FY 2025-2026

• L.  Akerkouch and T. Le, Shape Transitions of Red Blood Cell under Oscillatory Flows in Microchannels, AIP Advances 1 15, 085010 (2025).

• C. M. Adhikari, D. Thapa, T. D. Alexander, C. K. Addaman, S. Han, B. P. Bastakoti, D. E. Autrey, S. Kilina, B. K. Rai, and B. R. Gautam, Confinement of quasi-atomic structures in Ti₂N and Ti₃N₂ MXene Electrides, Journal of Physics and Chemistry of Solids 212, 113534 (2026).

• H. B. Griffin and A. Kryjevski, Phonon-mediated relaxation in nanomaterials using Boltzmann transport equation by combining density functional theory based non-adiabatic molecular dynamics with many-body perturbation theory, Journal of Chemical Physics 163, 134110 (2025).

• A. Nyporko, I. Voiteshenko, M. Zarudnaya, V. Hurmach, T. Shyryna, M. Platonov, S. Roszak, B. Rasulev, and L. Gorb, SARS-CoV‑2 RNA’s Dual Identity: G‑Quadruplex versus Hairpin, ACS Omega 10, 29408–29420 (2025).

• K. Diéguez-Santana, G. M. Casanola-Martin, R. Torres-Gutiérrez, B. Rasulev, and H. González-Díaz, AQUA Tox: A web tool for predicting aquatic toxicity in rotifer species using intrinsic explainable models, Journal of Hazardous Materials 492,138050 (2025).

• D. Usmanov, U. Yusupova, V. Syrov, G. M. Casanola-Martin, and B. Rasulev, A Quantitative Structure–Activity Relationship Study of the Anabolic Activity of Ecdysteroids, Computation 13, 195 (2025).

• J. Kayumov, D. Usmanov, U. Yusupova, Z. Smanova, and B. Rasulev, Exploring Chemistry in Virtual Reality: A Comparative Analysis of VR Simulations for Chemistry Education, Applied Sciences 15, 13254 (2025).

• S. Shirvanihosseini, J. M. Rodríguez-Díaz, G. M. Casanola-Martin, B. Rasulev, Machine learning based assessment of the toxicity of polymeric materials to green algae as an approach to design non-toxic polymeric coatings to deter marine biofouling, Results in Chemistry 20, 103005 (2026).

• T. Nguyen, D. Q. Quy, N. T. Tung, N. T Huyen, P. L. Minh, N. T. M. Huyen, T. Ho, N. T. T.  Ha, G. M. Casanola-Martin, B. Rasulev, and H. Pham-The, Beyond α-Glucosidase and α-Amylase Inhibition: Integrated In Vitro and Multi-Scale In Silico Insights into the Antidiabetic and Antioxidant Mechanisms of Oxalis corniculata L. Aerial Parts, Molecules 31, 630 (2026).

• M. Zarudnaya, I. Voiteshenko, V. Hurmah, T. Shyryna, A. Nyporko, M. Platonov, S. Roszak, B. Rasulev, K. Kapusta, and L. Gorb, In Search of the Most Significant Potential G-Quadruplexes in SARS-CoV-2 RNA: Genomic Analysis, Viruses 18, 253 (2026).

• K. N. Keya, A. Daghighi, G. M. Casanola-Martin, W. Xia, and B. Rasulev, Comparative evaluation of machine Learning-based QSPR techniques for predicting polymer glass transition temperature, Discover Materials 6, 154 (2026).

• J. L. Rodriguez, E. Ascencio, J. M. Ageitos, L. Feijoo, S. He, A. Daghighi, G. M. Casanola-Martin, C. R. Munteanu, S. R. Yañez, A. Pazos, H. Bediaga, B. D. Ordiales, R. Esteban, A. Heres, J. C. Yuste, L. Epelde, B. Rasulev, T. Gonzalez, S. Arrasate, and H. González-Diaz, Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence-Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study, Advanced Intelligent Systems 8, e202500587 (2026).

• D. Usmanov, P. Yadav, G. M. Casanola-Martin, A. S. Mallya, S. Shirvanihosseini, A. Hubel, and B. Rasulev, Machine learning framework to predict glass transition temperature in natural deep eutectic solvents: a step toward green functional materials, Green Chemistry 28, 9650–9666 (2026).

• J. R. White, J. P. McNellie, K. G. Keepers, B. C. Smart, Z. M. Portlas, Z. E. Marcus, N. C. Kane, J. R. Prasifka, and B. S. Hulke, Understanding genetic architecture overcomes tradeoffs between seed quality and insect resistance, Theoretical and Applied Genetics 138, 173 (2025).

• N. F. Khan, L. Liu, L. Bierscheid, J. C. Wilkinson, and C. Yan, Leveraging Vision Transformers for High-Precision Classification of Cancer Cell Cultures: A Comparative Study on MDA-MB-231 and PC3 Datasets, IEEE Open Journal of Engineering in Medicine and Biology 7, 70-78 (2026).

• G. Tiffany, A. Arshad, B. M. Weight, A. Amb, A. Forde, B. J. Gifford, A. Star, S. Tretiak, D. Kilin, and S. Kilina, Inducing Circular Dichroism in Carbon Nanotubes by Chemical Defects, ACS Nano 19, 30476–30486 (2025).

• G. Tiffany, B. M. Weight, B. J. Gifford, A. Arshad, A. Forde, D. Kilin, S. Kilina, and S. Tretiak, Collective Effect of Color-Centers on Chiroptical Response of Carbon Nanotubes, ChemRxiv (2026).

• D. Thapa, Y. Han, B. M. Weight, G. Tiffany, D. Kilin, S. Tretiak, and S. Kilina, Singlet and triplet excitations in chemically functionalized single-walled carbon nanotubes, Journal of Material Chemistry C 14, 4482–4495 (2026).

• S. S. Piletsky, E. E. Keblish, A. R. Goffin, X. Jin, I. Hwang, A. Amb, D. Kilin, S. Kilina, M. Zheng, M. Kim, and D. A. Heller, Handle-free attachment of small molecules on single-walled carbon nanotubes, Nature Synthesis (2026).

• B. M. Weight, G. Tiffany, B. J. Gifford, S. Kilina, D. Kilin, A. Forde, and S. Tretiak, Influence of Color-Center Electronegativity on Circular Dichroism in Single-Walled Carbon Nanotubes, ChemRxiv (2026).

• Q. Li, K. R. Amat, and J. Li, LLM-powered personalized glucose prediction in type 1 diabetes, Computational and Structural Biotechnology Reports 2,100068 (2025).

