Entropic Cost Research Articles

Effects of motive flow temperature on holding steam ejector Performance under Condenser temperature change by considering Entropy generation and Non-equilibrium condensation

The condenser plays a crucial role as one of the key components in a power plant, directly influencing its overall efficiency. Any alteration in the power plant’s efficiency has a substantial impact on both energy consumption and the environment. The holding steam ejector (HSE) is essential for condenser operation by creating a vacuum and effectively removing air. The primary objective of this study is to evaluation the motive flow temperature (MFT) by considering various parameters such as steam price, production entropy, air suction, and entrainment ratio (ER). The investigation focuses on different temperatures within the power plant condenser. The study examines the changes in MFT within the range of 350 ˚C to 400 ˚C, as well as the variation in condenser temperature (CDT) spanning from 47 ˚C to 67 ˚C. The results demonstrate that varying the MFT impacts the functional parameters of the HSE. As the MFT increases, there is an increasing trend in the ER. Simultaneously, there is a decreasing trend observed in the cost of steam production, production entropy, and air suction. When the MFT increased from 350 ˚C to 400 ˚C, the suction air mass flow rate for temperatures of 47 ˚C, 57 ˚C and 67 ˚C decreases by 2.22%, 2.09% and 1.99%, respectively. These results highlight the influence of temperature on various parameters, showcasing how adjustments in the MFT and CDTs can affect the flow characteristics and associated factors in the system.

The C-terminal self-binding helical peptide of human estrogen-related receptor γ can be druggably targeted by a novel class of rationally designed peptidic antagonists.

Orphan nuclear estrogen-related receptor γ (ERRγ) has been recognized as a potential therapeutic target for cancer, inflammation and metabolic disorder. The ERRγ contains a regulatory AF2 helical tail linked C-terminally to its ligand-binding domain (LBD), which is a self-binding peptide (SBP) and serves as molecular switch to dynamically regulate the receptor alternation between active and inactive states by binding to and unbinding from the AF2-binding site on ERRγ LBD surface, respectively. Traditional ERRγ modulators are all small-molecule chemical ligands that can be classified into agonists and inverse agonists in terms of their action mechanism; the agonists stabilize the AF2 in ABS site with an agonist conformation, while the inverse agonists lock the AF2 out of the site to largely abolish ERRγ transcriptional activity. Here, a class of ERRγ peptidic antagonists was described to compete with native AF2 for the ABS site, thus blocking the active state of AF2 binding to ERRγ LBD domain. Self-inhibitory peptide was derived from the SBP-covering AF2 region and we expected it can rebind potently to the ABS site by reducing its intrinsic disorder and entropy cost upon the rebinding. Hydrocarbon stapling was employed to do so, which employed an all-hydrocarbon bridge across the [i, i + 4]-anchor residue pair in the N-terminal, middle or C-terminal region of the self-inhibitory peptide. As might be expected, it is revealed that the stapled peptides are good binders of ERRγ LBD domain and can effectively compete with the native AF2 helical tail for ERRγ ABS site, which exhibit a basically similar binding mode with AF2 to the site and form diverse noncovalent interactions with the site, thus conferring stability and specificity to the domain-peptide complexes.

Anomalous thermodynamic cost of clock synchronization

Clock synchronization is critically important in positioning, navigation and timing systems. While its performance has been intensively studied in a wide range of disciplines, much less is known for the fundamental thermodynamics of clock synchronization‒what limits the precision and how to optimize the energy cost for clock synchronization. Here, we report the first experimental investigation of two stochastic autonomous clocks synchronization, unveiling the thermodynamic relation between the entropy cost and clock synchronization in an open cavity optomechanical system. Two interacting clocks are synchronized spontaneously owing to the disparate decay rates of hybrid modes by engineering the controllable cavity-mediated dissipative coupling. The measured dependence of the degree of synchronization on the overall entropy cost exhibits an unexpected non-monotonic characteristic, while the relation between the degree of synchronization and the entropy cost for the synchronization is monotonically decreasing. The investigation of transient dynamics of clock synchronization exposes a trade-off between energy and time consumption. Our results demonstrate the possibility of clock synchronization in an effective linear system, reveal the fundamental relation between clock synchronization and thermodynamics, and have a great potential for precision measurements, distributed quantum networks, and biological science.

