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DOE OSTI2021

Relationship between microstructure evolution and properties enhancement of carbon nanotubes‐filled polybutylene terephthalate/polypropylene blends induced by thermal annealing

Abstract Thermal annealing induced microstructure evolution and properties enhancement of polybutylene terephthalate/polypropylene/carbon nanotubes (PBT/PP/CNTs) nanocomposites was methodically investigated. The electrical conductive PBT/PP/CNTs nanocomposites with a low percolation threshold were obtained by simple melt blending due to the selective location of the CNTs in PBT phase and the formation of the double percolation structure. Thermal annealing further remarkably decreased the volume resistivity of the nanocomposites, with the maximum reduction of seven orders of magnitude. Scanning electron microscope observation and rheology tests demonstrated that the relatively large CNTs agglomerates were redistributed to build more homogeneous CNTs networks after annealing. The phase coalescence during annealing promoted the formation of the more perfect co‐continuous structure. These phenomena helped to enhance the electrical conductivity of the nanocomposites. Flexural properties of the nanocomposites were also enhanced after annealing, which might be due to the more effective stress transfer between the polymer and CNTs induced by the reconstructed CNTs networks. The nanocomposites obtained in this study possess excellent electrical and mechanical properties, which can be applied to the fields of sensors, electromagnetic interference shielding, anti‐static materials, and so forth.

Shang, Mengyao↗

DOE OSTI2023

Large Enhancements in Optical and Piezoelectric Properties in Ferroelectric Zn 1- x Mg x O Thin Films through Engineering Electronic and Ionic Anharmonicities

Multifunctionality as a paradigm requires materials exhibiting multiple superior properties. Integrating second-order optical nonlinearity and large bandgap with piezoelectricity can, for example, enable broadband, strain-tunable photonics. Though very different phenomena at distinct frequencies, both second-order optical nonlinearity and piezoelectricity are third-rank polar tensors present only in acentric crystal structures. However, simultaneously enhancing both phenomena is highly challenging since it involves competing effects with tradeoffs. Recently, a large switchable ferroelectric polarization of ≈80 μC cm –2 was reported in Zn 1-x Mg x O films. Here, ferroelectric Zn 1-x Mg x O is demonstrated to be a platform that hosts simultaneously a 30% increase in the electronic bandgap, a 50% enhancement in the second harmonic generation (SHG) coefficients, and a near 200% improvement in the piezoelectric coefficients over pure ZnO. These enhancements are shown to be due to a 400% increase in the electronic anharmonicity and a ≈200% decrease in the ionic anharmonicity with Mg substitution. Precisely controllable periodic ferroelectric domain gratings are demonstrated down to 800 nm domain width, enabling ultraviolet quasi-phase-matched optical harmonic generation as well as domain-engineered piezoelectric devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Enhancing Crystallization in Hybrid Perovskite Solar Cells Using Thermally Conductive 2D Boron Nitride Nanosheet Additive

Controlling crystallization and grain growth is crucial for realizing highly efficient hybrid perovskite solar cells (PSCs). In this work, enhanced PSC photovoltaic performance and stability by accelerating perovskite crystallization and grain growth via 2D hexagonal boron nitride (hBN) nanosheet additives incorporated into the active perovskite layer are demonstrated. Specifically, in situ X-ray scattering and infrared thermal imaging during the perovskite annealing process revealed the highly thermally conductive hBN nanosheets promoted the phase conversion and grain growth in the perovskite layer by facilitating a more rapid and spatially uniform temperature rise within the perovskite film. Complementary structural, physicochemical, and electrical characterizations further showed that the hBN nanosheets formed a physical barrier at the perovskite grain boundaries and the interfaces with charge transport layers, passivating defects, and retarding ion migration. As a result, the power conversion efficiency of the PSC is improved from 17.4% to 19.8%, along with enhanced device stability, retaining ≈90% of the initial efficiency even after 500 h ambient air storage. Here, the results not only highlight 2D hBN as an effective additive for PSCs but also suggest enhanced thermal transport as one of the pathways for improved PSC performance by 2D material additives in general.