• K. Hoang and M. D. Johannes, Native defects, hydrogen impurities, and metal dopants in CeO2, Physical Review Materials 9, 095801 (2025).

• M. A. Baluk, D. Makowski, A. Pieczyńska, K. Nikiforow, J. Łuczak, A. Mikolajczyk, K. Hoang, N. Pinna, and A. Zaleska-Medynska, Effects of copper, cobalt, or nickel modification of NH2-MIL-125 oxide-derivatives on simultaneous photocatalytic pollutant degradation and hydrogen generation from natural seawater, International Journal of Hydrogen Energy 197, 152491 (2026).

• K. Hoang, Hydrogen defects as probes of band alignment in metal–organic frameworks, Materials Horizons 13, 5097–5105 (2026).

• K. Hoang, First-principles characterization of native defects and oxygen impurities in GaAs, Journal of Physics: Condensed Matter 38, 225701 (2026).

• W. J. S. Diniz, A. K. Ward, K. L. McCarthy, C. J. Kassetas, F. Baumgaertner, L. P. Reynolds, P. P. Borowicz, K. K. Sedivec, J. D. Kirsch, S. T. Dorsam, T. L. Neville, J. C. Forcherio, R. Scott, J. S. Caton, and C. R. Dahlen, Nutrient-sensing and developmental pathways in fetal brain and muscle are modulated by maternal nutrition during early gestation in beef cattle, Animal Nutriomics 3, e17 (2026).

• G.D. Ramírez-Zamudio, W. J. S. Diniz, F. Baumgaertner, A. C. B. Menezes, J. L. Hurlbert, K. A. Bochantin, S. R. Underdahl, K. L. McCarthy, L. P. Reynolds, A. K. Ward, P. P. Borowicz, K. K. Sedivec, J. S. Caton, and C. R. Dahlen, Effects of maternal early gestational weight gain on skeletal muscle gene expression profile in F1 and F2 beef cattle offspring, Frontiers in Animal Science 6, 1725223 (2026).

• N. Paul, S. GC, J. V. Anderson, J. S. Kandel, A. Ali, M. Rahman, D. Horvath., and X. Sun, Bridging convolution and attention: An ultra-lightweight hybrid model for freeze damage classification in camelina, Smart Agricultural Technology 12, 101396 (2025).

• A. Hoque and M. Rahman, Deciphering the Underlying Genetics of Agronomic Traits Comparing Various Association Mapping Models in a Diversified Flax Collection, Plant Breeding 145, 405–424 (2026).

• H. Navasca, A. Bazrafkan, F. D. Dariva, J. Kim, H. Worral, J. P. Johnson, S. R. Acharya, L. Piche, A. Ross, G. Raymon, Q. Zhang, R. J. McGee, K. McPhee, C. J. Coyne, P. Flores, and N. Bandillo, Improving estimation of days to maturity in field pea using RGB aerial imagery and machine learning, The Plant Phenome Journal 8, e70038 (2025).

• S. R. Acharya, E. Bredu, H. Navasca, H. Worral, L. Piche, R. A. Saludares, J. P. Johnson, C. Coyne, K. McPhee, Q. Zhang, M. Ostlie, and N. Bandillo, Genomic and Transcriptomic Insights Into Salinity Tolerance in Dry Pea, Legume Science 8, e70131 (2026).

• S. D. Pasupuleti and S. A. Ludwig, Feature Selection Method Based on Simultaneous Perturbation Stochastic Approximation Technique Evaluated on Cancer Genome Data Classification, Algorithms 18, 622 (2025).

• J. Souri, B. Koyuncu, L. Chamorro, and T. Le, Lateral momentum transfer in ice-covered rivers, ESS Open Archive (2025).

• R. Dathi, T. Nguyen, I. N. Ahmed, Y. Zhang, H. Pan, Z. Lin, and T. B. Le, On the correlation between particle dynamics and erosion pattern in pipe bends: Insights via numerical simulation, AIP Advances 16, 025007 (2026).

• M. Ahmed, L. Akerkouch, A. Vanyo, A. Haage, and T. B. Le, Impacts of Morphology and Elasticity on Cancer Cell Deformation in Shear-flows, bioRxiv (2026).

• S. A. Tolba, T. Ash, and W. Xia. Ab initio investigations of zwitterionic polymers and their interactions with water and ice, Journal of Materials Chemistry A 13, 39065–39076 (2025).

• T. Ash, S. A. Tolba, and W. Xia, Tuning zwitterionic polymer interactions with water and ice through side-chain engineering, Molecular Systems Design and Engineering 11, 541–551 (2026).

• A. Arshad, S. Mazumdar, J. Goswami, M. Quadir, M. Nadagouda, A. N. Bezbaruah, and W. Xia, Ovalbumin as a PFAS carrier protein in aquatic environments, Cell Reports Physical Science 7 (2026).

• O. Alade, N. F. Khan, and A. Aboah, Enhancing Fisheye Object Detection Using Frequency-Domain Attention and Dual Aggregation Transformer, IEEE Access 13, 144325-144343 (2025).

• P. Saha, M. Yang, and A. Aboah, PixToPix GAN-based field mapping and its implementation for data-driven assessment, Smart Materials and Structures 35, 065041 (2026).

• R. Williamson, N. Dusek, E. Lopez-Echartea, M. K. T. Ramsett, and B. A. Geddes, Evaluation of Engineering Potential in Undomesticated Microbes With VECTOR, Microbial Biotechnology 18, e70215 (2025).

• J. Kilama, D. B. Holman, M. Abbasi, R. G. Amachawadi, T.G. Nagaraja, C. R. Dahlen, and S. Amat, Comparative Genomics of Bovine and Human Fusobacterium necrophorum Strains Reveal Subspecies- and Host-associated Differences in Virulence and Antimicrobial Resistance, bioRxiv (2026).

• M. Galad, N. Sarker, S. Eshkabilov, Z. Lin, and E. Monono, Simulating and optimizing the performance of a pilot scale (115 L) vacuum steam pasteurizer using discrete element method analysis, Food and Bioproducts Processing 156, 92-103 (2026).

• G. Singh, K. Acharya, B. Mumia, S. Ranabhat, E. Ojha, J. Singh, U. Gill, S. Walkowiak, H. S. Chawla, X. Li, J. Faris, Z. Liu, and G. Yan, Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale, Theoretical and Applied Genetics 139 (2026).

• M. Kazim, H. Pirim, C. Le, T. Le, and O. P. Yadav, Edge-level explainable graph neural networks with network centric features for transmission line failure prediction in power grids, Sustainable Energy, Grids and Networks 44, 101969 (2025).