On the difference between entropic cost and the optimal transport cost

On the difference between entropic cost and the optimal transport cost

Entropy Cost of ‘Erasure’ in Physically Irreversible Processes

A restricted form of Landauer’s principle, independent of computational considerations, is shown to hold for thermal systems by reference to the joint entropy associated with conjugate observables. It is shown that the source of the compensating entropy for irreversible physical processes is due to the ontological uncertainty attending values of such mutually incompatible observables, rather than due to epistemic uncertainty, as traditionally assumed in the information-theoretic approach. In particular, it is explicitly shown that erasure of logical (epistemic) information via reset operations is not equivalent to erasure of thermodynamic entropy, so that the traditional, information-theoretic form of Landauer’s principle is not supported by the physics. A further implication of the analysis is that, in principle, there can be no Maxwell’s Demon in the real world.

Displacement smoothness of entropic optimal transport

The function that maps a family of probability measures to the solution of the dual entropic optimal transport problem is known as the Schr¨odinger map. We prove that when the cost function is Ck+1 with k ∈ ℕ* then this map is Lipschitz continuous from the L2-Wasserstein space to the space of Ck functions. Our result holds on compact domains and covers the multi-marginal case. We also include regularity results under negative Sobolev metrics weaker than Wasserstein under stronger smoothness assumptions on the cost. As applications, we prove displacement smoothness of the entropic optimal transport cost and the well-posedness of certain Wasserstein gradient flows involving this functional, including the Sinkhorn divergence and a multi-species system.

Competing to Commit: Markets with Rational Inattention

Two homogeneous-good firms compete for a consumer’s unitary demand. The consumer is rationally inattentive and pays entropy costs to process information about firms’ offers. Compared to a collusion benchmark, competition produces two effects. As in standard models, competition puts downward pressure on prices. But, additionally, an attention effect arises: the consumer engages in trade more often. This alleviates the commitment problem that firms have when facing inattentive consumers and increases trade efficiency. For high enough attention costs, the attention effect dominates the effect on prices: firms’ profits are higher under competition than under collusion. (JEL D11, D21, D43, D83, L12)

Conformational preferences of heparan sulfate to recognize the CXCL8 dimer in aqueous medium: degree of sulfation and hydrogen bonds.

The sulfation pattern and epimerization of the long-chain sulfated polysaccharide heparan sulfate (HS) cause structural diversity and regulate various physiological and pathological processes when binding with proteins. In this work, we performed a series of molecular dynamics simulations of three variants of the octadecasaccharide HS with varying sulfation positions in aqueous medium in their free forms and in the presence of the chemokine CXCL8 dimer. The free energy of binding depicts the sulfation at the 6-O position of GlcNAc (HS6S), and both 3-O and 6-O positions of GlcNAc (HS3S6S) of HS variants are more likely to bind with the CXCL8 dimer than the triply sulfated HS2S3S6S, which is sulfated at the 2-O position of GlcUA additionally along with 3-O and 6-O positions of GlcNAc. Binding between HS and CXCL8 was driven by electrostatic and van der Waals interactions predominantly regardless of the sulfation pattern; however, unfavorable entropic contribution suppressed the interaction between HS and CXCL8. The contribution of different amino acid residues to the binding energetics suggested that basic amino acids line up the binding site of CXCL8. This study further acknowledges the role of interfacial water that is structured and bound with HS through hydrogen bonds, exhibiting differential hydrogen bond relaxation dynamics compared to when the HS molecules are free. Moreover, this study identifies that with the increase in sulfation, the HS-water hydrogen bond relaxation occurs faster with the complexation, while the reverse trend is followed in their free forms. Significant structural adaptation of the different sulfated HS molecules, as verified from the free energy landscapes generated from various reaction coordinates, root-mean-square-deviations, end-to-end distances, including ring pucker angles, dihedral flexibility, and the high conformational entropy cost arising from the glycosidic bonds, suggests that the different sulfated variants of HS undergo significant structural transformation to bind with CXCL8. The presence of a CXCL8 dimer imposes the bound forms of HS to adopt non-linear structures with skew-boat conformations. The atomistic details of the study would help in understanding the selectivity and conformational diversity, as well as the role of solvents in the recognition of CXCL8 by different sulfated variants of HS molecules.