2D materials↗

DOE OSTI2024

CO 2 Uptake and Stability Enhancement in Vinyltrimethoxysilane‐Treated SBA‐15 Solid Amine‐Based Sorbents

Abstract Silica‐supported amine absorbents, including materials produced by tethering aminosilanes or infusion of poly(ethyleneimine), represent a promising class of materials for CO 2 capture applications, including direct air and point source capture. Various silica surface treatments and functionalization strategies are explored to enhance stability and CO 2 uptake in amine‐based solid sorbent systems. Here, the synthesis and characterization of novel vinyltrimethoxysilane‐treated Santa Barbara Amorphous‐15 (SBA‐15) supports and the corresponding enhancement in CO 2 uptake compared to various SBA‐15‐based control supports are presented. The relationship between CO 2 diffusion and amine efficiency in these systems is explored using a previously reported kinetic model. The synthesized materials are characterized with CO 2 and H 2 O isotherms, diffuse reflectance infrared Fourier transform spectroscopy, 1 H T 1 – T 2 relaxation correlation NMR, and rapid thermal cycling experiments. The novel support materials are shown to enable high amine efficiencies, approaching a fourfold improvement over standard SBA‐15‐supported amines, while simultaneously exhibiting excellent stability when cycled rapidly under humid conditions. As the poly(ethyleneimine) loadings are held constant across the various samples, enhancements in CO 2 uptake are attributed to differences in the way the poly(ethyleneimine) interacts with the support surface.

Vallace, Anthony↗

DOE OSTI2026

Strangeness enhancement at its extremes: multiple (multi-)strange hadron production in pp collisions at $\sqrt{s}=5.02$ TeV

The probability to observe a specific number of strange and multi-strange hadrons (nS), denoted as P(nS), is measured by ALICE at midrapidity (|y| < 0.5) in $$\sqrt{s}=5.02$$ TeV proton-proton (pp) collisions, dividing events into several multiplicity-density classes. Exploiting, for the first time, a technique based on counting the number of strange-particle candidates event-by-event, this measurement allows one to extend the study of strangeness production beyond the mean of the distribution. This constitutes a new test bench for production mechanisms, probing events with a large imbalance between strange and non-strange content. The analysis of a large-statistics data sample makes it possible to extract P(nS) up to a maximum nS of 7 for $${\text{K}}_{\text{S}}^{0}$$, 5 for Λ and $$\overline{\Lambda }$$, 4 for Ξ− and $${\overline{\Xi } }^{+}$$, and 2 for Ω− and $${\overline{\Omega } }^{+}$$. From this, the probability of producing strange hadron multiplets per event is calculated, thereby enabling the extension of the study of strangeness enhancement to extreme situations where several strange quarks hadronize in a single event at midrapidity. Moreover, comparing hadron combinations with different u and d quark compositions and equal overall s quark content, the contribution to the enhancement pattern coming from non-strangeness related mechanisms is isolated. The results are compared with state-of-the-art phenomenological models implemented in commonly used Monte Carlo event generators, including PYTHIA 8 Monash 2013, PYTHIA 8 with QCD-based Color Reconnection and Rope Hadronization (QCD-CR + Ropes), and EPOS LHC, which incorporates both partonic interactions and hydrodynamic evolution. These comparisons show that the new approach dramatically enhances the sensitivity to the different underlying physics mechanisms modeled by each generator.