• H. Pirim, Z. Rahman, S. Saei, S. Gyawali, M. Marufuzzaman, N. Tajik, and H. Tekedar, Machine Learning and Network Analysis to Predict Hypothetical Protein Functions of Aeromonas hydrophila, bioRxiv (2025).

• M. Kazim, H. Pirim, C. Le, T. Le, and O. P. Yadav, Multilayer GNN for predictive maintenance and clustering in power grids, iScience 28, (2025).

• A. J. Craner, C. R. Dahlen, J. L. Hurlbert, A. C. B. Menezes, P. Banerjee, F. Baumgaertner, K. A. Bochantin-Winders, S. Amat, K. K. Sedivec, K. C. Swanson, and W. J. S. Diniz, Maternal Vitamin and Mineral Supplementation Affected Neonatal Gene Expression and Rewired Key Regulatory Genes Underlying Hepatic Metabolism, Animals 15, 2664 (2025).

• A. J. Christensen, E. K. Latch, M. Carstensen, and T. Seaborn, Assessing kinship detection: single nucleotide polymorphism array density and estimator comparison in white-tailed deer, G3 Genes|Genomes|Genetics 16, jkag007 (2026).

• R. Hall, M. A. Alston, J. P. Harmon, C. R. V. Otto, and T. Seaborn, Bee-ing similar: low diversity, no population structure, and signals of adaptation in two North Dakota bumble bees, Biodiversity and Conservation 35, 193 (2026).

• J. Singh, S. Gudi, P. J. Maughan, R. Gupta, and U. Gill, Improved reannotations of Aegilops umbellulata (PI 554389) genome and transcriptomics data provide candidates for leaf rust resistance for wheat improvement, Scientific Reports 15, 44930 (2025).

• E. C. Fernandez, G. Tu, W. Dai, S. Yang, Z. Liu, M. Grzybowski, and Z. Liang, Spatial coordination between leaf gradient and temperature response in barley, The Plant Journal 126, e70857 (2026).

• W. Ding, D. Cakir, L. R. Jaishi, J. Yuan, M. Anas, P. Kharel, B. Yao, and X. Xian, CVD-grown phase-pure V₂C nanosheets with pseudocapacitive behavior for fast and stable lithium-ion storage, Journal of Materials Chemistry A 14, 6392–6402 (2026).

• W. Ding, D. Cakir, M. Wieberdink, Y. Bian, L. R. Jaishi, J. Yuan, M. Anas, P. Kharel, V. Kee, H. Park, S. Jung, and X. Xian, Structural and Electronic Engineering of WSe₂ for High-Performance Gas Sensing, ACS Sensors 11, 4439–4450 (2026).

• F. S. Rad and J. Li, Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework, JMIR Diabetes 10, e72874 (2025).

FY 2024-2025

• B. Kankanamge and D. Çakır, Unveiling the Impact of Substitutional Doping on the Oxidation Behavior of MoAlB: A Comprehensive First-Principles Study, Journal of Physical Chemistry C 128, 19550–19558 (2024).

• S. Lu, L. Wei, and H. Liang, Social Media Policies as Social Control in the Newsroom: A Case Study of the New York Times on Twitter, Journalism Studies 26, 568–586 (2025).

• A. J. Craner, C. R. Dahlen, J. L. Hurlbert, A. C. B. Menezes, P. Banerjee, F. Baumgaertner, K. A. Bochantin-Winders, S. Amat, K. K. Sedivec, K. C. Swanson, and W. J. S. Diniz, Early life programming of the neonatal bovine jejunum in response to maternal vitamin and mineral supplementation, Journal of Developmental Origins of Health and Disease 16, e24 (2025).

• R. Tian, L. Zhang, and J. J. Chen, De-risking strategies of defined benefit plans and economic outcome: empirical evidence from U.S. Firms , Applied Economics 57, 9462–9479 (2025).

• S. N. Subhashree, C. Igathinathane,  J. Hendrickson, D. Archer, M. Liebig, J. Halvorson, S. Kronberg, D. Toledo, and K. Sedivec, Evaluating Remote Sensing Resolutions and Machine Learning Methods for Biomass Yield Prediction in Northern Great Plains Pastures, Agriculture 15, 505 (2025).

• J. D. Schumacher, N. Dusek, M. Mendoza-Suárez, and B. A. Geddes, Adaptation of Plasmid-ID Technology for Evaluation of N2-Fixing Effectiveness and Competitiveness for Root Nodulation in the Sinorhizobium–Medicago System, Environmental Microbiology 27, e70118 (2025).

• E. Lopez-Echartea, N. Dusek, M. Misialek, M. A. Mahmud-Un-Nabi, R. Williamson, K. Marathe, and B. A. Geddes, Culturomics from field-grown crop plants using dilution to extinction, two-step library preparation and amplicon sequencing, Microbiology 171 (2025).

• S. A. Tolba, A. Arshad, T. Ash, and W. Xia, Unraveling Polymer–Water Interaction: Ab Initio Insights into Neutral Polymer Hydration, Langmuir 41, 6065–6073 (2025).

• T. Nguyen, D. Kasperski, P. K. Huynh, T. Q. Le, and T. B. Le, Modal analysis of blood flows in saccular aneurysms, Physics of Fluids, 37, 011906 (2025).

• S. A. Ludwig, Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data, Algorithms 18, 220 (2025).

• M. I. Reza, P. Balraj, M. A. Thompson, Y. S. Prakash, C. M. Pabelick, R. D. Britt Jr., and V. Sathish, Asthma and inflammation transcriptionally up-regulate the aryl hydrocarbon receptor in airway smooth muscle via p38/JNK-AP1 signalling, British Journal of Pharmacology 182, 5269–5285 (2025).

• F. D. Dariva, A. Arman, M. Morales, H. Navasca, R. Shah, S. A. Atanda, L. Piche, H. Worral, G. Raymon, K. McPhee, C. Coyne, P. Flores, M. K. Ebert, and N. Bandillo, Identification of novel candidate genes for Ascochyta blight resistance in chickpea, Scientific Reports 14, 31415 (2024)

• S. Hosain, D. P. Horvath, J. Roy, A. Hoque, M. Arifuzzaman, and M. Rahman, Genome-wide association study and genomic prediction for pod-shattering tolerance in a diverse rapeseed/canola germplasm collection, Euphytica 221, 54 (2025).

• J. A. Lackmann, E. P. Fernandez Barrancos, R. A. Zahawi, and L. Aldrich-Wolfe, Restoration plantations accelerate recovery of fungal communities of coarse woody debris in southern Costa Rica, Global Ecology and Conservation 58, e03487 (2025).