On the Emergence of Autonomous Chemical Systems through Dissipation Kinetics.

This work addresses the kinetic requirements for compensating the entropic cost of self-organization and natural selection, thereby revealing a fundamental principle in biology. Metabolic and evolutionary features of life cannot therefore be separated from an origin of life perspective. Growth, self-organization, evolution and dissipation processes need to be metabolically coupled and fueled by low-entropy energy harvested from the environment. The evolutionary process requires a reproduction cycle involving out-of-equilibrium intermediates and kinetic barriers that prevent the reproductive cycle from proceeding in reverse. Model analysis leads to the unexpectedly simple relationship that the system should be fed energy with a potential exceeding a value related to the ratio of the generation time to the transition state lifetime, thereby enabling a process mimicking natural selection to take place. Reproducing life's main features, in particular its Darwinian behavior, therefore requires satisfying constraints that relate to time and energy. Irreversible reaction cycles made only of unstable entities reproduce some of these essential features, thereby offering a physical/chemical basis for the possible emergence of autonomy. Such Emerging Autonomous Systems (EASs) are found to be capable of maintaining and reproducing their kind through the transmission of a stable kinetic state, thereby offering a physical/chemical basis for what could be deemed an epigenetic process.

Preference for Knowledge

We examine the subjective value of gaining knowledge in a version of Savage's model for decisions under uncertainty in which the received outcome provides information about which event has obtained. Decision makers commonly value such knowledge either because they want to use it in future decisions or because they are personally interested in it. We find that in our model, the sure-thing principle and several other axioms of Savage are inconsistent with this value for knowledge about events. We provide a representation theorem for a subjective value of knowledge consisting of the sum of expected utility and a function of the information partition generated by the outcomes of an act. We characterize when the value of knowledge can be represented by a subjective value of knowledge about an information partition plus a Shannon entropy cost of processing information. Our results also provide a novel critique of the necessity of Savage's axioms for rational decisions under uncertainty.

Local and Large-Scale Conformational Dynamics in Unfolded Proteins and IDPs. II. Effect of Temperature and Internal Friction.

Internal dynamics of proteins are essential for protein folding and function. Dynamics in unfolded proteins are of particular interest since they are the basis for many cellular processes like folding, misfolding, aggregation, and amyloid formation and also determine the properties of intrinsically disordered proteins (IDPs). It is still an open question of what governs motions in unfolded proteins and whether they encounter major energy barriers. Here we use triplet-triplet energy transfer (TTET) in unfolded homopolypeptide chains and IDPs to characterize the barriers for local and long-range loop formation. The results show that the formation of short loops encounters major energy barriers with activation energies (Ea) up to 18 kJ/mol (corrected for effects of temperature on water viscosity) with very little dependence on amino acid sequence. For poly(Gly-Ser) and polySer chains the barrier decreases with increasing loop size and reaches a limiting value of 4.6 ± 0.4 kJ/mol for long and flexible chains. This observation is in accordance with the concept of internal friction encountered by chain motions due to steric effects, which is high for local motions and decreases with increasing loop size. Comparison with the results from the viscosity dependence of loop formation shows a negative correlation between Ea and the sensitivity of the reaction to solvent viscosity (α) in accordance with the Grote-Hynes theory of memory friction. The Arrhenius pre-exponential factor (A) also decreases with increasing loop size, indicating increased entropic costs for loop formation. Long-range loop formation in the investigated sequences derived from IDPs shows increased Ea and A compared with poly(Gly-Ser) and polySer chains. This increase is exclusively due to steric effects that cause additional internal friction, whereas intramolecular hydrogen bonds, dispersion forces, and charge interactions do not affect the activation parameters.

