The effect of severalkey factors on the mechanical properties of multilayer polymer filmsundertensile and sheardeformations was thoroughly investigated using atomistic molecular dynamics simulations. These factors included the composition of the layers, the compatibility of polymers in the layers, the crystallinity of polymers, and the thickness of the layers, especially when it decreases to values close to the radius of gyration (Rg) of the polymers. Three types of multilayer systems were considered: polylactide/poly(3-hydroxybutyrate) (PLA/PHB) based on polymers compatible for the selected chain lengths, polylactide/polyethylene (PLA/PE) with incompatible polymers in layers, and polylactide/polylactide (PLA/PLA). It was shown that reducing thelayerthickness to the value close to Rg led to an increase in Young’s modulus for both types of systems with compatible polymers in layers PLA/PHB and with incompatiblepolymers PLA/PE. This effect was found for the systems composed of amorphous polymers. The influence of the layer thickness on shear modulus, yield stress under tensile and shear deformations was also analyzed. Young’s modulus and yield stress under tensile deformation were in line with the “rule of mixture” for all types of the systems. Both the shear modulus and yield stress under shear for PLA/PE tended to the values for bulk PE. Analysis of local atomic shear strain was employed to quantify local plastic deformations at the atomic level during the shear deformation. The pattern of local atomic shear strain distribution for the PLA/PHB and PLA/PLA systems was found to be significantly different from that for PLA/PE.

The manufacture of nanocomposite materials based on polyolefins and paraffins is a promising approach for developing materials with enhanced performance characteristics for a wide range of applications. However, a more profound understanding is required to identify how the material properties depend on the type of filler and its concentration, as well as on the structure of the composite matrix. In this study, the effect of adding several types of polycyclic aromatic hydrocarbons (PAH) with different molecular sizes-coronene, ovalene, and hexabenzocoronene (HBC) at concentrations ranging from 10 to 40 wt%-to composites based on polyethylene (PE) or paraffin was studied using all-atomistic computer simulation. Our study revealed how the size of the PAH molecules influences their aggregate behavior, phase transitions, and the structure of the composite matrix. It was shown that coronene exhibits weak aggregation in paraffin and prevents its crystallization, which results in a pronounced decrease in the crystallization temperature of both PE and paraffin in the composites. Ovalene and HBC demonstrate a stronger tendency to aggregate, forming substantially larger aggregates than coronene. Both these PAHs increase the crystallization temperature of PE or paraffin in the composites. At the same time, up to a certain concentration, ovalene can integrate into the paraffin crystal structure at low temperature, promoting its crystallization. In contrast, HBC forms extended columnar aggregates at both high and low temperatures, creating steric hindrances to the formation of the crystalline matrix structure and ultimately reducing the degree of crystallinity of PE or paraffin in the composites. Thus, by adding aromatic nanofillers, it becomes possible to control the microstructure and phase behavior of polyolefin-based composites.

In this study, we have conducted a comparative analysis of the structural ordering of short oligoetherimide chains (dimers) near the bounding surface, depending on the structure of that surface. In order to clarify the possibility of oligoetherimide ordering along the symmetry axes of graphene, two types of bounding surfaces were considered: graphene, with a regular discrete position of interaction centers (carbon atoms), and a smooth, structureless impermeable wall. The chemical structures of the considered dimers consist of two repeating units of BPDA-P3, ODPA-P3, or aBPDA-P3 thermoplastic polyetherimides. Using all-atom molecular dynamics simulations, the process of structural ordering of the dimers near the surface of the graphene or wall was established. The ODPA-P3 and BPDA-P3 dimers form an ordered state near the graphene surface, while the aBPDA-P3 dimers do not demonstrate structural ordering. The simulation results confirmed that the ordering direction of the BPDA-P3 and ODPA-P3 dimers near the graphene surface is chosen randomly. Comparison of the oligoetherimide structure formed near the attracting wall without a symmetrical location of the interaction centers shows the similarity of the ordering of dimers near the graphene surface and the wall. As in the case of the graphene surface, the ordering of oligoetherimide molecules near the structureless wall demonstrates one direction of ordering. Therefore, we confirmed that the key factor for the onset of ordering is the presence of a confining surface, rather than the symmetrical arrangement of interaction centers in the substrate structure.