• X. Yang and J. Li, A clustering-based federated deep learning approach for enhancing diabetes management with privacy-preserving edge artificial intelligence, Healthcare Analytics 7, (2025).

• Y. Han, T. Vazhappilly, D. A. Micha, and D. S. Kilin, Relaxation of Photoexcited Electron–Hole Pairs at Si(111) Surfaces with Adsorbed Ag Monolayered Clusters of Increasing Size, Journal of Physical Chemistry Letters 16, 2905–2913 (2025).

• N. F. Khan, S. U. Amin, Z. Jan and C. Yan, Detection of Violent Scenes in Cartoon Movies Using a Deep Learning Approach, IEEE Access 12, 154080-154091 (2024).

• J. P. McNellie, W. E. May, L. H. Rieseberg, and B. S. Hulke, Association studies of salinity tolerance in sunflower provide robust breeding and selection strategies under climate change, Theoretical and Applied Genetics 137, 184 (2024).

• L. Wilken, N. Paul, T. Timmerman, S. A. Tolba, A. Arshad, D. Wu, W. Xia, B. Rasulev, R. Jansen, and D. Sun, FAPS: A Fast Platform for Protein Structureomics Analysis, arXiv (2025).

• K. Diéguez-Santana, G. M. Casanola-Martin, R. Torres-Gutiérrez, B. Rasulev, and H. González-Díaz, First report on Quantitative Structure-Toxicity Relationship modeling approaches for the prediction of acute toxicity of various organic chemicals against rotifer species, Science of The Total Environment 977, 179350 (2025).

• G. M Casanola-Martin, G. Tiffany, O. Eniodunmo, T. Oas, M. Jabed, W. Sun, D. Kilin, S. Kilina, and B. Rasulev, Accelerating the Design of Cu(I) Complexes with Near-Infrared Absorption by Interpretable Machine Learning Approaches, ChemRxiv (2025).

• R. A. Mahini, G. M. Casanola-Martin, S. Szwiec, S. A. Ludwig, and B. Rasulev, CombinatorixPy: Advancing mixture descriptors for computational chemistry, SoftwareX 29, (2025).

• M. Zamani, G. M. Casanola-Martin, and B. Rasulev, Machine Learning-based QSAR Modeling of α-Amylase Inhibitors as Potential Antidiabetic Agents, Preprints, 2025041159 (2025).

• R. A. Mahini, M. Safaripour, A. Khanam, G. M. Casanola-Martin, D. C. Webster, S. A. Ludwig, and B. Rasulev, Mixture-Based Machine Learning Analysis to Predict Fouling Release Using Insights from Newly Developed Mixture Descriptors, Preprints, 2024122487 (2024).

• K. Iduoku, M. Ngongang, J. Kulathunga, A. Daghighi, G. Casanola-Martin, S. Simsek, and B. Rasulev, Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study, Foods 13, 2147 (2024).

• D. Thapa, S. Westra, V. Oas, D. Kilin, and S. Kilina, Tunable magnetic order in Fe-Mg co-doped montmoril- lonite nano-clay interfaced with amino acids, ACS Omega 10, 2539–2552 (2025).

• A. Navasca, J. Singh, V. Rivera-Varas, U. Gill, G. Secor, and T. Baldwin, Dispensable genome and segmental duplications drive the genome plasticity in Fusarium solani, Frontiers in Fungal Biology 6, 1432339 (2025).

• J. Singh, S. Gudi, P. J. Maughan, Z. Liu, J. Kolmer, M. Wang, X. Chen, M. N. Rouse, P. Lasserre-Zuber, H. Rimbert, S. Sehgal, J. D. Fiedler, F. Choulet,  M. Acevedo, R. Gupta, and U. Gill, Genomes of Aegilops umbellulata provide new insights into unique structural variations and genetic diversity in the U-genome for wheat improvement, Plant Biotechnology Journal 22, 3505-3519 (2024).

• R. A. Saludares, S. A. Atanda, L. Piche, H. Worral, F. Dariva, K. McPhee, and N. Bandillo, Multi-trait multi-environment genomic prediction of preliminary yield trial in pulse crop, The Plant Genome 17, e20496 (2024).

• J. P. Johnson, L. Piche, H. Worral, S. A. Atanda, C. J. Coyne, R. J. McGee, K. McPhee, and N. Bandillo, Effective population size in field pea, BMC Genomics 25, 695 (2024).

• H. M. N. Faisal, H. K. Gaikwad, K. S. Katti, and D. R. Katti, In-silico investigation of mechanical behavior of hydrated Na-montmorillonite tactoid, Colloids and Surfaces A: Physicochemical and Engineering Aspects 694, 134117 (2024).

• B. Koyuncu, L. Akerkouch, and T. Le, On the depth-averaged models of ice-covered flows, Environmental Fluid Mechanics 24, 1263–1289 (2024).

• H. Qu, Y. Han, J. Fortner, X. Wu, S. Kilina, D. Kilin, S. Tretiak, and Y. Wang, [2 + 2] Cycloaddition Produces Divalent Organic Color-Centers with Reduced Heterogeneity in Single-Walled Carbon Nanotubes, Journal of the American Chemical Society 146, 23582–23590 (2024).

• B. Samanta, E. M. D. Siriwardane, and D. Çakır, Ab initio prediction of phase stability of quaternary Mo_1−xM_xAlB (M = Cr, Fe, Mn, Nb, Sc, Ta, Ti, V, and W) MAB sd solutions, Journal of Applied Physics 136, 65104 (2024).

• P. Ray, A. Sedigh, M. Confeld, L. Alhalhooly, K. Iduoku, G. M. Casanola-Martin, H. Pham-The, B. Rasulev, Y. Choi, Z. Yang, a. Mallik and M. Quadir, Design and evaluation of nanoscale materials with programmed responsivity towards epigenetic enzymes, Journal of Materials Chemistry B 12, 9905–9920 (2024).

• S. He, K. Nader, J. S. Abarrategi, H. Bediaga, D. Nocedo-Mena, E. Ascencio, G. M. Casanola-Martin, I. Castellanos-Rubio, M. Insausti, B. Rasulev, S. Arrasate and H. González-Díaz, NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study, Journal of Nanobiotechnology 22, 1–19 (2024).

• A. Karuth, S. Szwiec, G. M. Casanola-Martin, A. Khanam, M. Safaripour, D. Boucher, W. Xia, D. C. Webster, and B. Rasulev, Integrated machine learning, computational, and experimental investigation of compatibility in oil-modified silicone elastomer coatings, Progress in Organic Coatings 193, 108526 (2024).

