Browsing by Subject "Thermodynamics"

Fracture is a common phenomenon in engineering applications. Many types of fracture exist, including, but not limited to, brittle fracture, quasi-brittle fracture, cohesive fracture, and ductile fracture. Predicting fracture has been one of the most challenging research topics in computational mechanics. The variational treatment of fracture and its associated phase-field regularization have been employed with great success for modeling fracture in brittle materials. Extending the variational statement to describe other types of fracture and coupled field phenomena has proven less straightforward. Main challenges that remain include how to best construct a total potential that is both mathematically sound and physically admissible, and how to properly describe the coupling between fracture and other phenomena.

The research presented in this dissertation aims at addressing the aforementioned challenges. A variational framework is proposed to describe fracture in general dissipative solids. In essence, the variational statement is extended to account for large deformation kinematics, inelastic deformation, dissipation mechanisms, dynamic effects, and thermal effects. The proposed variational framework is shown to be consistent with conservations and laws of thermodynamics, and it provides guidance and imposes restrictions on the construction of models for coupled field problems. Within the proposed variational framework, several models are instantiated to address practical engineering problems. A brittle and quasi-brittle fracture model is used to investigate fracture evolution in polycrystalline materials; a cohesive fracture model is applied to revisit soil desiccation; a novel ductile fracture model is proposed and successfully applied to simulate some challenging benchmark problems; and a creep fracture model is developed to simulate the spallation of oxide scale on high temperature heat exchangers.

Abundant and widely available solar energy is one possible solution to the increasing demands for clean energy. The Thermodynamics and Sustainable Energy Laboratory (T-SEL) in Duke University has been dedicated to investigating methods to harness solar energy. Hybrid Solar System (HSS) is one of the promising methods to use solar energy, as it absorbs sunlight to produce hydrogen, which then can electrically power equipment through fuel cells. Hydrogen is produced through a biofuel reforming process, which occurs at a high temperature (over 700℃ for methane). Methods to design a high-temperature solar selective coating are investigated in this thesis.

The solar irradiance spectrum was assumed to be the same as Air Mass (AM) 1.5. A transfer-matrix method was adopted in this work to calculate the optical properties of the NREL #6, a design of nine-layer solar selective coating. Based on the design of NREL #6 coating, Differential Evolution (DE) algorithm was introduced to optimize this design. Two objective functions were considered: selectivity-oriented function and efficiency-oriented function, yielding the design of Revision #1 and Revision #2 respectively. The results showed a high selectivity (around 13) with low efficiency (66.6%) in Revision #1 and a high efficiency (82.6%) with moderate selectivity (around 9) in Revision #2.

The advancement of mass spectrometry-based protein stability profiling measurements within the past twenty years has led to the development of a suite of approaches that enables the evaluation of protein folding stability on a broad range of biological mixtures with varying complexity. These approaches include chemical and thermal denaturation techniques (SPROX and TPP, respectively) as well as proteolysis strategies such as limited proteolysis (LiP) and pulse proteolysis (PP) which have all been extensively used and evaluated for small molecule protein target discovery applications. However, the capabilities of these methods have yet to be fully evaluated in the characterization of disease phenotypes and other biological events such as post-translational modifications and RNA-protein interactions. A major focus of the work included in this dissertation has been the comparative analysis of the above techniques for the characterization of biological phenotypes. The application and comparative analysis of the above techniques to the characterization of RNA-protein interactions is also described.

RNA recognition frequently results in conformational changes that optimize

intermolecular binding. As a consequence, the overall binding affinity of RNA

to its binding partners depends not only on the intermolecular interactions

formed in the bound state, but also on the energy cost associated with changing

the RNA conformational distribution. Measuring these conformational penalties

is however challenging because bound RNA conformations tend to have equilibrium

populations in the absence of the binding partner that fall outside detection by

conventional biophysical methods.

In this work we employ as a model system HIV-1 TAR RNA and its interaction with

the ligand argininamide (ARG), a mimic of TAR’s cognate protein binding partner,

the transactivator Tat. We use NMR chemical shift perturbations (CSP) and NMR

relaxation dispersion (RD) in combination with Bayesian inference to develop a

detailed thermodynamic model of coupled conformational change and ligand

binding. Starting from a comprehensive 12-state model of the equilibrium, we

estimate the energies of six distinct detectable thermodynamic states that are

not accessible by currently available methods.