In the present work, we investigate the solubility of various gases (CH4, CO2, O2, N2, and He) in a thermoplastic polyimide R-BAPB at room temperature by means of extensive molecular dynamics (MD) simulations, focusing on the effects of thermal prehistory during cooling of polymer melts with different cooling velocities. We show that the cooling velocity employed in MD simulations is an important factor affecting the solubility of gases. Lowering the cooling velocity by 4 orders of magnitude (from 1000 to 0.25 K/ns) reduces the simulated gas solubilities by a factor of 2, with no indication of saturation to steady solubility values. In order to extrapolate the dependence of the gas solubility values to experimental cooling velocities, we use an analytical phenomenological approach based on Struik's theory of isothermal free volume evolution in polymer aging. As a result, we are able to estimate gas solubility values in MD-simulated polymer samples prepared at experimentally relevant cooling velocities. We verify our approach by comparing the direct MD solubility data, the theory-based extrapolation, and the limited experimental data available for R-BAPB polyimide. For additional verification, we extend our approach to ULTEM polyimide, which is much better studied experimentally. We show that the theory-based extrapolation considerably improves the correspondence between modeling and experiment in the case of ULTEM. By combining extensive all-atom MD simulations with an analytical theory, we capture the effects of thermal history on the observed physical properties (specific volume and solubility of gases) and provide the means to bridge a huge gap between the experimental and computational time domains.

INTRODUCTION:Multicolor flow cytometry (MFC) has highly reliable and flexible algorithms for diagnosis and monitoring of acute lymphoblastic leukemia (ALL). However, MFC analysis can be affected by poor sample quality or novel therapeutic options (e.g., targeted therapies and immunotherapy). Therefore, an additional confirmation of MFC data may be needed. We propose a simple approach for validation of MFC findings in ALL by sorting questionable cells and analyzing immunoglobulin/T-cell receptor (IG/TR) gene rearrangements via EuroClonality-based multiplex PCR.PATIENTS AND METHODS:We obtained questionable MFC results for 38 biological samples from 37 patients. In total, 42 cell populations were isolated by flow cell sorting for downstream multiplex PCR. Most of the patients (n = 29) had B-cell precursor ALL and were investigated for measurable residual disease (MRD); 79% of them received CD19-directed therapy (blinatumomab or CAR-T).RESULTS:We established the clonal nature of 40 cell populations (95.2%). By using this technique, we confirmed very low MRD levels (<0.01% MFC-MRD). We also applied it to several ambiguous findings for diagnostic samples, including those with mixed-phenotype acute leukemia, and the results obtained impacted the final diagnosis.CONCLUSION:We have demonstrated possibilities of a combined approach (cell sorting and PCR-based clonality assessment) to validate MFC findings in ALL. The technique is easy to implement in diagnostic and monitoring workflows, as it does not require isolation of a large number of cells and knowledge of individual clonal rearrangements. We believe it provides important information for further treatment.

Asphaltenes represent a novel class of carbon nanofillers that are of potential interest for many applications, including polymer nanocomposites, solar cells, and domestic heat storage devices. In this work, we developed a realistic coarse-grained Martini model that was refined against the thermodynamic data extracted from atomistic simulations. This allowed us to explore the aggregation behavior of thousands of asphaltene molecules in liquid paraffin on a microsecond time scale. Our computational findings show that native asphaltenes with aliphatic side groups form small clusters that are uniformly distributed in paraffin. The chemical modification of asphaltenes via cutting off their aliphatic periphery changes their aggregation behavior: modified asphaltenes form extended stacks whose size increases with asphaltene concentration. At a certain large concentration (44 mol. %), the stacks of modified asphaltenes partly overlap, leading to the formation of large, disordered super-aggregates. Importantly, the size of such super-aggregates increases with the simulation box due to phase separation in the paraffin-asphaltene system. The mobility of native asphaltenes is systematically lower than that of their modified counterparts since the aliphatic side groups mix with paraffin chains, slowing down the diffusion of native asphaltenes. We also show that diffusion coefficients of asphaltenes are not very sensitive to the system size: enlarging the simulation box results in some increase in diffusion coefficients, with the effect being less pronounced at high asphaltene concentrations. Overall, our findings provide valuable insight into the aggregation behavior of asphaltenes on spatial and time scales that are normally beyond the scales accessible for atomistic simulations.