• E. Ascencio-Medina, S. He, A. Daghighi, K. Iduoku, G. M. Casanola-Martin, S. Arrasate, H. González-Díaz, and B. Rasulev, Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR), Polymers 16, 2731 (2024).

• T. Shevtsova, K. Iduoku, K. P. Setien, I. Olabode, G. M. Casanola-Martin, B. Rasulev, and A. Voronov, Enhancing Plant Protein-Based Bioplastics with Natural Additives: A Comprehensive Study by Experimental and Computational Approaches, ACS Sustainable Chemistry & Engineering 12, 15948–15960 (2024).

• G. M. Casanola-Martin, A. Karuth, H. Pham-The, H. González-Díaz, D. C. Webster, and B. Rasulev, Machine learning analysis of a large set of homopolymers to predict glass transition temperatures, Communications Chemistry 7, 226 (2024).

• G. M. Casanola-Martin, J. Wang, J. Zhou, B. Rasulev, and J. Leszczynski, Chemical Feature-Based Machine Learning Model for Predicting Photophysical Properties of BODIPY Compounds: Density Functional Theory and Quantitative Structure–Property Relationship Modeling, Journal of Molecular Modeling 31, 18 (2025).

• R. A. Mahini, G. Casanola-Martin, S. A. Ludwig, and B. Rasulev, MixtureMetrics: A comprehensive package to develop additive numerical features to describe complex materials for machine learning modeling, SoftwareX 28, 101911 (2024).

• Y. Asad, K. P. Jangili, A. Arshad, M. Elma, K. Rasuleva, A. Akinlalu, T. Gao, U. R. Tida, W. Xia, and D. Sun, Characterizing biomolecular structure features through an innovative elliptical dichroism spectrometry for cancer detection, Heliyon 10, e38399 (2024).

FY 2023-2024

• Y. Leng, Y. Du, J. Fiedler, S. Haridas, I. V. Grigoriev, and Shaobin Zhong, A Telomere-to-Telomere Genome Assembly Resource of Bipolaris sorokiniana, the Fungal Pathogen Causing Spot Blotch and Common Root Rot Diseases in Barley and Wheat, PhytoFrontiers 4, 247-250 (2024).

• D. Gossweiler, B. C. Smart, and B. S. Hulke, Survival analysis of freezing stress in the North American native perennial flax, Linum lewisii, AoB PLANTS 16, (2024).

• S. Pogoda, K. G. Keepers, S. Reinert, Z. I. Talukder, B. C. Smart, Z. Attia, J. A. Corwin, K. L. Money, E. C. E. Collier-Zans, W. Underwood, T. J. Gulya, C. A. Quandt, N. C. Kane, and B. S. Hulke, Heritable differences in abundance of bacterial rhizosphere taxa are correlated with fungal necrotrophic pathogen resistance, Molecular Ecology 33, e17218 (2024).

• M. A. Morales, H. Worral, L. Piche, A. S. Adeniyi, F. Dariva, C. Ramos, K. Hoang, C. Yan, P. Flores, and N. Bandillo, High-Throughput Phenotyping of Seed Quality Traits Using Imaging and Deep Learning in Dry Pea, bioRxiv (2024).

• K. Kundu, H. K. Gaikwad, S. V. Jaswandkar, P. Ravi, P. Vyas, M. R. Hoffmann, D. Cakir, D. R. Katti, and K. S. Katti, Biomechanically tunable scaffolds for bone tissue regeneration and testbeds of cancer bone metastasis, Materialia 33, 102024 (2024).

• V. O. Jimenez, Y. T. H. Pham, D. Zhou, M. Liu, F. A. Nugera, V. Kalappattil, T. Eggers, K. Hoang, D. L. Duong, M. Terrones, H. Rodriguez Gutiérrez, and M. H. Phan, Transition Metal Dichalcogenides: Making Atomic-Level Magnetism Tunable with Light at Room Temperature, Advanced Science 11, 2304792 (2024).

• M. Weight, B. J. Gifford, G. Tiffany, E. Henderson, D. Mihaylov, D. Kilin, and S. Kilina, Optically active defects in carbon nanotubes via chlorination: computational insights, RSC Applied Interfaces 1, 281–300 (2024).

• Thapa, S. B. Sharma, D. Alfè, D. Kilin, and S. Kilina, Signature of low-dimensional quasi-F centers in zirconium-rich electrides, Materials Horizons 11, 3613–3622 (2024).

• M. Erickson, G. Casañola-Martin, Y. Han, B. Rasulev, and D. Kilin, Relationships between the Photodegradation Reaction Rate and Structural Properties of Polymer Systems, Journal of Physical Chemistry B 128, 2190–2200 (2024).

• Karuth, G. M. Casanola-Martin, L. Lystrom, W. Sun, D. Kilin, S. Kilina, and B. Rasulev, Combined Machine Learning, Computational, and Experimental Analysis of the Iridium(III) Complexes with Red to Near-Infrared Emission, Journal of Physical Chemistry Letters 15, 471–480 (2024).

• R. Graupner and D. S. Kilin, Nonadiabatic Dynamics in Two-Dimensional Perovskites Assisted by Machine Learned Force Fields, Journal of Physical Chemistry C 128, 3935–3944 (2024).

• Fernando, D. Khan, M. R. Hoffmannb, and D. Çakır, Exploring the biointerfaces: ab initio investigation of nano-montmorillonite clay, and its interaction with unnatural amino acids, Physical Chemistry Chemical Physics 25, 29624–29632 (2023).

• S. O. Akande, B. Samanta, C. Sevik, and D. Çakır, First-principles investigation of mechanical and thermal properties of 𝑀AlB (𝑀=Mo,W), Cr₂AlB₂, and Ti₂InB₂, Physics Review Applied 20, 044064 (2023).

• Samanta and D. Çakır, First-Principles Investigation of Oxidation Mechanisms in MoAlB, Journal of Physical Chemistry C 127, 21289–21298 (2023).

• N. Fjodorova, M. Novič, K. Venko, B. Rasulev, M. T. Saçan, G. Tugcu, S. S. Erdem, A. P. Toropova, and A. A. Toropov, Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives, International Journal of Molecular Sciences 24, 14160 (2023).

• Y. Zhuravskyi, K. Iduoku, M. E. Erickson, A. Karuth, D. Usmanov, G. Casanola-Martin, M. N. Sayfiyev, D. A. Ziyaev, Z. Smanova, A. Mikolajczyk, and B. Rasulev, Quantitative Structure─Permittivity Relationship Study of a Series of Polymers, ACS Materials Au 4, 195–203 (2024).

