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Open Access Publications from the University of California

This series is home to publications and data sets from the Bourns College of Engineering at the University of California, Riverside.

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Center for Environmental Research and Technology

Cover page of GPU Implementation of a Gas-Phase Chemistry Solver in the CMAQ Chemical Transport Model.

GPU Implementation of a Gas-Phase Chemistry Solver in the CMAQ Chemical Transport Model.

(2025)

The Community Multiscale Air Quality (CMAQ) model simulates atmospheric phenomena, including advection, diffusion, gas-phase chemistry, aerosol physics and chemistry, and cloud processes. Gas-phase chemistry is often a major computational bottleneck due to its representation as large systems of coupled nonlinear stiff differential equations. We leverage the parallel computational performance of graphics processing unit (GPU) hardware to accelerate the numerical integration of these systems in CMAQs CHEM module. Our implementation, dubbed CMAQ-CUDA, in reference to its use in the Compute Unified Device Architecture (CUDA) general purpose GPU (GPGPU) computing solution, migrates CMAQs Rosenbrock solver from Fortran to CUDA Fortran. CMAQ-CUDA accelerates the Rosenbrock solver such that simulations using the chemical mechanisms RACM2, CB6R5, and SAPRC07 require only 51%, 50%, or 35% as much time, respectively, as CMAQv5.4 to complete a chemistry time step. Our results demonstrate that CMAQ is amenable to GPU acceleration and highlight a novel Rosenbrock solver implementation for reducing the computational burden imposed by the CHEM module.

Cover page of Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces.

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces.

(2025)

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

Cover page of Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

(2025)

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

Cover page of Flexibility in PAM recognition expands DNA targeting in xCas9.

Flexibility in PAM recognition expands DNA targeting in xCas9.

(2025)

xCas9 is an evolved variant of the CRISPR-Cas9 genome editing system, engineered to improve specificity and reduce undesired off-target effects. How xCas9 expands the DNA targeting capability of Cas9 by recognising a series of alternative protospacer adjacent motif (PAM) sequences while ignoring others is unknown. Here, we elucidate the molecular mechanism underlying xCas9s expanded PAM recognition and provide critical insights for expanding DNA targeting. We demonstrate that while wild-type Cas9 enforces stringent guanine selection through the rigidity of its interacting arginine dyad, xCas9 introduces flexibility in R1335, enabling selective recognition of specific PAM sequences. This increased flexibility confers a pronounced entropic preference, which also improves recognition of the canonical TGG PAM. Furthermore, xCas9 enhances DNA binding to alternative PAM sequences during the early evolution cycles, while favouring binding to the canonical PAM in the final evolution cycle. This dual functionality highlights how xCas9 broadens PAM recognition and underscores the importance of fine-tuning the flexibility of the PAM-interacting cleft as a key strategy for expanding the DNA targeting potential of CRISPR-Cas systems. These findings deepen our understanding of DNA recognition in xCas9 and may apply to other CRISPR-Cas systems with similar PAM recognition requirements.

Cover page of VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

(2025)

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains. Program summary: Program Title: VAN-DAMME CPC Library link to program files:: https://doi.org/10.17632/zcgw2n5bjf.1 Licensing provisions: GNU General Public License 3 Programming language: C++ and CUDA Nature of problem: The VAN-DAMME software package utilizes GPU-accelerated routines and new algorithmic improvements to compute optimized time-dependent magnetic fields that can drive a system from a known initial qubit configuration to a specified target state with a large (≈1) transition probability. Solution method: Quantum control, GPU acceleration, analytic gradients, matrix exponential, and gradient ascent optimization.

Cover page of Engineering the Ratios of Nanoparticles Dispersed in Triphasic Nanocomposites for Biomedical Applications.

Engineering the Ratios of Nanoparticles Dispersed in Triphasic Nanocomposites for Biomedical Applications.

(2025)

Polymer/ceramic nanocomposites integrated the advantages of both polymers and ceramics for a wide range of biomedical applications, such as bone tissue repair. Here, we reported triphasic poly(lactic-co-glycolic acid) (PLGA, LA/GA = 90:10) nanocomposites with improved dispersion of hydroxyapatite (HA) and magnesium oxide (MgO) nanoparticles using a process that integrated the benefits of ultrasonic energy and dual asymmetric centrifugal mixing. We characterized the microstructure and composition of the nanocomposites and evaluated the effects of the HA/MgO ratios on degradation behavior and cell-material interactions. The PLGA/HA/MgO nanocomposites were composed of 70 wt % PLGA and 30 wt % nanoparticles made of 20:10, 25:5, and 29:1% by weight of HA and MgO, respectively. The results showed that the nanocomposites had a homogeneous nanoparticle distribution and as-designed elemental composition. The cell study indicated that reducing the MgO content in the triphasic nanocomposite increased the BMSC adhesion density under both direct and indirect contact conditions. Specifically, after the 24 and 48 h of culture, the PLGA/HA/MgO group with a weight ratio of 70:29:1 (P70/H29/M1) exhibited the greatest average cell adhesion density under direct and indirect contact conditions among triphasic nanocomposites. During a 28-day degradation study, the mass loss of triphasic nanocomposites was 18 ± 2% for P70/H20/M10, 9 ± 2% for P70/H25/M5, and 7 ± 1% for P70/H29/M1, demonstrating that MgO nanoparticles accelerated the degradation of the nanocomposites. Postculture analysis showed that the pH values and Mg2+ ion concentrations in the media increased with increasing MgO content in the nanocomposites. Triphasic nanocomposites provided different degradation profiles that can be tuned for different biomedical applications, especially when a shorter or longer period of degradation would be desirable for optimal bone tissue regeneration. The concentration and ratio of nanoparticles should be adjusted and optimized when other polymers with different degradation modes and rates are used in the nanocomposites.

