementation of a geostatistical model that considers the spatiotemporal correlation between them to fill the cloud-related gaps. Using Hyperion hyperspectral images, we demonstrate a capacity to reconstruct cloud-affected pixels and predict their underlying surface reflectance values. To do this, cloudy pixels were masked and a parametric family of non-separable covariance functions was automated fitted, using a composite likelihood estimator. A subset of cloud-free pixels per scene was used to perform a kriging interpolation and to predict the spectral reflectance per each cloud-affected pixel. The approach was evaluated using a benchmark dataset of cloud-free pixels, with a synthetic cloud superimposed upon these data. An overall root mean square error (RMSE) of between 0.5% and 16% of the reflectance was achieved, representing a relative root mean square error (rRMSE) of between 0.2% and 7.5%. The spectral similarity between the predicted and reference reflectance signatures was described by a mean spectral angle (MSA) of between 1° and 11°, demonstrating the spatial and spectral coherence of predictions. The approach provides an efficient spatiotemporal interpolation framework for cloud removal, gap-filling, and denoising in remotely sensed datasets.
  • Deep Learning Deepens the Analysis of Alternative Splicing

    Zou, Xudong; Gao, Xin; Chen, Wei (Genomics, Proteomics & Bioinformatics, Elsevier BV, 2019-05-14) [Article]
  • Poly-phenylenediamine-derived Atomically Dispersed Ni Sites for Electroreduction of CO2 to CO

    Zheng, Yonglong; Han, Jianyu; Takele, Leta; Xie, Feng; Zhang, Yin; Sun, Jiqing; Han, Bing; Chen, Jing; Gao, Yan; Tang, Zhiyong (Inorganic Chemistry Frontiers, Royal Society of Chemistry (RSC), 2019-05-14) [Article]
    CO2 electroreduction is a promising technique for the management of the global carbon balance by low-grade renewable electricity. However, the lack of high efficient and selective catalyst has frustrated the development of this area. Here, we report a poly-phenylenediamine-derived atomically dispersed Ni catalyst as a highly efficient and selective electrocatalyst for the conversion of CO2 to CO. The catalyst exhibited efficient production of CO with high Faradaic efficiency (FE) (90%) and a large current density of 11.6 mA cm-2 at −0.8 V vs. reversible hydrogen electrode (RHE). An excellent turnover frequency (TOF) of 3079 h−1 for electroreduction of CO2 was also achieved at −0.8 V vs. RHE.
  • Semantics in the Deep: Semantic Analytics for Big Data

    Koutsomitropoulos, Dimitrios; Likothanassis, Spiridon; Kalnis, Panos (Data, MDPI AG, 2019-05-13) [Article]
  • Fingerprint-to-CH stretch continuously tunable high spectral resolution Stimulated Raman Scattering microscope

    Laptenok, Sergey P; Rajamanickam, Vijayakumar Palanisamy; Genchi, Luca; Monfort, Tual; Lee, Yeonwoo; Patel, Imran I; Bertoncini, Andrea; Liberale, Carlo (Journal of Biophotonics, Wiley, 2019-05-13) [Article]
    Stimulated Raman scattering (SRS) microscopy is a label-free method generating images based on chemical contrast within samples, and has already shown its great potential for high-sensitivity and fast imaging of biological specimens. The capability of SRS to collect molecular vibrational signatures in bio-samples, coupled with the availability of powerful statistical analysis methods, allows quantitative chemical imaging of live cells with sub-cellular resolution. This application has substantially driven the development of new SRS microscopy platforms. Indeed, in recent years, there has been a constant effort on devising configurations able to rapidly collect Raman spectra from samples over a wide vibrational spectral range, as needed for quantitative analysis by using chemometric methods. In this paper an SRS microscope which exploits spectral shaping by a narrowband and rapidly tunable Acousto Optical Tunable Filter (AOTF) is presented. This microscope enables spectral scanning from the Raman fingerprint region to the CH-stretch region without any modification of the optical setup. Moreover, it features also a high enough spectral resolution to allow resolving Raman peaks in the crowded fingerprint region. Finally, application of the developed SRS microscope to broadband hyperspectral imaging of biological samples over a large spectral range from 800 cm-1 till 3600 cm-1 , is demonstrated. This article is protected by copyright. All rights reserved.
  • Addition of the Lewis Acid Zn(C6F5)2 Enables Organic Transistors with a Maximum Hole Mobility in Excess of 20 cm2/Vs

    Paterson, Alexandra F.; Tsetseris, Leonidas; Li, Ruipeng; Basu, Aniruddha; Faber, Hendrik; Emwas, Abdul-Hamid; Panidi, Julianna; Fei, Zhuping; Niazi, Muhammad Rizwan; Anjum, Dalaver H.; Heeney, Martin; Anthopoulos, Thomas D. (Advanced Materials, Wiley, 2019-05-10) [Article]
    Incorporating the molecular organic Lewis acid tris(pentafluorophenyl)borane [B(C6 F5 )3 ] into organic semiconductors has shown remarkable promise in recent years for controlling the operating characteristics and performance of various opto/electronic devices, including, light-emitting diodes, solar cells, and organic thin-film transistors (OTFTs). Despite the demonstrated potential, however, to date most of the work has been limited to B(C6 F5 )3 with the latter serving as the prototypical air-stable molecular Lewis acid system. Herein, the use of bis(pentafluorophenyl)zinc [Zn(C6 F5 )2 ] is reported as an alternative Lewis acid additive in high-hole-mobility OTFTs based on small-molecule:polymer blends comprising 2,7-dioctyl[1]benzothieno [3,2-b][1]benzothiophene and indacenodithiophene-benzothiadiazole. Systematic analysis of the materials and device characteristics supports the hypothesis that Zn(C6 F5 )2 acts simultaneously as a p-dopant and a microstructure modifier. It is proposed that it is the combination of these synergistic effects that leads to OTFTs with a maximum hole mobility value of 21.5 cm2 V-1 s-1 . The work not only highlights Zn(C6 F5 )2 as a promising new additive for next-generation optoelectronic devices, but also opens up new avenues in the search for high-mobility organic semiconductors.
  • Ultra-selective carbon molecular sieve membranes for natural gas separations based on a carbon-rich intrinsically microporous polyimide precursor