• Khanam, G. Casanola-Martin, A. Daghighi, D. Webster, and B. Rasulev, Development of QSAR Models on the Fouling-Release Performance of Silicone Oil-modified Siloxane Polyurethane Coatings, ChemRxiv (2024).

• Samanta, Y. L. Loh, and D. Çakır, Exploring Doping Effects on Magnetocaloric, Magnetoelastic, and Magnetostriction Properties of Fe₂AlB₂: A First-Principles Study, Journal of Physical Chemistry C 128, 1230–1242 (2024).

• S. O. Akande, B. Samanta, U. Adhikarige, and D. Çakır, Elucidating the Oxidation Mechanisms in Cr2AlB2 Using Density Functional Theory and Thermodynamic Modeling, Journal of Physical Chemistry C 128, 2471–2483 (2024).

• T. Kocabaş, B. Samanta, E. d. S. Barboza, C. Sevik, M. V. Milošević, and D. Çakır, Electron-phonon coupling and thermal conductivity of MAB compounds, Physical Review Materials 8, 055002 (2024).

• Daghighi, G. M. Casanola-Martin, K. Iduoku, H. Kusic, H. González-Díaz, and B. Rasulev, Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling, Environmental Science & Technology 58, 10116–10127 (2024).

• L. Gorb, I. Voiteshenko, V. Hurmach, M. Zarudnaya, A. Nyporko, T. Shyryna, M. Platonov, S. Roszak, and B. Rasulev, From RNA sequence to its three-dimensional structure: geometrical structure, stability and dynamics of selected fragments of SARS-CoV-2 RNA, NAR Genomics and Bioinformatics 6, 62 (2024).

• M. Erickson, D. Vasyutyn, M. Ngongang, A. Daghighi, S. Szwiec, G. Casañola-Martin, and B. Rasulev, In Silico Prediction of the Biodegradability of Chlorinated Com-pounds: Application of Quantitative Structure-Biodegradability Relationship Approach [Preprint], ChemRxiv (2024).

• Y. Wang, S. Zhang, G. Freychet, Z. Li, K.-L. Chen, C.-T. Liu, Z. Cao, Y.-C. Chiu, W. Xia, and X. Gu, Highly deformable rigid glassy conjugated polymeric thin films, Advanced Functional Materials 33, 2306576 (2023).

• Akinlalu, Z. Flaten, K. Rasuleva, M. S. Mia, A. Bauer, S. Elamurugan, N. Ejjigu, S. Maity, A. Arshad, M. Wu, W. Xia, J. Fan, A. Guo, S. Mathew, and D. Sun, Integrated proteomic profiling identifies amino acids selectively cytotoxic to pancreatic cancer cells, The Innovation 5, 100626 (2024).

• M. Meringer, G. M. Casanola-Martin, B. Rasulev, and H. J. Cleaves II, Similarity Analysis of Computer-Generated and Commercial Libraries for Targeted Biocompatible Coded Amino Acid Replacement, International Journal of Molecular Sciences 25, 12343 (2024).

FY 2022-2023

• S. O. Akande and D. Çakır, Defect formation and migration in MAlB (M =Mo, W) and N₂AlB₂ (N=Cr, Fe): A first-principles study, Physical Review Materials 7, 053610 (2023).

• B. Koyuncu and T. B. Le, Modeling shear stress distribution in ice-covered streams, Geological Society of London, Special Publications 540, SP540-2022-161 (2024).

• L. Akerkouch, H. Jasuja, K. Katti, D. Katti, and T. B. Le, The influence of fluid shear stress on bone and cancer cells proliferation and distribution, Annals of Biomedical Engineering 51, 1199 (2023).

• B. Koyuncu and T. B. Le, On the impacts of ice cover on flow profiles in a bend, Water Resources Research 58, e2021WR031742 (2022).

• B. Bakare, D. Motuba, and J. Szmerekovsky, Do corporate social responsibility ratings have any effect on traffic congestion?, Transportation Research Part A: Policy and Practice 165, 98 (2022).

• S. S. Graham, Z. P. Majdik, J. B. Barbour, and J. F. Rousseau, Associations between aggregate NLP-extracted conflicts of interest and adverse events by drug product, Studies in Health Technology and Informatics 290, 405 (2022).

• P. T. Diem-Tran, T.-T. Ho, N.-V. Tuan, L.-Q. Bao, H. T. Phuong, T. T. G. Chau, H. T. B. Minh, C.-T. Nguyen, Z. Smanova, G. M. Casanola-Martin, B. Rasulev, H. Pham-The, and L. C. V. Cuong, Stability constant and potentiometric sensitivity of heavy metal–organic fluorescent compound complexes: QSPR models for prediction and design of novel coumarin-like ligands, Toxics 11, 595 (2023).

• A. Daghighi, G. M. Casanola-Martin, T. Timmerman,  D. Milenković, B. Lucic, and B. Rasulev, In silico prediction of the toxicity of nitroaromatic compounds: Application of ensemble learning QSAR approach, Toxics 10, 746 (2022).

• S. Karabulut, B. Mansour, B. Rasulev, and J. W. Gauld, The hydrolysis rate of paraxonase-1 Q and R isoenzymes: An in silico study based on in vitro data, Molecules 27, 6780 (2022).

• A. Tomić, M. Kovačić, H. Kusic, P. Karamanis, B. Rasulev, and A. L. Božić, Structural features promoting photocatalytic degradation of contaminants of emerging concern: Insights into degradation mechanism employing QSA/PR modeling, Molecules 28, 2443 (2023).

• K. Howlader and Lu Liu, Transfer learning pre-training dataset and fine-tuning effect analysis on cancer histopathology images, 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 3015-3022 (2022).

• R. Alenezi and S. A. Ludwig, Detecting pneumonia based on chest X-ray images using reinforcement learning, IEEE Artificial Intelligence & Knowledge Engineering, Laguna Hills, CA, USA, 67–73 (2022).

• K. Hoang, Defects and persistent luminescence in Eu-doped SrAl₂O₄, Physical Review Applied 19, 024060 (2023).

• Q. Yan, H. Xu, K. Hoang, X. Zhou, P. Kidkhunthod, P. Lightfoot, W. Yao, and Y. Tang, Na₂FeF₄ as a stable cathode material for Na-ion batteries, Applied Physics Letters 121, 143902 (2022).

• K. Hoang, Design of battery materials via defects and doping, in Computational Design of Battery Materials, edited by D. A. H. Hanaor (Springer, 2023).