Our approach identifies a minimum of four RNA intermediates that differ in terms

of the TAR conformation and ARG-occupancy. The dominant bound TAR conformation

features two bound ARG ligands and has an equilibrium population in the absence

of ARG that is below detection limit. Consequently, even though ARG binds to TAR

with an apparent overall weak affinity ($\Kdapp \approx \SI{0.2}{\milli

\Molar}$), it binds the prefolded conformation with a $K_{\ch{d}}$ in the nM

range. Our results show that conformational penalties can be major determinants

of RNA-ligand binding affinity as well as a source of binding cooperativity,

with important implications for a predictive understanding of how RNA is

recognized and for RNA-targeted drug discovery.

Additionally, we describe in detail the development of our approach for fitting

complex ligand binding data to mathematical models using Bayesian

inference. We provide crucial benchmarks and demonstrate the

robustness of our fitting approach with the goal of application

to other systems. This thesis aims to provide new insight into

the dynamics of RNA-ligand recognition as well as provide new

methods that can be applied to achieve this goal.

Many of the biological roles of proteins are modulated through protein-ligand interactions, making proteins important targets for drug therapies and diagnostic imaging probes. The discovery of novel ligands for a protein of interest often relies on the use of high throughput screening (HTS) technologies designed to detect protein-ligand binding. The basis of one such technology is a recently reported mass spectrometry-based assay termed SUPREX (stability of unpurified proteins from rates of H/D exchange). SUPREX is a technique that uses H/D exchange and MALDI-mass spectrometry for the measurement of protein stabilities and protein-ligand binding affinities. The single-point SUPREX assay is an abbreviated form of SUPREX that is capable of detecting protein-ligand interactions in a high throughput manner by exploiting the change in protein stability that occurs upon ligand binding.

This work is focused on the development and application of high throughput SUPREX protocols for the detection of protein-ligand binding. The first step in this process was to explore the scope of SUPREX for the analysis of non-two-state proteins to determine whether this large subset of proteins would be amenable to SUPREX analyses. Studies conducted on two model proteins, Bcl-xL and alanine:glyoxylate aminotransferase, indicate that SUPREX can be used to detect and quantify the strength of protein-ligand binding interactions in non-two-state proteins.

The throughput and efficiency of a high throughput SUPREX protocol (i.e., single-point SUPREX) was also evaluated in this work. As part of this evaluation, cyclophilin A, a protein target of diagnostic and therapeutic significance, was screened against the 880-member Prestwick Chemical Library to identify novel ligands that might be useful as therapeutics or imaging agents for lung cancer. This screening not only established the analytical parameters of the assay, but it revealed a limitation of the technique: the efficiency of the assay is highly dependent on the precision of each mass measurement, which generally decreases as protein size increases.

To overcome this limitation and improve the efficiency and generality of the assay, a new SUPREX protocol was developed that incorporated a protease digestion step into the single-point SUPREX protocol. This new protocol was tested on two model proteins, cyclophilin A and alanine:glyoxylate aminotransferase, and was found to result in a significant improvement in the efficiency of the SUPREX assay in HTS applications. This body of work resulted in advancements in the use of SUPREX for high throughput applications and laid the groundwork for future HTS campaigns on target proteins of medical significance.