Abualrob, I J↗

DOE OSTI2024

Nano-enhanced solid-state hydrogen storage: Balancing discovery and pragmatism for future energy solutions

Nanomaterials have revolutionized the battery industry by enhancing energy storage capacities and charging speeds, and their application in hydrogen (H 2 ) storage likewise holds strong potential, though with distinct challenges and mechanisms. H 2 is a crucial future zero-carbon energy vector given its high gravimetric energy density, which far exceeds that of liquid hydrocarbons. However, its low volumetric energy density in gaseous form currently requires storage under high pressure or at low temperature. This review critically examines the current and prospective landscapes of solid-state H 2 storage technologies, with a focus on pragmatic integration of advanced materials such as metal-organic frameworks (MOFs), magnesium-based hybrids, and novel sorbents into future energy networks. These materials, enhanced by nanotechnology, could significantly improve the efficiency and capacity of H 2 storage systems by optimizing H 2 adsorption at the nanoscale and improving the kinetics of H 2 uptake and release. We discuss various H 2 storage mechanisms—physisorption, chemisorption, and the Kubas interaction—analyzing their impact on the energy efficiency and scalability of storage solutions. The review also addresses the potential of “smart MOFs”, single-atom catalyst-doped metal hydrides, MXenes and entropy-driven alloys to enhance the performance and broaden the application range of H 2 storage systems, stressing the need for innovative materials and system integration to satisfy future energy demands. High-throughput screening, combined with machine learning algorithms, is noted as a promising approach to identify patterns and predict the behavior of novel materials under various conditions, significantly reducing the time and cost associated with experimental trials. In closing, we discuss the increasing involvement of various companies in solid-state H 2 storage, particularly in prototype vehicles, from a techno-economic perspective. In conclusion, this forward-looking perspective underscores the necessity for ongoing material innovation and system optimization to meet the stringent energy demands and ambitious sustainability targets increasingly in demand.

25 ENERGY STORAGE↗

DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

DOE OSTI2020

Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass

Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Enhanced mobility of cations and anions in the redox state: The polaronium mechanism

Hugely enhanced slow-ion diffusivity has been widely observed under extreme redox conditions and for unclear reasons. Aided by first-principles calculations on model systems of ZrO 2 , CeO 2 , BaTiO 3 and Li 4/3 Mn 2/3 O 2 , here we successfully explained the intriguing phenomenon by a polaronium mechanism. We found a polaronium, defined as a transitory complex of a polaronic electron or hole and a migrating counterion, becomes highly mobile when the counterion comes from a d 0 or f 0 cation (e.g., Zr 4+ , Ti 4+ and Ce 4 ) or a p 6 anion (e.g., O 2- ) in the host compound. Upon a redox reaction, the complex attains a d 1 /f 1 or p 5 configuration, which spontaneously forms because it is favored by an electron-phonon interaction (manifest as the Jahn-Teller effect in high symmetry systems) that enables local relaxation and lowers the system energy. Here our calculations found such interaction reaching its peak at the saddle point where the local environment is softest, so soft that it allows a reorientation of the anisotropic d/f/p orbital to minimize the electron repulsion locally. Since the complex may dissolve after a successful ion-migration event, the redox electron/hole can be recycled to form another free-radical-like polaronium elsewhere, thereby enhancing ion migration repeatedly. The proposed polaronium mechanism, which also operates in ceramics doped with mixed-valence cations, is most relevant under dynamic and extreme thermal/field/irradiation conditions where extra electrons/holes are abundantly generated by non-equilibrium redox reactions. For such operations, some with emerging applications, our diffusion-enhancing mechanism may provide new theoretical insight to help understand their material/microstructure stability and performance.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Remarkable enhancement in thermal conductivity of stainless-steel leveraging metal composite via laser powder bed fusion: 316L-Cu composite

This work aimed to significantly enhance the thermal conductivity of the SS matrix by fabricating a metal composite SS-Cu system utilizing a laser powder bed fusion process. The impact of process parameters on the microstructure of SS-Cu samples is investigated. Here, the processing and post-processing factors that influence the effective thermal conductivity of the metal composite SS-Cu system are discussed. Then, the effective thermal conductivity and mechanical properties of the SS-Cu composite are measured at room temperature and operating temperature of 300 °C. The optimized laser powder bed fusion parameters led to low Marangoni convection, high cooling rate, greater macro-segregation, and higher thermal conductivity values albeit at the cost of ductility in SS-Cu metal composite likely due to the presence of the unmelted powder particles. As-printed SS-60 vol % Cu and annealed SS-60 vol % Cu had 2.5X and 6.6X thermal conductivity enhancement, respectively. During annealing, phase separation, partial melting of Cu, and formation of a continuous network of Cu surrounding SS play a key role in enhancing the thermal conductivity of the SS-Cu metal composite structure.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Effects of Cr/Zircaloy-4 coating qualities for enhanced accident tolerant fuel cladding

