Pakistan Science News API

{
    "totalArticles": 22822,
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        {
            "id": "8f594b7531ec1ab262fa5fb4a029e9b9",
            "title": "Soft computing models for predicting polymer viscosity across wide thermal and ionic-strength conditions",
            "description": "Characterizing polymer properties under varying thermal and ionic-strength conditions is crucial across diverse fields, from materials science to environmental engineering. While experimental techniques are effective, they are often time-consuming and costly, underscoring the need for rapid, reliable computational alternatives. This study evaluates the performance of various soft computing techniques, ranging from traditional machine learning methods (MLP, SVR, RF, GBM, LGBM, and XGB) to advanced deep learning approaches (CNNs), for predicting polymer viscosity under diverse temperature and salinity conditions. The models are trained on a curated database of 4,366 experimental measurements spanning ten commercially used polymers and wide ranges of molecular weight, polymer concentration, temperature, salinity, and shear rate. Using hold-out validation, 10-fold cross-validation, and a strict unseen-polymer test, all models achieve high accuracy (test R² ≥ 0.98), with LGBM and CNN providing the best overall performance. Compared with traditional models (MLP and SVR), these methods reduce test-set error metrics by approximately 25–30%, and the CNN attains R² = 0.997 on the unseen-polymer dataset. Permutation-importance analysis identifies polymer concentration as the dominant predictor, followed by shear rate and molecular weight, in agreement with established rheological behavior. The results demonstrate that ensemble and deep learning models can serve as fast, reliable surrogates for polymer viscosity across high-temperature and high-salinity conditions, reducing experimental effort and supporting data-driven optimization of polymer selection and operating conditions.",
            "content": "Abd-El‐Aziz, A. S. et al. The next 100 years of polymer science. Macromol. Chem. Phys. 221, 2000216 (2020).\nYaragatti, N. & Patnaik, A. A review on additive manufacturing of polymers composites. Mater. Today: Proc. 44, 4150–4157 (2021).\nGbadamosi, A.... [10185 chars]",
            "url": "https://www.nature.com/articles/s41598-026-42546-4?error=cookies_not_supported&code=4f25ec8f-52c3-4e8d-88cb-798e4eecc89a",
            "image": "https://www.nature.com/static/images/favicons/nature/favicon-48x48-b52890008c.png",
            "publishedAt": "2026-04-17T06:17:44Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        },
        {
            "id": "27748bb6d03edfe0656817a91fb3b2ec",
            "title": "How Little Can You Workout Per Week And Still Build Muscle?",
            "description": "Experts explain the minimum amount of exercise you need to do to still build muscle. Here's how to build muscle only doing two weight training sessions a week.",
            "content": "5 min read\nOfficial exercise guidance from the Centers for Disease Control and Prevention says adults need at least two sessions of weight training each week for overall health. But if you’ve ever searched for a structured workout program, you might ... [6579 chars]",
            "url": "https://www.womenshealthmag.com/fitness/a71041850/how-can-you-build-muscle-with-two-workouts-a-week/",
            "image": "https://hips.hearstapps.com/hmg-prod/images/402a77a5-0c46-4ed2-b4d5-752aca9aa7a1.jpeg?crop=1xw:0.75xh;center,top&resize=1200:*",
            "publishedAt": "2026-04-16T19:44:00Z",
            "lang": "en",
            "source": {
                "id": "821424c4e5310ff2bae7ebc5077bed3e",
                "name": "Women's Health",
                "url": "https://www.womenshealthmag.com"
            }
        },
        {
            "id": "65f4b1e91fe90d75d6bb7ca85906159d",
            "title": "Researchers uncover a ‘treasure trove’ of bioactive molecules in coral reefs",
            "description": "(Santa Barbara, Calif,) — Could the next big antibiotic or cancer therapy be found on the nearest coral reef?  Researchers have found that reefs are home to a vast array of previously unknown bioactive metabolites — small biomolecules that have the biotechnological potential to provide the basis for new drugs, and a host of other products.",
            "content": "(Santa Barbara, Calif,) — Could the next big antibiotic or cancer therapy be found on the nearest coral reef? Researchers have found that reefs are home to a vast array of previously unknown bioactive metabolites — small biomolecules that have the bi... [3851 chars]",
            "url": "https://www.eurekalert.org/news-releases/1124519",
            "image": "https://www.eurekalert.org/images/EurekAlert-bluebg_Twitter_601X601.png",
            "publishedAt": "2026-04-16T17:28:12Z",
            "lang": "en",
            "source": {
                "id": "6a95657332d8b1bd75fe6a91118746ff",
                "name": "EurekAlert!",
                "url": "https://www.eurekalert.org"
            }
        }
    ]
}