The Reversibility Paradox: Role of the Velocity Reversal Step

The reversibility, or Loschmidt paradox, is a thought experiment in which microscopic reversibility is exploited to generate an apparently spontaneous trajectory in which entropy decreases, thus violating the Second Law of Thermodynamics (SLT). To achieve this, the system is allowed to evolve from a low-entropy to a high-entropy configuration, at which point all velocities of its molecules are reversed, thus producing the desired effect. In this paper we focus on the velocity reversal step. Implementing this step requires the measurement of velocities and positions, which must be stored in a memory. Even in the case of a reversible measurement, the erasure of the stored information, necessary to reset the measuring device to its original state, has an entropy cost that offsets the entropy decrease during the reverse evolution of the system. This cost is sufficient to explain why the described procedure does not violate the SLT.

Optimal Time-Entropy Bounds and Speed Limits for Brownian Thermal Shortcuts.

By controlling the variance of the radiation pressure exerted on an optically trapped microsphere in real time, we engineer temperature protocols that shortcut thermal relaxation when transferring the microsphere from one thermal equilibrium state to another. We identify the entropic footprint of such accelerated transfers and derive optimal temperature protocols that either minimize the production of entropy for a given transfer duration or accelerate the transfer for a given entropic cost as much as possible. Optimizing the trade-off yields time-entropy bounds that put speed limits on thermalization schemes. We further show how optimization expands the possibilities for accelerating Brownian thermalization down to its fundamental limits. Our approach paves the way for the design of optimized, finite-time thermodynamics for Brownian engines. It also offers a platform for investigating fundamental connections between information geometry and finite-time processes.

Feature selection for indoor temperature prediction in large-space buildings based on transfer entropy and life cycle cost

Indoor temperature prediction as an essential reference for heating, ventilation, and air-conditioning (HVAC) system tuning has boomed in recent years, with the development of information technology. But for data-driven techniques, inputs as key factors in prediction accuracy, learning efficiency and generalization capacity, did not pay enough attention. Existing research focused only on prediction accuracy by copying previous practices in other fields like medicine and hydrology, without considering prediction horizons and economic costs, which is meaningless and even may mislead the configuration of the monitoring system, especially for large-space buildings with long-span space, diverse zones and coupling parameters. In this work, a novel hybrid feature selection technique for indoor temperature prediction was developed. Herein, transfer entropy (TE) was introduced into filter to evaluate importance of features, where Max-min TE as a gauge was defined to cope with time delays in HVAC system; Then gated recurrent network was taken in wrapper as a bridge to transform evaluations in filter into contributions to prediction; Lastly, life cycle cost was employed as a referee to judge cost-efficient alternatives. The proposed technique was validated by time-series data collected from a library and system energy consumption baseline simulated with TRNSYS to suggest optimal feature subsets under different prediction horizons.

Low entropic cost of binding confers high selectivity on an allosteric ERK2 inhibitor

Extracellular signal-regulated kinase 2 (ERK2), a mitogen-activated protein kinase (MAPK), plays an essential role in physiological cellular processes and is a drug target for treating cancers and type 2 diabetes. A previous in silico screening study focusing on an allosteric site that plays a crucial role in substrate anchoring conferred an ERK2 inhibitor (compound 1). In this report, compound 1 was found to show high selectivity toward ERK2 compared with the nearest off-target p38α MAPK, and the crystal structure revealed that compound 1 binds to the allosteric site of ERK2. Fragment molecular orbital calculations based upon this crystal structure provided the structural basis to improve potency of compound 1 derivatives. Further computational studies uncovered that the low entropic cost of binding conferred the high selectivity of compound 1 toward ERK2 over p38α MAPK. These findings demonstrate the feasibility of developing potent and selective ERK2 inhibitors.

Using Implicit-Solvent Potentials to Extract Water Contributions to Enthalpy-Entropy Compensation in Biomolecular Associations.

