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一杯凍檸水溶化,冰當中嘅 H2O 分子變成,並且散開。

粵拼soeng1英文entropy)係統計力學熱力學常用嘅一個概念,係一個熱力學系統具有嘅外延性質(外延性質係會同個系統嘅大細成比例嘅物理性質)。考慮 呢個數值:是但搵個熱力學系統,佢會有一啲宏觀性質(例如溫度壓力等),而個系統有若干個可能嘅微狀態(microstate;「粒子 A 喺位置 X 而粒子 B 喺位置 Y...」、「粒子 A 喺位置 Y 而粒子 B 喺位置 X...」等等),能夠同個系統啲宏觀性質吻合嘅微狀態數量就係 ;熵係 函數,即係話熵反映咗「已知個系統嘅宏觀性質如此,個系統有幾多個可能嘅微狀態」。假設每個微狀態都一樣噉有可能發生(概率一樣),個系統嘅熵可以用以下呢條式計出嚟[1][2]

當中 kB波茲曼常數(Boltzmann constant)[3]

喺實際應用上, 嘅數值通常都極之大:根據估計,一舊喺室溫同大氣壓力之下、容量 20 公升氣體總共有大約 N&000000082000-80-66.0000006×1023 噉多粒氣體分子(阿伏加德羅常數;Avogadro number),而呢舊氣體嘅 數值( 反映「已知呢舊氣體有 N&000000082000-80-66.0000006×1023 粒分子,可能嘅微狀態數量」)會更加大[3]

根據熱力學第二定律(The second law of thermodynamics),一個封閉系統(closed system)當中嘅熵永遠唔會跌,衹有可能維持不變或者升。熱力學第二定律意味住,搵個封閉系統,隨住時間過去,佢內部嘅粒子同能量頂櫳維持唔郁,而喺現實多數會慢慢走位(可能嘅微狀態數量上升),會漸漸趨向熱力學平衡(thermodynamic equilibrium)-熵數值最大化嘅狀態。好似生物等嘅非封閉系統(會同周圍環境傳能量)可以內部熵下降,但噉做實會引致佢周圍環境嘅熵升,而且升至少同一樣噉多。因為噉,宇宙嘅總熵依然會升[4]。順帶一提,如果宇宙最後真係完全變成熱力學平衡,根據物理學家計算,宇宙最後會變成溫度分佈完全平均,而且溫度接近絕對零度攝氏零下 273.15 度)嘅空間,唔會再有任何作功,更加唔會有生命-而呢個情況就係假想中嘅熱寂(heat death)[5]

此外,熵仲同訊息有住密切嘅啦掕:熵由帶隨機性嘅微狀態數量決定,所以熵會反映「知道咗個系統嘅宏觀性質,需要幾多訊息先可以講明個系統處於乜嘢物理狀態」;因為呢個緣故,外行人會話熵表達咗個系統有幾「亂」-一個系統嘅熵愈高,就表示觀察者對佢知道得愈少(有愈多不確定嘅可能性),所以就愈「亂」。而對物理意義上嘅熵嘅考量的確同訊息論(information theory)有關(不過訊息論當中講嘅「」係一個同物理熵唔同嘅概念)[6][7]

睇埋[編輯]

參考[編輯]

  • Adam, Gerhard; Otto Hittmair (1992). Wärmetheorie. Vieweg, Braunschweig. ISBN 978-3-528-33311-9.
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  • Ben-Naim, Arieh (2007). Entropy Demystified. World Scientific. ISBN 978-981-270-055-1.
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  • Chang, Raymond (1998). Chemistry (6th ed.). New York: McGraw Hill. ISBN 978-0-07-115221-1.
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  • Dugdale, J. S. (1996). Entropy and its Physical Meaning (2nd ed.). Taylor and Francis (UK); CRC (US). ISBN 978-0-7484-0569-5.
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[編輯]

  1. Ligrone, Roberto (2019). "Glossary". Biological Innovations that Built the World: A Four-billion-year Journey through Life & Earth History. Entropy. Springer. p. 478.
  2. Baierlein, Ralph (2003). Thermal Physics. Cambridge University Press.
  3. 3.0 3.1 Richard Feynman (1970). The Feynman Lectures on Physics Vol I. Addison Wesley Longman.
  4. Zohuri, Bahman (2016). Dimensional Analysis Beyond the Pi Theorem. Springer. p. 111.
  5. Adams, Fred C.; Laughlin, Gregory (1997). "A dying universe: the long-term fate and evolution of astrophysical objects". Reviews of Modern Physics. 69 (2): 337–72.
  6. Rietman, Edward A.; Tuszynski, Jack A. (2017). "Thermodynamics & Cancer Dormancy: A Perspective". In Wang, Yuzhuo; Crea, Francesco (eds.). Tumor Dormancy & Recurrence (Cancer Drug Discovery and Development). Introduction: Entropy & Information. Humana Press. p. 63.
  7. Brooks, D. R., Collier, J., Maurer, B. A., Smith, J. D., & Wiley, E. O. (1989). Entropy and information in evolving biological systems. Biology and Philosophy, 4(4), 407-432.

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