Coextruded multilayer polymer films are promising packaging materials since their architecture and properties can be adjusted while the production technology is environmentally friendly. Here, the effect of layers thickness and polymers compatibility in alternating layers on the structure and thermophysical properties of such films was studied by means of molecular dynamics simulations. The results show that the model films with layers of incompatible polymers polylactide (PLA) and polyethylene (PE) are stable in time and have very low interfacial diffusion depth even when the layers thickness is about several nanometers. Systems with incompatible polymers differ from the systems with compatible ones by the presence of anisotropy in the mobility of polymer atoms. These films also have two glass transition temperatures. Multilayer films based on compatible for the selected chain lengths polymers PLA and poly(3-hydroxybutyrate) (PHB) as well as one-component systems with PLA layers have a single glass transition point. In these films interfacial diffusion depth tends to gradually increase during the simulation. However, even for one-component system with layers thickness of 7.5 nm sufficiently stable structure of the film is formed, while heterogeneous films with PLA and PHB layers reach metastable state during the modeling with almost constant interfacial diffusion depth.

The cells of acute myeloid leukemia are defined by clonal growth and heterogenous immunophenotypes. Chimeric antigen receptors (CARs) commonly recognize molecular targets by single-chain antibody fragments (scFvs) specific to a tumor-associated antigen. However, ScFvs may form aggregates, thus stimulating tonic CAR T-cell activation and reducing CAR T-cell functioning in vivo. Harnessing natural ligands as recognition parts of CARs, specific targeting of membrane receptors can be achieved. Previously, we presented ligand-based Flt3-CAR T-cells targeting the Flt3 receptor. The extracellular part of Flt3-CAR consisted of full-size Flt3Lg. Meanwhile, upon recognition, Flt3-CAR may potentially activate Flt3, triggering proliferative signaling in blast cells. Moreover, the long-lasting presence of Flt3Lg may lead to Flt3 downregulation. In this paper, we present mutated Flt3Lg-based Flt3m-CAR ('m'-for 'mutant') T-cells targeting Flt3. The extracellular part of Flt3m-CAR consists of full-length Flt3Lg-L27P. We have determined that ED50 for recombinant Flt3Lg-L27P produced in CHO cells is at least 10-fold higher than for the wild-type Flt3Lg. We show that the mutation in the recognizing domain of Flt3m-CAR did not affect the specificity of Flt3m-CAR T-cells when compared to Flt3-CAR T-cells. Flt3m-CAR T-cells combine the specificity of ligand-receptor recognition with reduced Flt3Lg-L27P bioactivity, leading to potentially safer immunotherapy.

Atomistic computer simulations suggest that asphaltenes with enlarged aromatic cores can improve the performance of heat storage devices based on organic phase change materials.

Mixed-phenotype acute leukemia (MPAL), a rare and heterogeneous category of acute leukemia, is characterized by cross-lineage antigen expression. Leukemic blasts in MPAL can be represented either by one population with multiple markers of different lineages or by several single-lineage populations. In some cases, a major blast population may coexist with a smaller population that has minor immunophenotypic abnormalities and may be missed even by an experienced pathologist. To avoid misdiagnosis, we suggest sorting doubtful populations and leukemic blasts and searching for similar genetic aberrations. Using this approach, we examined questionable monocytic populations in five patients with dominant leukemic populations of B-lymphoblastic origin. Cell populations were isolated either for fluorescence in situ hybridization or for clonality assessment by multiplex PCR or next-generation sequencing. In all cases, monocytic cells shared the same gene rearrangements with dominant leukemic populations, unequivocally confirming the same leukemic origin. This approach is able to identify implicit cases of MPAL and therefore leads to the necessary clinical management for patients.