Cover page of Food packaging solutions in the post-per- and polyfluoroalkyl substances (PFAS) and microplastics era: A review of functions, materials, and bio-based alternatives.

Food packaging solutions in the post-per- and polyfluoroalkyl substances (PFAS) and microplastics era: A review of functions, materials, and bio-based alternatives.

(2025)

Food packaging (FP) is essential for preserving food quality, safety, and extending shelf-life. However, growing concerns about the environmental and health impacts of conventional packaging materials, particularly per- and polyfluoroalkyl substances (PFAS) and microplastics, are driving a major transformation in FP design. PFAS, synthetic compounds with dual hydro- and lipophobicity, have been widely employed in food packaging materials (FPMs) to impart desirable water and grease repellency. However, PFAS bioaccumulate in the human body and have been linked to multiple health effects, including immune system dysfunction, cancer, and developmental problems. The detection of microplastics in various FPMs has raised significant concerns regarding their potential migration into food and subsequent ingestion. This comprehensive review examines the current landscape of FPMs, their functions, and physicochemical properties to put into perspective why there is widespread use of PFAS and microplastics in FPMs. The review then addresses the challenges posed by PFAS and microplastics, emphasizing the urgent need for sustainable and bio-based alternatives. We highlight promising advancements in sustainable and renewable materials, including plant-derived polysaccharides, proteins, and waxes, as well as recycled and upcycled materials. The integration of these sustainable materials into active packaging systems is also examined, indicating innovations in oxygen scavengers, moisture absorbers, and antimicrobial packaging. The review concludes by identifying key research gaps and future directions, including the need for comprehensive life cycle assessments and strategies to improve scalability and cost-effectiveness. As the FP industry evolves, a holistic approach considering environmental impact, functionality, and consumer acceptance will be crucial in developing truly sustainable packaging solutions.

CIMNE-CRISPR: A novel amplification-free diagnostic for rapid early detection of African Swine Fever Virus.

(2025)

African Swine Fever Virus (ASFV) is a highly contagious pathogen with nearly 100% mortality in swine, causing severe global economic loss. Current detection methods rely on nucleic acid amplification, which requires specialized equipment and skilled operators, limiting accessibility in resource-constrained settings. To address these challenges, we developed the Covalently Immobilized Magnetic Nanoparticles Enhanced CRISPR (CIMNE-CRISPR) system. This amplification-free diagnostic system seamlessly combines target recognition, sequence-specific enrichment, and signal generation. This approach uses covalent immobilization of CRISPR-LbCas12a-crRNA complexes on Fe3O4@SiO2 core-shell magnetic nanoparticles, which improves enzyme specificity and robustness over traditional adsorption. The CIMNE-CRISPR assay reached a limit of detection (LOD) of 8.1 × 104 copies/μL and a limit of quantification (LOQ) of 4.2 × 105 copies/μL, with a dynamic range spanning 105 to 1010 copies/μL and a matrix factor of 100.29% in porcine plasma. It maintained great specificity and accurately detecting 105 copies/μL of ASFV DNA even with high mutant concentrations (1013 copies/μL). The method demonstrated decent reproducibility across different nanoparticle synthesis batches, with an RSD of 9.63% and recovery rates between 97% and 103%, and features rapid processing well-suited for field diagnostics. Overall, this system's cost-effectiveness, simplicity, and reliability highlight its potential to pave the way for advanced CRISPR-based diagnostics, particularly for diverse viral and bacterial targets in agricultural, environmental, and zoonotic disease contexts.

Cover page of Photoinduced Electron–Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments

Photoinduced Electron–Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments

(2024)

The recently synthesized monolayer fullerene network in a quasi-hexagonal phase (qHP-C60) exhibits superior electron mobility and optoelectronic properties compared to molecular fullerene (C60), making it highly promising for a variety of applications. However, the microscopic carrier dynamics of qHP-C60 remain unclear, particularly in realistic environments, which are of significant importance for applications in optoelectronic devices. Unfortunately, traditional ab initio methods are prohibitive for capturing the real-time carrier dynamics of such large systems due to their high computational cost. In this work, we present the first real-time electron-nuclear dynamics study of qHP-C60 using velocity-gauge density functional tight binding, which enables us to perform several picoseconds of excited-state electron-nuclear dynamics simulations for nanoscale systems with periodic boundary conditions. When applied to C60, qHP-C60, and their solvated counterparts, we demonstrate that water/moisture significantly increases the electron-hole recombination time in C60 but has little impact on qHP-C60. Our excited-state electron-nuclear dynamics calculations show that qHP-C60 is extremely unique and enable exploration of time-resolved dynamics for understanding excited-state processes of large systems in complex, solvated environments.

Cover page of Domain adaptation in small-scale and heterogeneous biological datasets.

Domain adaptation in small-scale and heterogeneous biological datasets.

(2024)

Machine-learning models are key to modern biology, yet models trained on one dataset are often not generalizable to other datasets from different cohorts or laboratories due to both technical and biological differences. Domain adaptation, a type of transfer learning, alleviates this problem by aligning different datasets so that models can be applied across them. However, most state-of-the-art domain adaptation methods were designed for large-scale data such as images, whereas biological datasets are smaller and have more features, and these are also complex and heterogeneous. This Review discusses domain adaptation methods in the context of such biological data to inform biologists and guide future domain adaptation research. We describe the benefits and challenges of domain adaptation in biological research and critically explore some of its objectives, strengths, and weaknesses. We argue for the incorporation of domain adaptation techniques to the computational biologists toolkit, with further development of customized approaches.