• S. Ghazanfari, A. Alesadi, Y. Liao, Y. Zhang, and W. Xia, Molecular insights into the temperature and pressure dependence of mechanical behavior and dynamics of Na-montmorillonite clay, Nanoscale Advances 5, 5449–5459 (2023).

• Y. Wang, S. Zhang, G. Freychet, Z. Li, K.-L. Chen, C.-T. Liu, Z. Cao, Y.-C. Chiu, W. Xia, and X. Gu, Highly deformable rigid glassy conjugated polymeric thin films, Advanced Functional Materials 33, 2306576 (2023).

• S. A. Tolba and W. Xia, Molecular insights into the hydration of zwitterionic polymers, Molecular Systems Design and Engineering 8, 1040 (2023).

• Y. Liao, Z. Li, L. Chen, A.B. Croll, and W. Xia, Crumpling defective graphene sheets, Nano Letters 23, 3637 (2023).

• W. M. A. Jayawardana, Y. Liao, Z. Li, W. Xia, and A. Croll, Crumpled kirigami, Soft Matter 19, 1081 (2023).

• S. Gumber, O. Eniodunmo, S. Ivanov, S. Kilina, O. V. Prezhdo, D. Ghosh, and S. Tretiak, Hot carrier relaxation dynamics in non-stoichiometric cdse quantum dots: computational insights, Journal of Materials Chemistry A 11, 8256 (2023).

• B. Liu, X. Yang, M. Jabed, S. Kilina,  Z. Yang, and  W. Sun, Water-soluble dinuclear iridium(III) and ruthenium(II) bis-terdentate complexes: Photophysics and electrochemiluminescence, Dalton Transactions 51, 13858 (2022).

• A. Forde, L.  Lystrom, W. Sun, D. Kilin, and S. Kilina, Improving near-infrared emission of meso-aryldipyrrin indium(iii) complexes via annulation bridging: excited-state dynamics, Journal of Physical Chemistry Letters 13, 9210 (2022).

• Y. Zheng, Y. Han, B. Weight, Z. Lin, B. Gifford, M. Zheng, D. Kilin, S. Kilina, S. Doorn, H. Htoon, and S. Tretiak, Photochemical spin-state control of binding configuration for tailoring organic color center emission in carbon nanotubes, Nature Communications 13, 4439 (2022).

• S. A. Atanda, J. Steffes, Y. lan, M. A. Al Bari, J. Kim, M. Morales, J. P. Johnson, R. Saludares, H. Worral, L. Piche, A. Ross, M. Grusak, C. Coyne, R. McGee, J. Rao, and N. Bandillo, Multi-trait genomic prediction improves selection accuracy for enhancing seed mineral concentrations in pea, The Plant Genome 15, e20260 (2022).

• M. A. Al Bari, D. Fonseka, J. Stenger, K. Zitnick-Anderson, S. A. Atanda, M. Morales, H. Worral, L. Piche, J. Kim, J. Johnson, R. A. Saludares, P. Flores, J. Pasche, and N. Bandillo, A greenhouse-based high-throughput phenotyping platform for identification and genetic dissection of resistance to Aphanomyces root rot in field pea, The Plant Phenome Journal 6, e20063.

• R. Gomes, N. Paul, N. He, A. F. Huber, and R. J. Jansen, Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers, Genes 13, 1557 (2022).

• K. J. Simons, S. Schröder, A. Oladzad, P. E. McClean, R. L. Conner, W. C. Penner, D. B. Stoesz, and J. M Osorno, Modified screening method of middle american dry bean genotypes reveals new genomic regions on Pv10 associated with anthracnose resistance, Frontiers in Plant Science 13, 1015583 (2022).

• W. J. S. Diniz, A. K. Ward, K. L. McCarthy, C. J. Kassetas, F. Baumgaertner, L. P. Reynolds, P. P. Borowicz, K. K. Sedivec, J. D. Kirsch, S. T. Dorsam, T. L. Neville, J. C. Forcherio, R. Scott, J. S. Caton, and C. R. Dahlen, Periconceptual Maternal Nutrition Affects Fetal Liver Programming of Energy- and Lipid-Related Genes, Animals 13, 600 (2023).

• W. J.S. Diniz, A. K. Ward, K. L. McCarthy, C. J. Kassetas, F. Baumgaertner, L. P. Reynolds, P. P. Borowicz, K. K. Sedivec, J. D. Kirsch, S. T. Dorsam, T. L. Neville, J. C. Forcherio, R. Scott, J. S. Caton, and C. R. Dahlen, Dataset of RNA-Seq transcriptome of the fetal liver at day 83 of gestation associated with periconceptual maternal nutrition in beef heifers, Data in Brief 48, 109173 (2023).

FY 2021-2022

• T. B. Le, M. Usta, C. Aidun, A. Yoganathan, and F. Sotiropoulos, Computational methods for fluid-structure interaction simulation of heart valves in patient-specific left heart anatomies, Fluids 7, 94 (2022).

• L. Akerkouch and T. B. Le, A hybrid continuum-particle approach for fluid-structure interaction simulation of red blood cells in fluid flows, Fluids 6, 139 (2021).

• K. Rasuleva, S. Elamurugan, A. Bauer, M. Khan, Q. Wen, Z. Li, P. Steen, A. Guo, W. Xia, S. Mathew, R. Jansen, and D. Sun, Beta-sheet richness of the circulating tumor-derived extracellular vesicles for noninvasive pancreatic cancer screening, ACS Sensors 6, 4489-4498 (2021).

• Z. P. Majdik and J. Wynn, Building better machine learning models for rhetorical analyses: The use of rhetorical feature sets for training artificial neural network models, Technical Communication Quarterly 32, 63-78 (2023).

• K. Hoang, Rare-earth defects in GaN: A systematic investigation of the lanthanide series, Physical Review Materials 6, 044601 (2022).

• K. Hoang, Rare-earth defects and defect-related luminescence in ZnS, Journal of Applied Physics 131, 015705 (2022).

• K. Hoang, C. Latouche, and S. Jobic, Why is it so difficult to realize Dy⁴⁺ in as-synthesized BaZrO₃?, Journal of the American Ceramic Society 105, 4242-4249 (2022).

• W. J. S. Diniz, L. P. Reynolds, A. K. Ward, P. P. Borowicz, K. K. Sedivec, K. L. McCarthy, C. J. Kassetas, F. Baumgaertner, J. D. Kirsch, S. T. Dorsam, T. L. Neville, J. C. Forcherio, R. R. Scott, J. S. Caton, and C. R. Dahlen, Untangling the placentome gene network of beef heifers in early gestation, Genomics 114, 110274 (2022).