Cr-coated zirconium alloys represent a modern approach to enhance cladding safety during accident scenarios. Two high-power impulse magnetron sputtered Cr-coated Zry-4 systems were subjected to simulated loss-of-coolant accident conditions to investigate cladding performance. The first Cr-coating (4.8 µm thick) was deposited onto Zry-4 cladding and exhibited through-thickness cracking while the second Cr-coating (6.8 µm thick) was deposited with improved deposition parameters onto polished Zry-4 and exhibited no cracking. During burst testing, the coating with a higher density of defects failed to consistently reduce oxidation and exhibited similar burst behavior as Zry-4. In contrast, the second Cr-coating reduced ZrO 2 formation through formation of Cr 2 O 3 and displayed enhanced burst temperatures by ~80 °C compared to Zry-4. Utilizing an empirical relation for burst behavior of zirconium alloys, the 6.8 µm Cr/Zry-4 system displayed enhanced burst temperatures equivalent to an effective 0.464 mm increase in Zry-4 wall thickness, highlighting the value of continuous Cr coatings for accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Multifractally-enhanced superconductivity in thin films

The multifractal superconducting state originates from the interplay of Anderson localization and interaction effects. In this article we overview the recent theory of the superconductivity enhancement by multifractality and extend it to describe the spectral properties of superconductors on the scales of the order of the superconducting gap. Specifically, using the approach based on renormalization group within the nonlinear sigma model, we develop the theory of a multifractal superconducting state in thin films. We derive a modified Usadel equation that incorporates the interplay of disorder and interactions at energy scales larger than the spectral gap and study the effect of such an interplay on the low-energy physics. We determine the spectral gap at zero temperature which occurs to be proportional to the multifractally enhanced superconducting transition temperature. The modified Usadel equation results in the disorder-averaged density of states that, near the spectral gap, resembles the one obtained in the model of a spatially random superconducting order parameter. We reveal strong mesoscopic fluctuations of the local density of states in the superconducting state. Such strong mesoscopic fluctuations imply that the interval of energies in which the superconducting gap establishes is parametrically large in systems with multifractally-enhanced superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗

DOE OSTI2020

Multimodal imaging and machine learning to enhance microscope images of shale

A machine learning based image processing workflow is presented to enhance shale source rock microscopic images obtained using diverse imaging platforms. Images were acquired from a 30 μm diameter cylindrical Vaca Muerta shale sample using both nondestructive Transmission X-Ray Microscopy (TXM, alternately referred to as nano computed tomography) and destructive Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM). Output cross-sectional images from each modality were aligned using a combination of manual and automated registration techniques to create a registered image dataset. We then apply this dataset for two image processing tasks: prediction of image cross sections with SEM-like resolution from nondestructive TXM data and repair of charged region artifacts (localized accumulation of electrons) within SEM images. The image processing algorithms for both tasks use deep learning models, specifically image-to-image Convolutional Neural Networks (CNNs) and conditional Generative Adversarial Networks (cGANs). In the image enhancement tasks, we are able to achieve significant qualitative and quantitative improvement in TXM images. Here, the best model reaches an average Peak Signal to Noise Ratio (PSNR) of 15.8 dB. Conditioning on TXM data is also shown to reduce artifacts from SEM charging, achieving an average PSNR of 25.8 dB. Furthermore, our results suggest that properly trained and validated networks are capable of significant enhancement of images obtained using nondestructive techniques, thereby improving interpretation of two- and three-dimensional images while preserving samples for future use.