    Hazazi, Khalid; Ma, Xiaohua; Wang, Yingge; Ogieglo, Wojciech; Alhazmi, Abdulrahman; Han, Yu; Pinnau, Ingo (Journal of Membrane Science, Elsevier BV, 2019-05-10) [Article]
    A highly contorted, carbon-rich intrinsically microporous polyimide (PIM-PI) made from spirobifluorene dianhydride and 3,3-dimethylnaphthidine (SBFDA-DMN) was employed as a precursor for the formation of carbon molecular sieve (CMS) membranes at pyrolysis temperatures from 550 to 1000 °C. The high carbon content of SBFDA-DMN (∼84%) resulted in only 28% total weight loss during pyrolysis under a nitrogen atmosphere at 1000 °C. The development of the various microstructural textures was characterized by gas sorption analysis, Brunauer-Emmett-Teller (BET) surface area, X-ray diffraction, Raman spectroscopy, electrical conductivity, and gas transport properties. Heat treatment of a pristine SBFDA-DMN membrane at 550 °C resulted in reduced permeability for all gases (e.g.: PCO2 dropped from 4700 to 1500 barrer) as well as lower BET surface area from 621 to 545 m2 g−1. At 600 °C, new pores induced by pyrolysis increased the BET surface area to nearly that of the precursor and significantly improved gas separation performance. Above 600 °C, a progressive collapse of the micropores became evident with CMS membranes showing higher gas-pair selectivity but lower permeability. At 1000 °C, ultra-micropores comparable in size with the kinetic diameter of CH4 emerged and induced a prominent molecular sieving effect resulting in very high CH4 rejection. This strong size exclusion effect, further supported by gravimetric gas sorption measurements, resulted in unusually high N2/CH4 and CO2/CH4 selectivities of 35 and 1475, respectively.
  • Discretizations of Surfaces with Constant Ratio of Principal Curvatures

    Jimenez, Michael R.; Müller, Christian; Pottmann, Helmut (Discrete & Computational Geometry, Springer Science and Business Media LLC, 2019-05-10) [Article]
    Motivated by applications in architecture, we study surfaces with a constant ratio of principal curvatures. These surfaces are a natural generalization of minimal surfaces, and can be constructed by applying a Christoffel-type transformation to appropriate spherical curvature line parametrizations, both in the smooth setting and in a discretization with principal nets. We link this Christoffel-type transformation to the discrete curvature theory for parallel meshes and characterize nets that admit these transformations. In the case of negative curvature, we also present a discretization of asymptotic nets. This case is suitable for design and computation, and forms the basis for a special type of architectural support structures, which can be built by bending flat rectangular strips of inextensible material, such as sheet metal.
  • Assessment of CO2 Injectivity During Sequestration in Depleted Gas Reservoirs

    Hoteit, Hussein; Fahs, Marwan; Soltanian, Mohamad Reza (Geosciences, MDPI AG, 2019-05-09) [Article]
    Depleted gas reservoirs are appealing targets for carbon dioxide (CO 2 ) sequestration because of their storage capacity, proven seal, reservoir characterization knowledge, existing infrastructure, and potential for enhanced gas recovery. Low abandonment pressure in the reservoir provides additional voidage-replacement potential for CO 2 and allows for a low surface pump pressure during the early period of injection. However, the injection process poses several challenges. This work aims to raise awareness of key operational challenges related to CO 2 injection in low-pressure reservoirs and to provide a new approach to assessing the phase behavior of CO 2 within the wellbore. When the reservoir pressure is below the CO 2 bubble-point pressure, and CO 2 is injected in its liquid or supercritical state, CO 2 will vaporize and expand within the well-tubing or in the near-wellbore region of the reservoir. This phenomenon is associated with several flow assurance problems. For instance, when CO 2 transitions from the dense-state to the gas-state, CO 2 density drops sharply, affecting the wellhead pressure control and the pressure response at the well bottom-hole. As CO 2 expands with a lower phase viscosity, the flow velocity increases abruptly, possibly causing erosion and cavitation in the flowlines. Furthermore, CO 2 expansion is associated with the Joule–Thomson (IJ) effect, which may result in dry ice or hydrate formation and therefore may reduce CO 2 injectivity. Understanding the transient multiphase phase flow behavior of CO 2 within the wellbore is crucial for appropriate well design and operational risk assessment. The commonly used approach analyzes the flow in the wellbore without taking into consideration the transient pressure response of the reservoir, which predicts an unrealistic pressure gap at the wellhead. This pressure gap is related to the phase transition of CO 2 from its dense state to the gas state. In this work, a new coupled approach is introduced to address the phase behavior of CO 2 within the wellbore under different operational conditions. The proposed approach integrates the flow within both the wellbore and the reservoir at the transient state and therefore resolves the pressure gap issue. Finally, the energy costs associated with a mitigation process that involves CO 2 heating at the wellhead are assessed.

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