• W. J. S. Diniz, G. Bobe, J. Klopfestein, et al., Maternal selenium supplementation during different trimesters of pregnancy: Effects on neonatal calve muscle transcriptome, 12th International Symposium on Selenium in Biology and Medicine, Hawaii, USA (2022).

• W. J. S. Diniz, A. K. Ward, L. P. Reynolds, P. P. Borowicz, K. K. Sedivec, K. L. McCarthy, C. J. Kassetas, F. Baumgaertner, J. D. Kirsch, S. T. Dorsam, T. L. Neville, J. Chris Forcherio, R. Scott, J. Caton, C. R. Dahlen, PSVIII-22 Maternal vitamin and mineral supplementation affect fetal hepatic expression of genes underlying mineral homeostasis and lipid metabolism in early pregnancy, 2021 ASAS Midwest Section Meeting, USA (2021).

• W. J. S. Diniz, G. Bobe, J. J. Klopfenstein, Y. Gultekin, T. Z. Davis, A. K. Ward, and J. A. Hall, Supranutritional maternal organic selenium supplementation during different trimesters of pregnancy affects the muscle gene transcriptome of newborn beef calves in a time-dependent manner, Genes 12, 1844 (2021).

• W. J. S. Diniz, M. S. Crouse, J. S. Caton, K. J. Claycombe-Larson, A. K. Lindholm-Perry, L. P. Reynolds, C. R. Dahlen, P. P. Borowicz, and A. K. Ward, DNA methylation dataset of bovine embryonic fibroblast cells treated with epigenetic modifiers and divergent energy supply, Data in Brief 42, 108074 (2022).

• M. A. Bari, P. Zheng, I. Vieira, H. Worral, S. Szwiec, Y. Ma, D. Main, C. Coyne, R. McGee, and N. Bandillo, Harnessing genetic diversity in the USDA pea germplasm collection through genomic prediction, Frontiers in Genetics 12, 707754 (2021).

• S. V. Jaswandkar, K. S. Katti, and D. R. Katti, Molecular and structural basis of actin filament severing by ADF/cofilin, Computational and Structural Biotechnology Journal 20, 4157-4171 (2022).

• H. M. N. Faisal, K. S. Katti, and D. R. Katti, An insight into quartz mineral interactions with kerogen in Green River oil shale, International Journal of Coal Geology 238, 103729 (2021).

• H. M. N. Faisal, K. S. Katti, and D. R. Katti, Binding of SARS-COV-2 (COVID-19) and SARS-COV to human ACE2: Identifying binding sites and consequences on ACE2 stiffness, Chemical Physics 551, 111353 (2021).

• H. M. N. Faisal, K. S. Katti, and D. R. Katti, Differences in interactions within viral replication complexes of SARS-CoV-2 (COVID-19) and SARS-CoV coronaviruses control RNA replication ability, JOM 73, 1684-1695 (2021).

• H. M. N. Faisal, K. S. Katti, and D. R. Katti, Molecular mechanics of the swelling clay tactoid under compression, tension and shear, Applied Clay Science 200, 105908 (2021).

• S. V. Jaswandkar, H. M. N. Faisal, K. S. Katti, and D. R. Katti, Dissociation mechanisms of G-actin subunits govern deformation response of actin filament, Biomacromolecules 22, 907-917 (2021).

• K. S. Katti, H. Jasuja, S. Kar, and D. R. Katti, Nanostructured biomaterials for in vitro models of bone metastasis cancer, Current Opinion in Biomedical Engineering 17, 100254 (2021).

• M. D. S. Molla, D. R. Katti, and K. S. Katti, Mechanobiological evaluation of prostate cancer metastasis to bone using an in vitro prostate cancer testbed, Journal of Biomechanics 114, 110142 (2021).

• A. B. Croll, Y. Liao, Z. Li, W. M. A. Jayawardana, T. Elder, and W. Xia, Sticky crumpled matter, Matter 5, 1792-1805 (2022).

• A. Alesadi, Z. Cao, Z. Li, S. Zhang, H. Zhao, X. Gu, and W. Xia, Machine learning prediction of glass transition temperature of conjugated polymers from chemical structure, Cell Reports Physical Science 3, 10091 (2022).

• S. Ghazanfari, H. M. N. Faisal, K. S. Katti, D. R. Katti, and W. Xia, A coarse-grained model for the mechanical behavior of Na-montmorillonite clay, Langmuir 38, 4859-4869 (2022).

• N. A. Miller, Z. Li, W. Xia, and C. S. Davis, Buckling mechanics modulus measurement of anisotropic cellulose nanocrystal thin films, ACS Applied Polymer Materials 4, 3045-3053 (2022).

• Y. Liao, Z. Li, W. Nie, and W. Xia, Effect of reconstructed vacancy defects on the crumpling behavior of graphene sheets, Forces in Mechanics 6, 100057 (2022).

• Z. Li, Y. Liao, Y. Zhang, Yida Zhang, and W. Xia, Microstructure and dynamics of nanocellulose films: Insights into the deformational behavior, Extreme Mechanics Letters 50, 101519 (2022).

• Y. Liao, Z. Li, S. Ghazanfari, F. Fatima, A. B. Croll, and W. Xia, Understanding the role of self-adhesion in crumpling behaviors of sheet macromolecules, Langmuir 37, 8627-8637 (2021).

• C. Bulathsinghalage and L. Liu, Transfer learning pre-training dataset effect analysis for breast cancer imaging, Proceedings of 14th International Conference on Bioinformatics and Computational Biology 83, 108-115 (2022).

• C. Bulathsinghalage and L. Liu, A heuristic strategy for multi-mapping reads to enhance Hi-C data, 2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE), 1-6 (2021).

• A. Karuth, A. Alesadi, A. Vashisth, W. Xia, and B. Rasulev, A reactive molecular dynamics study of hygrothermal degradation of crosslinked epoxy polymers, ACS Applied Polymer Materials 4, 4411-4423 (2022).

• G. P. J. Varghese, D. A. David, A. Karuth, F. M. J. Jabeen, P. M. S. Begum, J. J. George, B. Rasulev, and P. Raghavan, Experimental and simulation studies on nonwoven polypropylene-nitrile rubber blend: Recycling of medical face masks to an engineering product,  ACS Omega 7, 4791-4803 (2022).

• N. Fjodorova, M. Novic, K. Venko, V. Drgan, B. Rasulev, M. T. Sacan, S. S. Erdem, G. Tugcu, A. P. Toropova, and A. A. Toropov, How fullerene derivatives (FDs) act on therapeutically important targets associated with diabetic diseases, Computational and Structural Biotechnology Journal 20, 913-924 (2022).