Biomolecular assembly typically exhibits enthalpy-entropy compensation (EEC) behavior whose molecular origin remains a long-standing puzzle. While water restructuring is believed to play an important role in EEC, its contribution to the entropy and enthalpy changes, and how these changes relate to EEC, remains poorly understood. Here, we show that water reorganization entropy/enthalpy can be obtained by exploiting the temperature dependence in effective, implicit-solvent potentials. We find that the different temperature dependencies in the hydrophobic interaction, rooted in water reorganization, result in substantial variations in the entropy/enthalpy change, which are responsible for EEC. For lower-critical-solution-temperature association, water reorganization entropy dominates the free-energy change at the expense of enthalpy; for upper-critical-solution-temperature association, water reorganization enthalpy drives the process at the cost of entropy. Other effects, such as electrostatic interaction and conformation change of the macromolecules, contribute much less to the variations in entropy/enthalpy.

Tetradehydro-Diels-Alder Reactions of Flexible Arylalkynes via Folding Inside a Molecular Cage.

The tetradehydro-Diels-Alder (TDDA) reaction is a useful transformation for the rapid assembly of polycyclic scaffolds from simple linear precursors in a single synthetic step. However, the reaction requires careful substrate design and harsh reaction conditions to overcome the inherent entropic cost for this transformation. Herein we report an efficient site-selective TDDA transformation within a self-assembled Pd6L4 cage. Despite the large size, the flexibility of the employed substrates allows for efficient encapsulation within the host cavity. The rate of thermal cyclization of the encapsulated guest was found to be greatly enhanced, and high product selectivity for an unsymmetrical substrate was observed. The efficiency of this system relies on the precise conformational control of the substrate within the confined space of the host cage.

An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs

An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs

Large-deviation theory of increasing returns.

An influential theory of increasing returns was proposed by the economist W. B. Arthur in the 1980s to explain the lock-in phenomenon between two competing commercial products. In the most simplified situation there are two competing products that gain customers according to a majority mechanism: each new customer arrives and asks which product they bought to a certain odd number of previous customers, and then buys the most shared product within this sample. It is known that one of these two companies becomes a monopoly almost surely in the limit of infinite customers. Here we consider a generalization [Dosi, Ermoliev, and Kaniovsky, J. Math. Econom. 23, 1 (1994)10.1016/0304-4068(94)90032-9] in which the new customer follows the indication of the sample with some probability, and buys the other product otherwise. Other than economy, this model can be reduced to the urn of Hill, Lane, and Sudderth, and it includes several models of physical interest as special cases, such as the Elephant Random Walk, Friedman's urn, and other generalized urn models. We provide a large-deviation analysis of this model at the sample-path level, and we provide a formula that allows us to find the most likely trajectories followed by the market share variable. Interestingly, in the parameter range where the lock-in phase is expected, we observe a whole region of convergence where the entropy cost is sublinear. We also find a nonlinear differential equationfor the cumulant-generating function of the market share variable, which can be studied with a suitable perturbation theory.

Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions

In this article, we study the problem of multiple stochastic agents interacting in a dynamic game scenario with continuous state and action spaces. We define a new notion of stochastic Nash equilibrium for boundedly rational agents, which we call the entropic cost equilibrium (ECE). We show that ECE is a natural extension to multiple agents of maximum entropy optimality for a single agent. We solve both the “forward” and “inverse” problems for the multi-agent ECE game. For the forward problem, we provide a Riccati algorithm to compute closed-form ECE feedback policies for the agents, which are exact in the linear-quadratic-gaussian case. We give an iterative variant to find locally ECE feedback policies for the nonlinear case. For the inverse problem, we present an algorithm to infer the cost functions of the multiple interacting agents given noisy, boundedly rational input and state trajectory examples from agents acting in an ECE. The effectiveness of our algorithms is demonstrated in a simulated multi-agent collision avoidance scenario, and with data from the INTERACTION traffic dataset. In both cases, we show that, by taking into account the agents' game theoretic interactions using our algorithm, a more accurate model of agents' costs can be learned, compared with standard inverse optimal control methods.