Detection and quantification of protein-ligand binding interactions is extremely important for understanding interactions that occur in biological systems. Since traditional techniques for characterizing these types of interactions cannot be performed in complex systems such as cell lysates, a series of energetics-based techniques that are capable of assessing protein stability and measuring ligand binding affinities have been developed to overcome some of the limitations of previous techniques. Now that the capabilities of the energetics-based techniques have been exhibited in model systems, the false-positive rates of the techniques, the range of biological questions to which the techniques can be addressed, and the use of the techniques to discover novel interactions in unknown systems remained to be shown. The Stability of Proteins from Rates of Oxidation (SPROX) technique and the Pulse Proteolysis (PP) technique were applied to a wide range of biological questions in both yeast and human cell lysates to evaluate the scope of these experimental workflows. The false-positive rate of iTRAQ-SPROX protein target discovery on orbitrap mass spectrometer systems was determined to be < 0.8 %. The iTRAQ-SPROX technique was successfully applied to the discovery of both known and novel protein-protein, protein-ATP, and protein-drug interactions, leading to the quantification of protein-ligand binding affinities in each of these studies. In the pursuit of discovering geldanamycin protein interactors, the use of iTRAQ-SPROX and SILAC-PP in combination was determined to be advantageous for confirming protein-ligand interactions since the techniques utilize different quantitation strategies that are subject to separate technical errors in quantitation. Finally, the iTRAQ-SPROX and SILAC-PP techniques were used to evaluate the interactions of manassantin A in a human cell lysate. In this work, a previously unknown protein target of manassantin A, Filamin A, was detected as a hit protein using both the iTRAQ-SPROX and SILAC-PP protocols. The work completed in this dissertation has expanded the understanding of the limitations of energetics-based techniques and shown that biological replicate analyses are essential to confirm ligand interactions with novel protein targets.

Understanding and predicting the behavior of porous media holds unexpected potential for technological advances toward resilience and sustainability. Indeed, these materials are ubiquitous and exhibit a rich palette of processes, both multiphysics and multiscales, which are potential sources of inspiration for engineering design. Along these lines, the intended outcomes of this dissertation are twofold: 1) predicting the resilience of porous media and 2) enhancing behaviors of interest in these materials that could inspire sustainable metamaterials design. Geomaterials, a particularly complex subclass of porous media, will be the primary focus.

This program starts by laying down a general theoretical framework, based on non-equilibrium thermodynamics and differential geometry. A generalized relaxation equation is derived to ensure systematic satisfaction of the second law of thermodynamics. This is associated with a variational framework, based on Fermat's principle, that generalizes that of Onsager, in order to reckon with gyroscopic forces - that is, nondissipative but nonconservative forces.

This framework is then applied to modeling the microstructure of porous media, upon which the behavior of these materials largely depends. To that aim, phase-field modeling is employed to capturing the exact microstructural geometry, in association with digital rock physics based on microtomographic imaging. This effort is required to model processes too complex to be described by a unique constitutive law, such as pressure solution, as studied first in this dissertation. Therein, a microstructural viscosity is derived to capture the kinetics of processes, which is crucial for modeling geomaterials, since the associated timescales span from the engineering to the geological times.

Upon narrowing down the complexity of porous media processes, it is possible to extract the necessary and sufficient microstructural information through morphometry. From running phase-field simulations on a large variety of synthetic microstructures, a general morphometric strength law is inferred, which builds upon seminal works on metals and ceramics. This morphometric framework is applied to predicting the strength of various porous materials, including rocks and bones, from their microstructural geometry.

Protein biomarkers can facilitate the diagnosis of many diseases such as cancer and they can be important for the development of effective therapeutic interventions. Current large-scale biomarker discovery and disease state characterization studies have largely focused on the global analysis of gene and protein expression levels, which are not directly tied to function. Moreover, functionally significant proteins with similar expression levels go undetected in the current paradigm of using gene and protein expression level analyses for protein biomarker discovery. Protein-ligand interactions play an important role in biological processes. A number of diseases such as cancer are reported to have altered protein interaction networks. Current understanding of biophysical properties and consequences of altered protein interaction network in disease state is limited due to the lack of reproducible and high-throughput methods to make such measurements. Thermodynamic stability measurements can report on a wide range of biologically significant phenomena (e.g., point mutations, post-translational modifications, and new or altered binding interactions with cellular ligands) associated with proteins in different disease states. Investigated here is the use of thermodynamic stability measurements to probe the altered interaction networks and functions of proteins in disease states. This thesis outlines the development and application of mass spectrometry based methods for making proteome-wide thermodynamic measurements of protein stability in multifactorial complex diseases such as cancer. Initial work involved the development of SILAC-SPROX and SILAC-PP approaches for thermodynamic stability measurements in proof-of-concept studies with two test ligands, CsA and a non-hydrolyzable adenosine triphosphate (ATP) analogue, adenylyl imidodiphosphate (AMP-PNP). In these proof-of-principle studies, known direct binding target of CsA, cyclophilin A, was successfully identified and quantified. Similarly a number of known and previously unknown ATP binding proteins were also detected and quantified using these SILAC-based energetics approaches.