In the present work, we address the problem of utilizing machine learning (ML) methods to predict the thermal properties of polymers by establishing “structure–property” relationships. Having focused on a particular class of heterocyclic polymers, namely polyimides (PIs), we developed a graph convolutional neural network (GCNN), being one of the most promising tools for working with big data, to predict the PI glass transition temperature Tg as an example of the fundamental property of polymers. To train the GCNN, we propose an original methodology based on using a “transfer learning” approach with an enormous “synthetic” data set for pretraining and a small experimental data set for its fine-tuning. The “synthetic” data set contains more than 6 million combinatorically generated repeating units of PIs and theoretical values of their Tg values calculated using the well-established Askadskii’s quantitative structure–property relationship (QSPR) computational scheme. Additionally, an experimental data set for 214 PIs was also collected from the literature for training, fine-tuning, and validation of the GCNN. Both “synthetic” and experimental data sets are included into a PolyAskInG database (Polymer Askadskii’s Intelligent Gateway). By using the PolyAskInG database, we developed GCNN which allows estimation of Tg of PI with a mean absolute error (MAE) of about 20 K, which is 1.5 times lower than in the case of Askadskii QSPR analysis (33 K). To prove the efficiency and usability of the proposed GCNN architecture and training methodology for predicting polymer properties, we also employed “transfer learning” to develop alternative GCNN pretrained on proxy-characteristics taken from the popular quantum-chemical QM9 database for small compounds and fine-tuned on an experimental Tg values data set from PolyAskInG database. The obtained results indicate that pretraining of GCNN on the “synthetic” polymer data set provides MAE which is almost twice as low as that in the case of using the QM9 data set in the pretraining stage (∼41 K). Furthermore, we address the questions associated with the influence of the differences in the size of the experimental and “synthetic” data sets (so-called “reality gap” problem), as well as their chemical composition on the training quality. Our results state the overall priority of using polymer data sets for developing deep neural networks, and GCNN in particular, for efficient prediction of polymer properties. Moreover, our work opens up a challenge for the theoretically supported generation of large “synthetic” data sets of polymer properties for the training of the complex ML models. The proposed methodology is rather versatile and may be generalized for predicting other properties of different polymers and copolymers synthesized through the polycondensation reaction.

Adding carbon nanoparticles into organic phase change materials (PCMs) such as paraffin is a common way to enhance their thermal conductivity and to improve the efficiency of heat storage devices. However, the sedimentation stability of such blends can be low due to aggregation of aromatic carbon nanoparticles in the aliphatic paraffin environment. In this paper, we explore whether this important issue can be resolved by the introduction of a polymer agent such as poly(3-hexylthiophene) (P3HT) into the paraffin-nanoparticle blends: P3HT could ensure the compatibility of aromatic carbon nanoparticles with aliphatic paraffin chains. We employed a combination of experimental and computational approaches to determine the impact of P3HT addition on the properties of organic PCMs composed of paraffin and carbon nanoparticles (asphaltenes). Our findings clearly show an increase in the sedimentation stability of paraffin-asphaltene blends, when P3HT is added, through a decrease in average size of asphaltene aggregates as well as in an increase of the blends' viscosity. We also witness the appearance of the yield strength and gel-like behavior of the mixtures. At the same time, the presence of P3HT in the blends has almost no effect on their thermophysical properties. This implies that all properties of the blends, which are critical for heat storage applications, are well preserved. Thus, we demonstrated that adding polyalkylthiophenes to paraffin-asphaltene mixtures led to significant improvement in the performance characteristics of these systems. Therefore, the polymer additives can serve as promising compatibilizers for organic PCMs composed of paraffins and asphaltenes and other types of carbon nanoparticles.

Recently, a strong structural ordering of thermoplastic semi-crystalline polyimides near single-walled carbon nanotubes (SWCNTs) was found that can enhance their mechanical properties. In this study, a comparative analysis of the results of microsecond-scale all-atom computer simulations and experimental measurements of thermoplastic semi-crystalline polyimide R-BAPB synthesized on the basis of dianhydride R (1,3-bis-(3′,4-dicarboxyphenoxy) benzene) and diamine BAPB (4,4′-bis-(4″-aminophenoxy) biphenyl) near the SWCNTs on the rheological properties of nanocomposites was performed. We observe the viscosity increase in the SWCNT-filled R-BAPB in the melt state both in computer simulations and experiments. For the first time, it is proven by computer simulation that this viscosity change is related to the structural ordering of the R-BAPB in the vicinity of SWCNT but not to the formation of interchain linkage. Additionally, strong anisotropy of the rheological properties of the R-BAPB near the SWCNT surface was detected due to the polyimide chain orientation. The increase in the viscosity of the polymer in the viscous-flow state and an increase in the values of the mechanical characteristics (Young’s modulus and yield peak) of the SWCNT-R-BAPB nanocomposites in the glassy state are stronger in the directions along the ordering of polymer chains close to the carbon nanofiller surface. Thus, the new experimental data obtained on the R-BAPB-based nanocomposites filled with SWCNT, being extensively compared with simulation results, confirm the idea of the influence of macromolecular ordering near the carbon nanotube on the mechanical characteristics of the composite material.