58 GEOSCIENCES↗

DOE OSTI2025

Mixed lipid bilayers enable enhanced stability and activity retention of Lipase A in low-pH environments

Lipase A (LipA) from Bacillus subtilis is a versatile and industrially relevant enzyme, but its activity is compromised under acidic conditions due to aggregation and deactivation. In this study, we investigated the use of mixed lipid bilayers to stabilize and improve activity retention of LipA at low pH. Attachment to lipid bilayers, particularly those containing cationic lipids, greatly enhanced the long-term stability of LipA in acidic conditions while also leading to improvements in activity. Tethering to cationic bilayers not only shifted the apparent pH activity profile toward more acidic conditions, but also significantly enhanced activity retention upon incubation at pH 6. Notably, this protective effect persisted even without direct tethering, indicating that reversible, non-covalent interactions with the bilayer surface are sufficient for long-term stability. Circular dichroism further revealed that the secondary structure of LipA was retained, while dynamic light scattering suggested that activity loss in solution was primarily due to aggregation of the native state. Together, these findings support a model in which lipid bilayers mitigate aggregation and stabilize LipA through transient interactions and electrostatic modulation of the local surface environment. Furthermore, this approach exemplifies a simple, tether-free strategy for enhancing enzyme performance in acidic or destabilizing conditions, with implications for biocatalysis, biosensing, and therapeutic delivery.

Biocatalysis↗

DOE OSTI2020

Stimuli-responsive petroleum cement composite with giant expansion and enhanced mechanical properties

Shrinkage, as an inherent property of cement during the curing process, has been a concern in the oil & gas industry for centuries. Therefore, expansive cement has been studied for many decades, primarily through incorporation of expansive additives. Nevertheless, traditional expansive additives are not able to achieve the required expansive ratio or maintain a good mechanical property for the cement composite at extreme underground condition. Accordingly, a new generation of expansive additive, which not only has the required expansion, but also work at the downhole high temperature and high pressure environment, and maintain or even enhance the mechanical property, is highly desired. In this work, a high enthalpy storage shape memory polymer (SMP) as a new class of expansive additive is investigated. It is found that the cement composite achieves 1.4% circumferential expansion by only 6% by weight of SMP additives. The compressive strength and flexural strength are also enhanced at the same time, which is hardly achievable by other expansive additives with the same concertation. Good pumpability is also proved by rheological study. The mechanism controlling the enhanced properties is reveled through morphological study and element mapping analysis at the SMP/cement interface.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Optimal operation of multi-plant steam district heating systems for enhanced efficiency and sustainability

Despite their crucial role in supplying heat and power to universities, industries, and healthcare facilities, many steam-based district heating systems rely on outdated control methods. Among these, multi-central plant districts are particularly challenging due to the complexities of coordinating multiple plants, optimizing load distributions, and managing system downtime. In response, new operational strategies are developed to enhance the efficiency and sustainability of steam districts while utilizing existing resources. These strategies include reducing plant operational pressure without compromising the reliable supply to buildings and optimizing load allocation across multiple plants. The load allocation considers boiler part-load efficiency, runtime, network losses, and building pressure set points, and is compared with traditional multi-boiler controls. To support this exploration, new dynamic Modelica models are developed. In addition, methods to reduce modeling complexities are incorporated, enhancing their suitability for practical applications. A holistic district-wide analysis using a real university case study demonstrates a 4.7% fuel savings by lowering boiler operational pressure from 900 kPa to 600 kPa, along with a 13.3% reduction in condensation losses across the distribution network. Furthermore, the load allocation approach results in a 13.1% reduction in fuel consumption during peak winter periods and 15.3% during shoulder periods, with corresponding decreases in carbon emissions and fuel costs. This approach can also save maintenance costs by reducing the boiler runtime by 49.6%. In conclusion, this research underscores the benefits of retrofitting aging steam district heating systems, offering immediate operational improvements by enhancing efficiency, meeting regulatory compliance, and extending infrastructure lifespans while delaying costly overhauls.

24 POWER TRANSMISSION AND DISTRIBUTION↗