Subsequent studies in this thesis involved thermodynamic stability measurements of proteins in the breast cancer cell line models to differentiate disease states. Using the SILAC-SPROX, ~800 proteins were assayed for changes in their protein folding behavior in three different cell line models of breast cancer including the MCF-10A, MCF-7, and MDA-MB-231 cell lines. Approximately, 10-12% of the assayed proteins in the comparative analyses performed here exhibited differential stability in cell lysates prepared from the different cell lines. Thermodynamic profiling differences of 28 proteins identified with SILAC-SPROX strategy in MCF-10A versus MCF-7 cell line comparison were also confirmed with SILAC-PP technique. The thermodynamic analyses performed here enabled the non-tumorigenic MCF-10A breast cell line to be differentiated from the MCF-7 and MDA-MB-231 breast cancer cell lines. Differentiation of the less invasive MCF-7 breast cancer cell line from the more highly invasive MDA-MB-231 breast cancer cell line was also possible using thermodynamic stability measurements. The differentially stabilized protein hits in these studies encompassed those with a wide range of functions and protein expression levels, and they included a significant fraction (~45%) with similar expression levels in the cell line comparisons. These proteins created novel molecular signatures to differentiate the cancer cell lines studied here. Our results suggest that protein folding and stability measurements complement the current paradigm of expression level analyses for biomarker discovery and help elucidate the molecular basis of disease.

Virtually all biologically relevant functions and processes are mediated by non-covalent, molecular recognition events, demonstrating astonishingly diverse affinities and specificities. Despite extensive research, the origin of affinity and specificity in aqueous solution - specifically the relationship between ligand binding thermodynamics and structure - remains remarkably obscure and is further complicated in the context of multivalent interactions. Multivalency describes the combinatorial interaction of multiple discrete epitopes across multiple binding surfaces where the association is considered as the sum of contributions from each epitope and the consequences of multivalent ligand assembly. Gaining the insight necessary to predictably influence biological processes with novel therapeutics begins with an understanding of the molecular basis of solution-phase interactions, and the thermodynamic parameters that follow from those interactions. Here we continue our efforts to understand the basis of aqueous affinity and the nature of multivalent additivity.

Multivalent additivity is the foundation of fragment-based drug discovery, where small, low affinity ligands are covalently assembled into a single high affinity inhibitor. Such systems are ideally suited for investigating the thermodynamic consequences of multivalent ligand assembly. In the first part of this work, we report the design and synthesis of a fragment-based ligand series for the Grb2-SH2 protein and thermodynamic evaluation of the low affinity ligand fragments compared to the intact, high affinity inhibitor by single and double displacement isothermal titration calorimetry (ITC). Interestingly, our investigations reveal positively cooperative multivalent additivity - a binding free energy of the full ligand greater than the sum of its constituent fragments - that is largely enthalpic in origin. These results contradict the most common theory of multivalent affinity enhancement arising from a "savings" in translational and rotational entropy. The Grb2-SH2 system reported here is the third distinct molecular system in which we have observed enthalpically driven multivalent enhancement of affinity.

Previous research by our group into similar multivalent affinity enhancements in protein-carbohydrate systems - the so-called "cluster glycoside effect" - revealed that evaluation of multivalent interactions in the solution-phase is not straightforward due to the accessibility of two disparate binding motifs: intramolecular, chelate-type binding and intermolecular, aggregative binding. Although a number of powerful techniques for evaluation of solution-phase multivalent interactions have been reported, these bulk techniques are often unable to differentiate between binding modes, obscuring thermodynamic interpretation. In the second part of this work, we report a competitive equilibrium approach to Molecular Recognition Force Microscopy (MRFM) for evaluation of ligand binding at the single-molecule level with potential to preclude aggregative associations. We have optimized surface functionalization strategies and MRFM experimental protocols to evaluate the binding constant of surface- and tip-immobilized single stranded DNA epitopes. Surprisingly, the monovalent affinity of an immobilized species is in remarkable agreement with the solution-phase affinity, suggesting the competitive equilibrium MRFM approach presents a unique opportunity to investigate the nature of multivalent additivity at the single molecule level.