Further development and commercialization of bulk heterojunction (BHJ) solar cells require the search for novel low-cost materials. The present study addresses the relations between the asphaltenes’ chemical structure and the morphology of the poly(3-hexylthiohene) (P3HT)/asphaltene blends as potential materials for the design of BHJ solar cells. By means of all-atom molecular dynamics simulations, the formation of heterophase morphology is observed for the P3HT-based blends with carboxyl-containing asphaltenes, as well as the aggregation of the asphaltenes into highly ordered stacks. Although the π–π interactions between the polyaromatic cores of the asphaltenes in solutions are sufficient for the molecules to aggregate into ordered stacks, in a blend with a conjugated polymer, additional stabilizing factors are required, such as hydrogen bonding between carboxyl groups. It is found that the asphaltenes’ aliphatic side groups may improve significantly the miscibility between the polymer and the asphaltenes, thereby preventing the formation of heterophase morphology. The results also demonstrate that the carboxyl-containing asphaltenes/P3HT ratio should be at least 1:1, as a decrease in concentration of the asphaltenes leads to the folding of the polymer chains, lower ordering in the polymer phase and the destruction of the interpenetrating 3D structure formed by P3HT and the asphaltene phases. Overall, the results of the present study for the first time reveal the aggregation behavior of the asphaltenes of varying chemical structures in P3HT, as well the influence of their presence and concentration on the polymer phase structure and blend morphology, paving the way for future development of BHJ solar cells based on the conjugated polymer/asphaltene blends.

A molecular-level insight into phase transformations is in great demand for many molecular systems. It can be gained through computer simulations in which cooling is applied to a system at a constant rate. However, the impact of the cooling rate on the crystallization process is largely unknown. To this end, here we performed atomic-scale molecular dynamics simulations of organic phase-change materials (paraffins), in which the cooling rate was varied over four orders of magnitude. Our computational results clearly show that a certain threshold (1.2 × 1011 K/min) in the values of cooling rates exists. When cooling is slower than the threshold, the simulations qualitatively reproduce an experimentally observed abrupt change in the temperature dependence of the density, enthalpy, and thermal conductivity of paraffins upon crystallization. Beyond this threshold, when cooling is too fast, the paraffin’s properties in simulations start to deviate considerably from experimental data: the faster the cooling, the larger part of the system is trapped in the supercooled liquid state. Thus, a proper choice of a cooling rate is of tremendous importance in computer simulations of organic phase-change materials, which are of great promise for use in domestic heat storage devices.

Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications, such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can predict and reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.

Основная проблема современной полимерной науки — поиск путей дальнейшего развития полимерной цивилизации, к которой, несомненно, относятся живые организмы на Земле, без вредных последствий для этой самой цивилизации и планеты в целом. В обзоре рассмотрены подходы к решению проблемы накопления полимерных отходов в окружающей среде, а также обсуждены перспективные направления развития полимерных технологий, способных существенно сократить образование таких отходов. Отдельные разделы посвящены оригинальным методам аддитивных технологий, таким как экструдерные технологии печати мультислоевых пленок, 3D-печать высокотемпературными полиимидными материалами, новыми функциональными силоксановыми олигомерами, гидрогелями медицинского назначения. Значительное место уделено проблемам развития и применения биоразлагаемых материалов в медицине, упаковочной индустрии, сельском хозяйстве. Анализ европейского подхода к утилизации полимерных отходов показал его ограниченную применимость из-за высоких энергозатрат и нарушения углеродного баланса планеты. Изложены тезисы современного подхода к утилизации полимерного мусора, свободного от перечисленных недостатков. Библиография — 1233 ссылки.