Advancements in inelastic X-ray and neutron scattering techniques nowadays allow for the nearly complete measurement of anharmonic phonon behaviors near phase transitions. It is difficult to explain the observed effects of phonon anharmonicity without using first-principles calculations, for instance to obtain renormalized second- order and higher-order force-constants. Moreover, pump-probe experiments can now resolved femtosecond atomic dynamics by using an ultrafast laser pulse to excite materials out of equilibrium and then track the Bragg or diffuse intensities with a time-resolved pulse of X-rays. However, the response of materials to the laser pulse is complex, necessitating ab initio calculations to achieve a physical understanding of the processes underlying pump-probe experiments. Using ab initio calculations, this thesis investigates the significance of phonon anharmonicity in the thermal phase transition, as well as the lattice dynamics of photo-excited crystals, specifically in VO2 and SnS/SnSe single crystals.

The thermal transport behavior and thermodynamics of VO2, which exhibits a well-studied metal-insulator transition (MIT), are both heavily influenced by its anharmonic lattice dynamics. However, the precise evolution of its phonon dispersions over the MIT has remained unknown. Strong phonon softening and damping in rutile VO2 were revealed by our inelastic X-ray scattering (IXS) measurements. We reproduced the phonon softening and phonon damping in rutile VO2, as well as their absence in M1 VO2 and rutile TiO2, using first-principles simulations. Our simulations reveal that the anti-ferroelectric distortions are important to understand the phonon softening in rutile VO2, and the large mean square displacement contributes to the extensive damping of its low-energy phonon branches.

In addition to the thermally-induced transition, photo-excitation can also drive the insulator-to-metal transition (IMT) of VO2 on an ultrafast time scale. Using X-ray pump-probe (XPP) total scattering and Megaelectron-volt ultrafast electron diffraction (MeV-UED), we investigated the lattice dynamics upon photo-excitation. We used MeV-UED to track the Bragg intensity and structural response of M1 VO2 at laser fluences below saturation. Below the saturation laser fluence, our ab initio calculations reproduce the initial structural deformation towards the rutile structure. We also use ab initio calculations to show the dominant factor that causes the structural deformation below the saturation fluence. Moreover, we used XPP total scattering to track both the Bragg and diffuse scattering intensities of VO2 across the IMT at laser fluences above saturation. Above the saturation fluence, our ab initio calculations reproduce the evolvement of Bragg intensity and diffuse intensity. The photo-induced phase transition was found to proceed as an ultrafast disordering phase transition. The disordering IMT is enabled by the flattening of the potential energy surface following photo-excitation, which quickly enlarges the phase space for atomic motions.

Using inelastic neutron scattering (INS) and high-resolution Raman spectroscopy, we investigated the lattice dynamics across the high-temperature Pnma-Cmcm phase transition of SnS (and SnSe). We performed first-principles simulations to understand the strong phonon anharmonicity and its impact on lattice thermal conductivity. INS detected a drastic softening of the TA phonon branch in the Cmcm phase and a broad reconstruction of the low frequency TA and TO phonon modes in the Pnma phase, revealing high directionality of the bonding strength and anharmonicity. Our first-principles simulations use renormalized force-constants to reproduce the phonon reconstruction and explain the phonon anharmonicity, demonstrating that the substantial phonon softening has a direct impact on the lattice thermal conductivity, beyond perturbative scattering, primarily by decreasing phonon lifetime, through the reconstruction of scattering phase space.

Free-electron based laser pump-probe measurements of Pnma SnSe investigated the atomic displacement directions after photo-excitation. This thesis investigates the photo-excitation mechanism of SnSe using different methods and emphasizes the significance of selecting and comparing different simulation methods when interpreting experimental results. The distribution of electrons after photo-excitation inspires different schemes to approximate the complex photo-excitation process. Following photo-excitation, hole doping and constrained-DFT methods predict a structural distortion from Pnma to Immm, whereas electronic heating predicts a structural distortion from Pnma to Cmcm. In addition to the well-known electronic structure instability in the Pnma-Cmcm phase transition, the electronic structure changes from Pnma to Immm are also examined. This study further demonstrates the importance of first-principles modeling to understand the atomic dynamics following photo-excitation.