Relapsed/refractory acute myeloid leukemia (AML) cannot be cured with chemotherapy alone, as the blasts survive the treatment. Chimeric antigen receptor (CAR) approaches for AML are being actively developed. CARs promote immune reactions through recognition of the target molecular epitopes at the surface of cancer cells. The recognition involves the extracellular portion of the CAR protein, which corresponds to either the antibody or the physiological binding partner of the targeted antigen. Here, we design a chimeric receptor with a full-length natural Flt3-ligand recognition module that targets Flt3 tyrosine kinase, known as an adverse marker in AML. We demonstrate specific killing of Flt3-positive THP-1 cells by Flt3-CAR T cells and the lack of cytotoxicity towards Flt3-negative U937 cells. We prove that the inherent cytolytic capacity of T cells is essential for the killing. Finally, we confirm the authenticity of targeting by its competitive dose-dependent inhibition with a soluble Flt3-ligand. The developed system can be viewed as a non-immunogenic functional equivalent of scFv-mediated targeting. The robust in vitro antitumor effects of Flt3-CAR T cells, combined with their low off-target cytotoxicity, hold promise for AML treatment.

An accurate in silico evaluation of the thermal conductivity is critical for improving the thermal properties of organic phase-change materials on a rational basis. To explore the impact of a theoretical model on the computed thermal conductivity, here we employed the equilibrium and the non-equilibrium molecular dynamics (MD) simulations to study paraffin (n-eicosane) bulk samples, in both crystalline and liquid states, with the use of 10 atomistic force fields, both all-atom and united-atom ones. Overall, we found that the equilibrium MD method is preferable for computing the thermal conductivity of n-eicosane samples (at least for a 10-nm-size simulation box). For the n-eicosane crystals, the all-atom models provide larger thermal conductivity coefficients than their united-atom counterparts and, correspondingly, a better match with the experimental data. This is most likely because the crystalline lattice of the models with explicit hydrogen atoms is additionally stabilized by the electrostatic interactions. In contrast, in the liquid state, most all-atom models overestimate the experimental data for n-eicosane, providing thereby worse performance as compared to the united-atom force fields. However, when it comes to the experimentally observed increase in the thermal conductivity of n-eicosane samples upon crystallization, only all-atom models are able to reproduce quantitatively the experimental data. Each force field of n-eicosane was also characterized by an overall score which accumulated the deviations of the computed thermal conductivity coefficients from the experimental values, for both crystalline and liquid samples. It turns out that the best performance among 10 atomistic models of n-eicosane is observed for the all-atom GAFF force field. All in all, our study clearly demonstrates that a proper choice of the model for computing the thermal conductivity is a non-trivial task: even for such relatively simple compounds as paraffins (n-alkanes), different models perform quite differently, in equilibrium and in non-equilibrium MD simulations, as well as in crystalline and liquid phases.

The practical use of paraffin and other organic phase-change materials for heat storage is largely limited by their low thermal conductivity. In this paper we employed 60 microsecond-long atomic-scale computer simulations to explore for the first time whether the asphaltenes, natural polycyclic aromatic hydrocarbons, can be used as thermal conductivity enhancers for paraffin. We focused on a simple model molecule of asphaltene (a polycyclic aromatic core decorated with the peripheral alkane chains) and showed that the asphaltenes of such molecular architecture are not able to improve the thermal conductivity of paraffin. This is most likely due to the steric constraints imposed by the peripheral alkane groups, which prevent formation of the extended ordered asphaltene aggregates. To overcome this, we proposed a possible chemical modification of the asphaltene molecules through removing the peripheral alkane groups from their aromatic cores; this could be achieved e.g. by thermal cracking (dealkylation) of asphaltenes. It turns out that such a chemical modification drastically changes the situation: the modified asphaltenes form extended columnar aggregates which can serve as thermal conduction paths, considerably enhancing the thermal conductivity of a liquid composite sample. This effect, however, vanishes upon cooling because the columnar extended stacks of chemically modified asphaltenes transform into the helical twisted structures, which reduces the overlap of adjacent asphaltenes in aggregates. Importantly, all the simulations have been carried out with two different all-atom force fields. We have demonstrated that both computational models give qualitatively similar results. Overall, our findings clearly show that chemically modified asphaltene molecules can be considered as promising carbon based thermal conductivity enhancers for liquid paraffin; this result can be used for optimizing the paraffin-based thermal energy storage systems. (c) 2021 Elsevier B.V. All rights reserved.